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ORCIDJaime G. Carbonell
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- affiliation: Carnegie Mellon University, Language Technologies Institute, Pittsburgh, PA, USA
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2020 – today
- 2021
[c257]Vidhisha Balachandran, Artidoro Pagnoni, Jay Yoon Lee, Dheeraj Rajagopal, Jaime G. Carbonell, Yulia Tsvetkov:
StructSum: Summarization via Structured Representations. EACL 2021: 2575-2585- [c256]Petar Stojanov, Zijian Li, Mingming Gong, Ruichu Cai, Jaime G. Carbonell, Kun Zhang:
Domain Adaptation with Invariant Representation Learning: What Transformations to Learn? NeurIPS 2021: 24791-24803 - 2020
- [j55]Shuyan Zhou, Shruti Rijhwani, John Wieting, Jaime G. Carbonell, Graham Neubig:
Improving Candidate Generation for Low-resource Cross-lingual Entity Linking. Trans. Assoc. Comput. Linguistics 8: 109-124 (2020) - [c255]Shriphani Palakodety
, Ashiqur R. KhudaBukhsh, Jaime G. Carbonell:
Voice for the Voiceless: Active Sampling to Detect Comments Supporting the Rohingyas. AAAI 2020: 454-462 - [c254]Kyungtae Lim, Jay Yoon Lee, Jaime G. Carbonell, Thierry Poibeau:
Semi-Supervised Learning on Meta Structure: Multi-Task Tagging and Parsing in Low-Resource Scenarios. AAAI 2020: 8344-8351 - [c253]Shruti Rijhwani, Shuyan Zhou, Graham Neubig, Jaime G. Carbonell:
Soft Gazetteers for Low-Resource Named Entity Recognition. ACL 2020: 8118-8123 - [c252]Daegun Won, Peter J. Jansen, Jaime G. Carbonell:
Minimizing and Recovering from the Effect of Concept Drift via Feature Selection. ECAI 2020: 1611-1617 - [c251]Shriphani Palakodety, Ashiqur R. KhudaBukhsh, Jaime G. Carbonell:
Hope Speech Detection: A Computational Analysis of the Voice of Peace. ECAI 2020: 1881-1889 - [c250]Shriphani Palakodety, Ashiqur R. KhudaBukhsh, Jaime G. Carbonell:
Mining Insights from Large-Scale Corpora Using Fine-Tuned Language Models. ECAI 2020: 1890-1897 - [c249]Shriphani Palakodety, Ashiqur R. KhudaBukhsh, Jaime G. Carbonell:
The Refugee Experience Online: Surfacing Positivity Amidst Hate. ECAI 2020: 2925-2926 - [c248]Zirui Wang, Sanket Vaibhav Mehta, Barnabás Póczos, Jaime G. Carbonell:
Efficient Meta Lifelong-Learning with Limited Memory. EMNLP (1) 2020: 535-548 - [c247]Zirui Wang, Jiateng Xie, Ruochen Xu, Yiming Yang, Graham Neubig, Jaime G. Carbonell:
Cross-lingual Alignment vs Joint Training: A Comparative Study and A Simple Unified Framework. ICLR 2020 - [c246]Xinyi Wang, Hieu Pham, Paul Michel, Antonios Anastasopoulos, Jaime G. Carbonell, Graham Neubig:
Optimizing Data Usage via Differentiable Rewards. ICML 2020: 9983-9995 - [c245]Ashiqur R. KhudaBukhsh, Shriphani Palakodety, Jaime G. Carbonell:
Harnessing Code Switching to Transcend the Linguistic Barrier. IJCAI 2020: 4366-4374 - [i52]Ashiqur R. KhudaBukhsh, Shriphani Palakodety, Jaime G. Carbonell:
Harnessing Code Switching to Transcend the Linguistic Barrier. CoRR abs/2001.11258 (2020) - [i51]Vidhisha Balachandran, Artidoro Pagnoni, Jay Yoon Lee, Dheeraj Rajagopal, Jaime G. Carbonell, Yulia Tsvetkov:
StructSum: Incorporating Latent and Explicit Sentence Dependencies for Single Document Summarization. CoRR abs/2003.00576 (2020) - [i50]Shuyan Zhou, Shruti Rijhwani, John Wieting, Jaime G. Carbonell, Graham Neubig:
Improving Candidate Generation for Low-resource Cross-lingual Entity Linking. CoRR abs/2003.01343 (2020) - [i49]Shruti Rijhwani, Shuyan Zhou, Graham Neubig, Jaime G. Carbonell:
Soft Gazetteers for Low-Resource Named Entity Recognition. CoRR abs/2005.01866 (2020) - [i48]Zirui Wang, Sanket Vaibhav Mehta, Barnabás Póczos, Jaime G. Carbonell:
Efficient Meta Lifelong-Learning with Limited Memory. CoRR abs/2010.02500 (2020)
2010 – 2019
- 2019
- [j54]Ashiqur R. KhudaBukhsh, Jaime G. Carbonell:
Expertise drift in referral networks. Auton. Agents Multi Agent Syst. 33(5): 645-671 (2019) - [c244]Jay Yoon Lee, Sanket Vaibhav Mehta, Michael L. Wick, Jean-Baptiste Tristan, Jaime G. Carbonell:
Gradient-Based Inference for Networks with Output Constraints. AAAI 2019: 4147-4154 - [c243]Shruti Rijhwani, Jiateng Xie, Graham Neubig, Jaime G. Carbonell:
Zero-Shot Neural Transfer for Cross-Lingual Entity Linking. AAAI 2019: 6924-6931 - [c242]Zihang Dai, Zhilin Yang, Yiming Yang, Jaime G. Carbonell, Quoc Viet Le, Ruslan Salakhutdinov:
Transformer-XL: Attentive Language Models beyond a Fixed-Length Context. ACL (1) 2019: 2978-2988 - [c241]Junjie Hu, Mengzhou Xia, Graham Neubig, Jaime G. Carbonell:
Domain Adaptation of Neural Machine Translation by Lexicon Induction. ACL (1) 2019: 2989-3001 - [c240]Petar Stojanov, Mingming Gong, Jaime G. Carbonell, Kun Zhang:
Low-Dimensional Density Ratio Estimation for Covariate Shift Correction. AISTATS 2019: 3449-3458 - [c239]Petar Stojanov, Mingming Gong, Jaime G. Carbonell, Kun Zhang:
Data-Driven Approach to Multiple-Source Domain Adaptation. AISTATS 2019: 3487-3496 - [c238]Zirui Wang, Zihang Dai, Barnabás Póczos, Jaime G. Carbonell:
Characterizing and Avoiding Negative Transfer. CVPR 2019: 11293-11302 - [c237]Aditi Chaudhary, Jiateng Xie, Zaid Sheikh, Graham Neubig, Jaime G. Carbonell:
A Little Annotation does a Lot of Good: A Study in Bootstrapping Low-resource Named Entity Recognizers. EMNLP/IJCNLP (1) 2019: 5163-5173 - [c236]Harsh Jhamtani, Sanket Vaibhav Mehta, Jaime G. Carbonell, Taylor Berg-Kirkpatrick:
Learning Rhyming Constraints using Structured Adversaries. EMNLP/IJCNLP (1) 2019: 6024-6030 - [c235]Zhilin Yang, Zihang Dai, Yiming Yang, Jaime G. Carbonell, Ruslan Salakhutdinov, Quoc V. Le:
XLNet: Generalized Autoregressive Pretraining for Language Understanding. NeurIPS 2019: 5754-5764 - [c234]Ashiqur R. KhudaBukhsh, Jaime G. Carbonell:
Toward Reciprocity-Aware Distributed Learning in Referral Networks. PRICAI (2) 2019: 121-135 - [i47]Eduard H. Hovy, Jaime G. Carbonell, Hans Chalupsky, Anatole Gershman, Alex Hauptmann, Florian Metze, Teruko Mitamura, Zaid Sheikh, Ankit Dangi, Aditi Chaudhary, Xianyang Chen, Xiang Kong, Bernie Huang, Salvador Medina, Hector Liu, Xuezhe Ma, Maria Ryskina, Ramon Sanabria, Varun Gangal:
OPERA: Operations-oriented Probabilistic Extraction, Reasoning, and Analysis. TAC 2019 - [i46]Zihang Dai, Zhilin Yang, Yiming Yang, Jaime G. Carbonell, Quoc V. Le, Ruslan Salakhutdinov:
Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context. CoRR abs/1901.02860 (2019) - [i45]Aditi Chaudhary, Siddharth Dalmia, Junjie Hu, Xinjian Li, Austin Matthews, Aldrian Obaja Muis, Naoki Otani, Shruti Rijhwani, Zaid Sheikh, Nidhi Vyas, Xinyi Wang, Jiateng Xie, Ruochen Xu, Chunting Zhou, Peter J. Jansen, Yiming Yang, Lori S. Levin, Florian Metze, Teruko Mitamura, David R. Mortensen, Graham Neubig, Eduard H. Hovy, Alan W. Black, Jaime G. Carbonell, Graham Horwood, Shabnam Tafreshi, Mona T. Diab, Efsun Sarioglu Kayi, Noura Farra, Kathleen R. McKeown:
The ARIEL-CMU Systems for LoReHLT18. CoRR abs/1902.08899 (2019) - [i44]Junjie Hu, Mengzhou Xia, Graham Neubig, Jaime G. Carbonell:
Domain Adaptation of Neural Machine Translation by Lexicon Induction. CoRR abs/1906.00376 (2019) - [i43]Zhilin Yang, Zihang Dai, Yiming Yang, Jaime G. Carbonell, Ruslan Salakhutdinov, Quoc V. Le:
XLNet: Generalized Autoregressive Pretraining for Language Understanding. CoRR abs/1906.08237 (2019) - [i42]Aditi Chaudhary, Elizabeth Salesky, Gayatri Bhat, David R. Mortensen, Jaime G. Carbonell, Yulia Tsvetkov:
CMU-01 at the SIGMORPHON 2019 Shared Task on Crosslinguality and Context in Morphology. CoRR abs/1907.10129 (2019) - [i41]Aditi Chaudhary, Jiateng Xie, Zaid Sheikh, Graham Neubig, Jaime G. Carbonell:
A Little Annotation does a Lot of Good: A Study in Bootstrapping Low-resource Named Entity Recognizers. CoRR abs/1908.08983 (2019) - [i40]Harsh Jhamtani, Sanket Vaibhav Mehta, Jaime G. Carbonell, Taylor Berg-Kirkpatrick:
Learning Rhyming Constraints using Structured Adversaries. CoRR abs/1909.06743 (2019) - [i39]Shriphani Palakodety, Ashiqur R. KhudaBukhsh, Jaime G. Carbonell:
Kashmir: A Computational Analysis of the Voice of Peace. CoRR abs/1909.12940 (2019) - [i38]Shriphani Palakodety, Ashiqur R. KhudaBukhsh, Jaime G. Carbonell:
Voice for the Voiceless: Active Sampling to Detect Comments Supporting the Rohingyas. CoRR abs/1910.03206 (2019) - [i37]Zirui Wang, Jiateng Xie, Ruochen Xu, Yiming Yang, Graham Neubig, Jaime G. Carbonell:
Cross-lingual Alignment vs Joint Training: A Comparative Study and A Simple Unified Framework. CoRR abs/1910.04708 (2019) - [i36]Xinyi Wang, Hieu Pham, Paul Michel, Antonios Anastasopoulos, Graham Neubig, Jaime G. Carbonell:
Optimizing Data Usage via Differentiable Rewards. CoRR abs/1911.10088 (2019) - 2018
- [j53]Ashiqur R. KhudaBukhsh, Jaime G. Carbonell, Peter J. Jansen:
Robust learning in expert networks: a comparative analysis. J. Intell. Inf. Syst. 51(2): 207-234 (2018) - [j52]Liu Yang, Steve Hanneke, Jaime G. Carbonell:
Bounds on the minimax rate for estimating a prior over a VC class from independent learning tasks. Theor. Comput. Sci. 716: 124-140 (2018) - [c233]Ashiqur R. KhudaBukhsh, Jaime G. Carbonell:
Expertise Drift in Referral Networks. AAMAS 2018: 425-433 - [c232]Abdelwahab Bourai, Jaime G. Carbonell:
I Know What You Don't Know: Proactive Learning through Targeted Human Interaction. AAMAS 2018: 479-487 - [c231]Jiateng Xie, Zhilin Yang, Graham Neubig, Noah A. Smith, Jaime G. Carbonell:
Neural Cross-lingual Named Entity Recognition with Minimal Resources. EMNLP 2018: 369-379 - [c230]Jesse Dunietz, Jaime G. Carbonell, Lori S. Levin:
DeepCx: A transition-based approach for shallow semantic parsing with complex constructional triggers. EMNLP 2018: 1691-1701 - [c229]Aditi Chaudhary, Chunting Zhou, Lori S. Levin, Graham Neubig, David R. Mortensen, Jaime G. Carbonell:
Adapting Word Embeddings to New Languages with Morphological and Phonological Subword Representations. EMNLP 2018: 3285-3295 - [c228]Sanket Vaibhav Mehta, Jay Yoon Lee, Jaime G. Carbonell:
Towards Semi-Supervised Learning for Deep Semantic Role Labeling. EMNLP 2018: 4958-4963 - [c227]Daegun Won, Peter J. Jansen, Jaime G. Carbonell:
Temporal transfer learning for drift adaptation. ESANN 2018 - [c226]Ashiqur R. KhudaBukhsh, Jaime G. Carbonell:
Endorsement in Referral Networks. EUMAS 2018: 172-187 - [c225]George Philipp, Dawn Song, Jaime G. Carbonell:
Gradients explode - Deep Networks are shallow - ResNet explained. ICLR (Workshop) 2018 - [c224]Ashiqur R. KhudaBukhsh, Jong Woo Hong, Jaime G. Carbonell:
Market-Aware Proactive Skill Posting. ISMIS 2018: 323-332 - [c223]Zirui Wang, Jaime G. Carbonell:
Towards More Reliable Transfer Learning. ECML/PKDD (2) 2018: 794-810 - [i35]Eduard H. Hovy, Taylor Berg-Kirkpatrick, Jaime G. Carbonell, Hans Chalupsky, Anatole Gershman, Alexander G. Hauptmann, Florian Metze, Teruko Mitamura, Aditi Chaudhary, Xianyang Chen, Bernie Po-Yao Huang, Hector Zhengzhong Liu, Xuezhe Ma, Shruti Palaskar, Dheeraj Rajagopal, Maria Ryskina, Ramon Sanabria:
OPERA: Operations-oriented Probabilistic Extraction, Reasoning, and Analysis. TAC 2018 - [i34]George Philipp, Jaime G. Carbonell:
The Nonlinearity Coefficient - Predicting Overfitting in Deep Neural Networks. CoRR abs/1806.00179 (2018) - [i33]Zirui Wang, Jaime G. Carbonell:
Towards more Reliable Transfer Learning. CoRR abs/1807.02235 (2018) - [i32]Aditi Chaudhary, Chunting Zhou, Lori S. Levin, Graham Neubig, David R. Mortensen, Jaime G. Carbonell:
Adapting Word Embeddings to New Languages with Morphological and Phonological Subword Representations. CoRR abs/1808.09500 (2018) - [i31]Sanket Vaibhav Mehta, Jay Yoon Lee, Jaime G. Carbonell:
Towards Semi-Supervised Learning for Deep Semantic Role Labeling. CoRR abs/1808.09543 (2018) - [i30]Jiateng Xie, Zhilin Yang, Graham Neubig, Noah A. Smith, Jaime G. Carbonell:
Neural Cross-Lingual Named Entity Recognition with Minimal Resources. CoRR abs/1808.09861 (2018) - [i29]Shruti Rijhwani, Jiateng Xie, Graham Neubig, Jaime G. Carbonell:
Zero-shot Neural Transfer for Cross-lingual Entity Linking. CoRR abs/1811.04154 (2018) - [i28]Zirui Wang, Zihang Dai, Barnabás Póczos, Jaime G. Carbonell:
Characterizing and Avoiding Negative Transfer. CoRR abs/1811.09751 (2018) - 2017
- [j51]Meghana Kshirsagar, Keerthiram Murugesan, Jaime G. Carbonell, Judith Klein-Seetharaman:
Multitask Matrix Completion for Learning Protein Interactions Across Diseases. J. Comput. Biol. 24(6): 501-514 (2017) - [j50]Luís Marujo, Ricardo Ribeiro, Anatole Gershman, David Martins de Matos, João Paulo Neto, Jaime G. Carbonell:
Event-based summarization using a centrality-as-relevance model. Knowl. Inf. Syst. 50(3): 945-968 (2017) - [j49]Jaime G. Carbonell, Jade Goldstein:
The Use of MMR, Diversity-Based Reranking for Reordering Documents and Producing Summaries. SIGIR Forum 51(2): 209-210 (2017) - [j48]Jesse Dunietz, Lori S. Levin, Jaime G. Carbonell:
Automatically Tagging Constructions of Causation and Their Slot-Fillers. Trans. Assoc. Comput. Linguistics 5: 117-133 (2017) - [c222]Sz-Rung Shiang, Stephanie Rosenthal, Anatole Gershman, Jaime G. Carbonell, Jean Oh:
Vision-Language Fusion for Object Recognition. AAAI 2017: 4603-4610 - [c221]Jesse Dunietz, Lori S. Levin, Jaime G. Carbonell:
The BECauSE Corpus 2.0: Annotating Causality and Overlapping Relations. LAW@ACL 2017: 95-104 - [c220]Jay Yoon Lee, Michael L. Wick, Jean-Baptiste Tristan, Jaime G. Carbonell:
Enforcing Output Constraints via SGD: A Step Towards Neural Lagrangian Relaxation. AKBC@NIPS 2017 - [c219]Ashiqur R. KhudaBukhsh, Jaime G. Carbonell, Peter J. Jansen:
Incentive Compatible Proactive Skill Posting in Referral Networks. EUMAS/AT 2017: 29-43 - [c218]George Philipp, Jaime G. Carbonell:
Nonparametric Neural Networks. ICLR (Poster) 2017 - [c217]Seungwhan Moon, Jaime G. Carbonell:
Completely Heterogeneous Transfer Learning with Attention - What And What Not To Transfer. IJCAI 2017: 2508-2514 - [c216]Keerthiram Murugesan, Jaime G. Carbonell:
Self-Paced Multitask Learning with Shared Knowledge. IJCAI 2017: 2522-2528 - [c215]Ashiqur R. KhudaBukhsh, Jaime G. Carbonell, Peter J. Jansen:
Robust Learning in Expert Networks: A Comparative Analysis. ISMIS 2017: 292-301 - [c214]Keerthiram Murugesan, Jaime G. Carbonell:
Active Learning from Peers. NIPS 2017: 7008-7017 - [c213]Keerthiram Murugesan, Jaime G. Carbonell:
Multi-Task Multiple Kernel Relationship Learning. SDM 2017: 687-695 - [i27]Andrew Hsi, Jaime G. Carbonell, Yiming Yang:
CMU CS Event TAC-KBP2017 Event Argument Extraction System. TAC 2017 - [i26]Keerthiram Murugesan, Jaime G. Carbonell:
Self-Paced Multitask Learning with Shared Knowledge. CoRR abs/1703.00977 (2017) - [i25]Keerthiram Murugesan, Jaime G. Carbonell, Yiming Yang:
Co-Clustering for Multitask Learning. CoRR abs/1703.00994 (2017) - [i24]Adams Wei Yu, Qihang Lin, Ruslan Salakhutdinov, Jaime G. Carbonell:
Normalized Gradient with Adaptive Stepsize Method for Deep Neural Network Training. CoRR abs/1707.04822 (2017) - [i23]Jay Yoon Lee, Michael L. Wick, Jean-Baptiste Tristan, Jaime G. Carbonell:
Enforcing Constraints on Outputs with Unconstrained Inference. CoRR abs/1707.08608 (2017) - [i22]Guoqing Zheng, Yiming Yang, Jaime G. Carbonell:
Convolutional Normalizing Flows. CoRR abs/1711.02255 (2017) - [i21]Guoqing Zheng, Yiming Yang, Jaime G. Carbonell:
Likelihood Almost Free Inference Networks. CoRR abs/1711.08352 (2017) - [i20]George Philipp, Jaime G. Carbonell:
Nonparametric Neural Networks. CoRR abs/1712.05440 (2017) - [i19]George Philipp, Dawn Song, Jaime G. Carbonell:
Gradients explode - Deep Networks are shallow - ResNet explained. CoRR abs/1712.05577 (2017) - 2016
- [j47]Hanxiao Liu, Wanli Ma, Yiming Yang, Jaime G. Carbonell:
Learning Concept Graphs from Online Educational Data. J. Artif. Intell. Res. 55: 1059-1090 (2016) - [j46]Luís Marujo, Wang Ling, Ricardo Ribeiro, Anatole Gershman, Jaime G. Carbonell, David Martins de Matos, João Paulo Neto:
Exploring events and distributed representations of text in multi-document summarization. Knowl. Based Syst. 94: 33-42 (2016) - [c212]Ashiqur R. KhudaBukhsh, Jaime G. Carbonell, Peter J. Jansen:
Proactive Skill Posting in Referral Networks. Australasian Conference on Artificial Intelligence 2016: 585-596 - [c211]Andrew Hsi, Yiming Yang, Jaime G. Carbonell, Ruochen Xu:
Leveraging Multilingual Training for Limited Resource Event Extraction. COLING 2016: 1201-1210 - [c210]Ashiqur R. KhudaBukhsh, Peter J. Jansen, Jaime G. Carbonell:
Distributed Learning in Expert Referral Networks. ECAI 2016: 1620-1621 - [c209]Devendra Singh Chaplot, Yiming Yang, Jaime G. Carbonell, Kenneth R. Koedinger:
Data-driven Automated Induction of Prerequisite Structure Graphs. EDM 2016: 318-323 - [c208]Akash Bharadwaj, David R. Mortensen, Chris Dyer, Jaime G. Carbonell:
Phonologically Aware Neural Model for Named Entity Recognition in Low Resource Transfer Settings. EMNLP 2016: 1462-1472 - [c207]Ashiqur R. KhudaBukhsh, Jaime G. Carbonell, Peter J. Jansen:
Proactive-DIEL in Evolving Referral Networks. EUMAS/AT 2016: 148-156 - [c206]Guoqing Zheng, Yiming Yang, Jaime G. Carbonell:
Efficient Shift-Invariant Dictionary Learning. KDD 2016: 2095-2104 - [c205]Jeffrey Flanigan, Chris Dyer, Noah A. Smith, Jaime G. Carbonell:
Generation from Abstract Meaning Representation using Tree Transducers. HLT-NAACL 2016: 731-739 - [c204]Keerthiram Murugesan, Hanxiao Liu, Jaime G. Carbonell, Yiming Yang:
Adaptive Smoothed Online Multi-Task Learning. NIPS 2016: 4296-4304 - [c203]Seungwhan Moon, Jaime G. Carbonell:
Proactive Transfer Learning for Heterogeneous Feature and Label Spaces. ECML/PKDD (2) 2016: 706-721 - [c202]Meghana Kshirsagar, Jaime G. Carbonell, Judith Klein-Seetharaman, Keerthiram Murugesan:
Multitask Matrix Completion for Learning Protein Interactions Across Diseases. RECOMB 2016: 53-64 - [c201]Jeffrey Flanigan, Chris Dyer, Noah A. Smith, Jaime G. Carbonell:
CMU at SemEval-2016 Task 8: Graph-based AMR Parsing with Infinite Ramp Loss. SemEval@NAACL-HLT 2016: 1202-1206 - [i18]Andrew Hsi, Jaime G. Carbonell, Yiming Yang:
CMU CS Event TAC-KBP2016 Event Argument Extraction System. TAC 2016 - [i17]Keerthiram Murugesan, Jaime G. Carbonell:
Multi-Task Multiple Kernel Relationship Learning. CoRR abs/1611.03427 (2016) - 2015
- [c200]Dishan Gupta, Jaime G. Carbonell, Anatole Gershman, Steve Klein, David Miller:
Unsupervised Phrasal Near-Synonym Generation from Text Corpora. AAAI 2015: 2253-2259 - [c199]Meghana Kshirsagar, Sam Thomson, Nathan Schneider, Jaime G. Carbonell, Noah A. Smith, Chris Dyer:
Frame-Semantic Role Labeling with Heterogeneous Annotations. ACL (2) 2015: 218-224 - [c198]Luís Marujo, Wang Ling, Isabel Trancoso, Chris Dyer, Alan W. Black, Anatole Gershman, David Martins de Matos, João Paulo da Silva Neto, Jaime G. Carbonell:
Automatic Keyword Extraction on Twitter. ACL (2) 2015: 637-643 - [c197]Jesse Dunietz, Lori S. Levin, Jaime G. Carbonell:
Annotating Causal Language Using Corpus Lexicography of Constructions. LAW@NAACL-HLT 2015: 188-196 - [c196]Liu Yang, Steve Hanneke, Jaime G. Carbonell:
Bounds on the Minimax Rate for Estimating a Prior over a VC Class from Independent Learning Tasks. ALT 2015: 270-284 - [c195]Öznur Tastan, Yanjun Qi, Jaime G. Carbonell, Judith Klein-Seetharaman:
Refining Literature Curated Protein Interactions Using Expert Opinions. Pacific Symposium on Biocomputing 2015: 318-329 - [c194]Luís Marujo, Ricardo Ribeiro, David Martins de Matos, João Paulo Neto, Anatole Gershman, Jaime G. Carbonell:
Extending a Single-Document Summarizer to Multi-Document: a Hierarchical Approach. *SEM@NAACL-HLT 2015: 176-181 - [c193]Yiming Yang, Hanxiao Liu, Jaime G. Carbonell, Wanli Ma:
Concept Graph Learning from Educational Data. WSDM 2015: 159-168 - [i16]Andrew Hsi, Jaime G. Carbonell, Yiming Yang:
Modeling Event Extraction via Multilingual Data Sources. TAC 2015 - [i15]Liu Yang, Steve Hanneke, Jaime G. Carbonell:
Bounds on the Minimax Rate for Estimating a Prior over a VC Class from Independent Learning Tasks. CoRR abs/1505.05231 (2015) - [i14]Luís Marujo, Ricardo Ribeiro, David Martins de Matos, João Paulo Neto, Anatole Gershman, Jaime G. Carbonell:
Extending a Single-Document Summarizer to Multi-Document: a Hierarchical Approach. CoRR abs/1507.02907 (2015) - [i13]Luís Marujo, José Portelo, Wang Ling, David Martins de Matos, João Paulo Neto, Anatole Gershman, Jaime G. Carbonell, Isabel Trancoso, Bhiksha Raj:
Privacy-Preserving Multi-Document Summarization. CoRR abs/1508.01420 (2015) - [i12]Adams Wei Yu, Wanli Ma, Yaoliang Yu, Jaime G. Carbonell, Suvrit Sra:
Efficient Structured Matrix Rank Minimization. CoRR abs/1509.02447 (2015) - 2014
- [c192]Chung-Chi Huang, Maxine Eskénazi, Jaime G. Carbonell, Lun-Wei Ku, Ping-Che Yang:
Cross-Lingual Information to the Rescue in Keyword Extraction. ACL (System Demonstrations) 2014: 1-6 - [c191]Jeffrey Flanigan, Sam Thomson, Jaime G. Carbonell, Chris Dyer, Noah A. Smith:
A Discriminative Graph-Based Parser for the Abstract Meaning Representation. ACL (1) 2014: 1426-1436 - [c190]Seungwhan Moon, Jaime G. Carbonell:
Proactive learning with multiple class-sensitive labelers. DSAA 2014: 32-38 - [c189]Ashiqur R. KhudaBukhsh, Jaime G. Carbonell, Peter J. Jansen:
Detecting Non-Adversarial Collusion in Crowdsourcing. HCOMP 2014: 104-111 - [c188]Adams Wei Yu, Fatma Kilinç-Karzan, Jaime G. Carbonell:
Saddle Points and Accelerated Perceptron Algorithms. ICML 2014: 1827-1835 - [c187]Luís Marujo, João Paulo Carvalho, Anatole Gershman, Jaime G. Carbonell, João Paulo Neto, David Martins de Matos:
Textual Event Detection Using Fuzzy Fingerprints. IEEE Conf. on Intelligent Systems (1) 2014: 825-836 - [c186]Lori S. Levin, Teruko Mitamura, Brian MacWhinney, Davida Fromm, Jaime G. Carbonell, Weston Feely, Robert E. Frederking, Anatole Gershman, Carlos Ramírez:
Resources for the Detection of Conventionalized Metaphors in Four Languages. LREC 2014: 498-501 - [c185]Adams Wei Yu, Wanli Ma, Yaoliang Yu, Jaime G. Carbonell, Suvrit Sra:
Efficient Structured Matrix Rank Minimization. NIPS 2014: 1350-1358 - [c184]Luís Marujo, José Portelo, David Martins de Matos, João Paulo Neto, Anatole Gershman, Jaime G. Carbonell, Isabel Trancoso, Bhiksha Raj:
Privacy-Preserving Important Passage Retrieval. PIR@SIGIR 2014: 7-12 - [i11]Luís Marujo, Anatole Gershman, Jaime G. Carbonell, João Paulo Neto, David Martins de Matos:
Ensemble Detection of Single & Multiple Events at Sentence-Level. CoRR abs/1403.6023 (2014) - [i10]Luís Marujo, José Portelo, David Martins de Matos, João Paulo Neto, Anatole Gershman, Jaime G. Carbonell, Isabel Trancoso, Bhiksha Raj:
Privacy-Preserving Important Passage Retrieval. CoRR abs/1407.5416 (2014) - 2013
- [j45]Meghana Kshirsagar, Jaime G. Carbonell, Judith Klein-Seetharaman:
Multitask learning for host-pathogen protein interactions. Bioinform. 29(13): 217-226 (2013) - [j44]Liu Yang, Steve Hanneke, Jaime G. Carbonell:
A theory of transfer learning with applications to active learning. Mach. Learn. 90(2): 161-189 (2013) - [c183]Jesse Dunietz, Lori S. Levin, Jaime G. Carbonell:
The Effects of Lexical Resource Quality on Preference Violation Detection. ACL (2) 2013: 765-770 - [c182]Liu Yang, Avrim Blum, Jaime G. Carbonell:
Learnability of DNF with representation-specific queries. ITCS 2013: 37-46 - [c181]Jeffrey Flanigan, Chris Dyer, Jaime G. Carbonell:
Large-Scale Discriminative Training for Statistical Machine Translation Using Held-Out Line Search. HLT-NAACL 2013: 248-258 - [c180]Liu Yang, Jaime G. Carbonell:
Buy-in-Bulk Active Learning. NIPS 2013: 2229-2237 - [c179]Ricardo Ribeiro, Luís Marujo, David Martins de Matos, João Paulo Neto, Anatole Gershman, Jaime G. Carbonell:
Self reinforcement for important passage retrieval. SIGIR 2013: 845-848 - [i9]Luís Marujo, Miguel M. F. Bugalho, João Paulo da Silva Neto, Anatole Gershman, Jaime G. Carbonell:
Hourly Traffic Prediction of News Stories. CoRR abs/1306.4608 (2013) - [i8]Luís Marujo, Anatole Gershman, Jaime G. Carbonell, Robert E. Frederking, João Paulo Neto:
Supervised Topical Key Phrase Extraction of News Stories using Crowdsourcing, Light Filtering and Co-reference Normalization. CoRR abs/1306.4886 (2013) - [i7]Luís Marujo, Ricardo Ribeiro, David Martins de Matos, João Paulo Neto, Anatole Gershman, Jaime G. Carbonell:
Key Phrase Extraction of Lightly Filtered Broadcast News. CoRR abs/1306.4890 (2013) - [i6]Luís Marujo, Wang Ling, Anatole Gershman, Jaime G. Carbonell, João Paulo Neto, David Martins de Matos:
Recognition of Named-Event Passages in News Articles. CoRR abs/1306.4908 (2013) - [i5]Luís Marujo, Anatole Gershman, Jaime G. Carbonell, David Martins de Matos, João Paulo Neto:
Co-Multistage of Multiple Classifiers for Imbalanced Multiclass Learning. CoRR abs/1312.6597 (2013) - 2012
- [j43]Meghana Kshirsagar, Jaime G. Carbonell, Judith Klein-Seetharaman:
Techniques to cope with missing data in host-pathogen protein interaction prediction. Bioinform. 28(18): 466-472 (2012) - [j42]Jingrui He, Hanghang Tong, Jaime G. Carbonell:
An effective framework for characterizing rare categories. Frontiers Comput. Sci. 6(2): 154-165 (2012) - [j41]Paulo Gaspar, Jaime G. Carbonell, José Luís Oliveira:
On the parameter optimization of Support Vector Machines for binary classification. J. Integr. Bioinform. 9(3) (2012) - [c178]Bin Fu, Eugene Fink, Garth A. Gibson, Jaime G. Carbonell:
Fast Approximate Matching of Astronomical Objects. CLUSTER Workshops 2012: 1-6 - [c177]Luís Marujo, Wang Ling, Anatole Gershman, Jaime G. Carbonell, João Paulo Neto, David Martins de Matos:
Recognition of Named-Event Passages in News Articles. COLING (Demos) 2012: 329-336 - [c176]Vamshi Ambati, Stephan Vogel, Jaime G. Carbonell:
Collaborative workflow for crowdsourcing translation. CSCW 2012: 1191-1194 - [c175]Selen Uguroglu, Mark Doyle, Robert Biederman, Jaime G. Carbonell:
Cost-Sensitive Risk Stratification in the Diagnosis of Heart Disease. IAAI 2012: 2335-2340 - [c174]Luís Marujo, Anatole Gershman, Jaime G. Carbonell, Robert E. Frederking, João Paulo Neto:
Supervised Topical Key Phrase Extraction of News Stories using Crowdsourcing, Light Filtering and Co-reference Normalization. LREC 2012: 399-403 - [c173]Paulo Gaspar, Jaime G. Carbonell, José Luís Oliveira:
Parameter Influence in Genetic Algorithm Optimization of Support Vector Machines. PACBB 2012: 43-51 - [c172]Xi Chen, Jingrui He, Rick Lawrence, Jaime G. Carbonell:
Adaptive Multi-task Sparse Learning with an Application to fMRI Study. SDM 2012: 212-223 - [c171]Luís Marujo, Ricardo Ribeiro, David Martins de Matos, João Paulo Neto, Anatole Gershman, Jaime G. Carbonell:
Key Phrase Extraction of Lightly Filtered Broadcast News. TSD 2012: 290-297 - [c170]Xi Chen, Han Liu, Jaime G. Carbonell:
Structured Sparse Canonical Correlation Analysis. AISTATS 2012: 199-207 - [i4]Xi Chen, Qihang Lin, Seyoung Kim, Jaime G. Carbonell, Eric P. Xing:
Smoothing Proximal Gradient Method for General Structured Sparse Learning. CoRR abs/1202.3708 (2012) - 2011
- [j40]Zhongming Zhao, Junfeng Xia, Öznur Tastan, Irtisha Singh, Meghana Kshirsagar, Jaime G. Carbonell, Judith Klein-Seetharaman:
Virus interactions with human signal transduction pathways. Int. J. Comput. Biol. Drug Des. 4(1): 83-105 (2011) - [c169]Vamshi Ambati, Stephan Vogel, Jaime G. Carbonell:
Towards Task Recommendation in Micro-Task Markets. Human Computation 2011 - [c168]Vamshi Ambati, Sanjika Hewavitharana, Stephan Vogel, Jaime G. Carbonell:
Active Learning with Multiple Annotations for Comparable Data Classification Task. BUCC@ACL 2011: 69-77 - [c167]Rashmi Gangadharaiah, Ralf D. Brown, Jaime G. Carbonell:
Phrasal Equivalence Classes for Generalized Corpus-Based Machine Translation. CICLing (2) 2011: 13-28 - [c166]Shinjae Yoo, Yiming Yang, Jaime G. Carbonell:
Modeling personalized email prioritization: classification-based and regression-based approaches. CIKM 2011: 729-738 - [c165]Siddharth Gopal, Yiming Yang, Konstantin Salomatin, Jaime G. Carbonell:
Statistical Learning for File-Type Identification. ICMLA (1) 2011: 68-73 - [c164]Vamshi Ambati, Stephan Vogel, Jaime G. Carbonell:
Multi-Strategy Approaches to Active Learning for Statistical Machine Translation. MTSummit 2011 - [c163]Selen Uguroglu, Jaime G. Carbonell:
Feature Selection for Transfer Learning. ECML/PKDD (3) 2011: 430-442 - [c162]Xi Chen, Yanjun Qi, Bing Bai, Qihang Lin, Jaime G. Carbonell:
Sparse Latent Semantic Analysis. SDM 2011: 474-485 - [c161]Mehrbod Sharifi, Eugene Fink, Jaime G. Carbonell:
SmartNotes: Application of crowdsourcing to the detection of web threats. SMC 2011: 1346-1350 - [c160]Mehrbod Sharifi, Eugene Fink, Jaime G. Carbonell:
Detection of Internet scam using logistic regression. SMC 2011: 2168-2172 - [c159]Xi Chen, Qihang Lin, Seyoung Kim, Jaime G. Carbonell, Eric P. Xing:
Smoothing Proximal Gradient Method for General Structured Sparse Learning. UAI 2011: 105-114 - [c158]Liu Yang, Steve Hanneke, Jaime G. Carbonell:
Identifiability of Priors from Bounded Sample Sizes with Applications to Transfer Learning. COLT 2011: 789-806 - [c157]Liu Yang, Steve Hanneke, Jaime G. Carbonell:
The Sample Complexity of Self-Verifying Bayesian Active Learning. AISTATS 2011: 816-822 - 2010
- [j39]Yanjun Qi, Öznur Tastan, Jaime G. Carbonell, Judith Klein-Seetharaman, Jason Weston:
Semi-supervised multi-task learning for predicting interactions between HIV-1 and human proteins. Bioinform. 26(18) (2010) - [j38]Thahir P. Mohamed, Jaime G. Carbonell, Madhavi Ganapathiraju:
Active learning for human protein-protein interaction prediction. BMC Bioinform. 11(S-1): 57 (2010) - [j37]Hatice U. Osmanbeyoglu, Jessica A. Wehner, Jaime G. Carbonell, Madhavi Ganapathiraju:
Active machine learning for transmembrane helix prediction. BMC Bioinform. 11(S-1): 58 (2010) - [j36]Jingrui He, Jaime G. Carbonell:
Coselection of features and instances for unsupervised rare category analysis. Stat. Anal. Data Min. 3(6): 417-430 (2010) - [c156]Xi Chen, Yan Liu, Han Liu, Jaime G. Carbonell:
Learning Spatial-Temporal Varying Graphs with Applications to Climate Data Analysis. AAAI 2010: 425-430 - [c155]Vamshi Ambati, Stephan Vogel, Jaime G. Carbonell:
Active Learning-Based Elicitation for Semi-Supervised Word Alignment. ACL (2) 2010: 365-370 - [c154]Liu Yang, Steve Hanneke, Jaime G. Carbonell:
Bayesian Active Learning Using Arbitrary Binary Valued Queries. ALT 2010: 50-58 - [c153]Matthew W. Bilotti, Jonathan L. Elsas, Jaime G. Carbonell, Eric Nyberg:
Rank learning for factoid question answering with linguistic and semantic constraints. CIKM 2010: 459-468 - [c152]Rashmi Gangadharaiah, Ralf D. Brown, Jaime G. Carbonell:
Monolingual Distributional Profiles for Word Substitution in Machine Translation. COLING (Posters) 2010: 320-328 - [c151]Rashmi Gangadharaiah, Ralf D. Brown, Jaime G. Carbonell:
Automatic Determination of Number of clusters for creating Templates in Example-Based Machine Translation. EAMT 2010 - [c150]Jae Dong Kim, Ralf D. Brown, Jaime G. Carbonell:
Chunk-Based EBMT. EAMT 2010 - [c149]Jingrui He, Hanghang Tong, Jaime G. Carbonell:
Rare Category Characterization. ICDM 2010: 226-235 - [c148]Xi Chen, Bing Bai, Yanjun Qi, Qihang Lin, Jaime G. Carbonell:
Learning Preferences with Millions of Parameters by Enforcing Sparsity. ICDM 2010: 779-784 - [c147]Betty Yee Man Cheng, Jaime G. Carbonell:
Automatic Detection of HIV Drug Resistance-Associated Mutations. ICMLA 2010: 528-533 - [c146]Vamshi Ambati, Stephan Vogel, Jaime G. Carbonell:
Active Learning and Crowd-Sourcing for Machine Translation. LREC 2010 - [c145]Liang Xiong, Xi Chen, Tzu-Kuo Huang, Jeff G. Schneider, Jaime G. Carbonell:
Temporal Collaborative Filtering with Bayesian Probabilistic Tensor Factorization. SDM 2010: 211-222 - [c144]Jingrui He, Jaime G. Carbonell:
Co-selection of Features and Instances for Unsupervised Rare Category Analysis. SDM 2010: 525-536 - [c143]Pinar Donmez, Jaime G. Carbonell, Jeff G. Schneider:
A Probabilistic Framework to Learn from Multiple Annotators with Time-Varying Accuracy. SDM 2010: 826-837 - [c142]Mehrbod Sharifi, Eugene Fink, Jaime G. Carbonell:
Learning of personalized security settings. SMC 2010: 3428-3432 - [p1]Pinar Donmez, Jaime G. Carbonell:
From Active to Proactive Learning Methods. Advances in Machine Learning I 2010: 97-120 - [i3]Xi Chen, Seyoung Kim, Qihang Lin, Jaime G. Carbonell, Eric P. Xing:
Graph-Structured Multi-task Regression and an Efficient Optimization Method for General Fused Lasso. CoRR abs/1005.3579 (2010) - [i2]Xi Chen, Qihang Lin, Seyoung Kim, Javier Peña, Jaime G. Carbonell, Eric P. Xing:
An Efficient Proximal-Gradient Method for Single and Multi-task Regression with Structured Sparsity. CoRR abs/1005.4717 (2010) - [i1]Judith Gelernter, Dong Cao, Jaime G. Carbonell:
Studies on Relevance, Ranking and Results Display. CoRR abs/1006.4535 (2010)
2000 – 2009
- 2009
- [j35]Yan Liu, Jaime G. Carbonell, Vanathi Gopalakrishnan, Peter Weigele:
Conditional Graphical Models for Protein Structural Motif Recognition. J. Comput. Biol. 16(5): 639-657 (2009) - [c141]Pinar Donmez, Jaime G. Carbonell:
Active Sampling for Rank Learning via Optimizing the Area under the ROC Curve. ECIR 2009: 78-89 - [c140]Sivaraman Balakrishnan, Öznur Tastan, Jaime G. Carbonell, Judith Klein-Seetharaman:
Communication interception of human signal transduction pathways by Human Immunodeficiency Virus-1. GENSiPS 2009: 1-4 - [c139]Xi Chen, Weike Pan, James T. Kwok, Jaime G. Carbonell:
Accelerated Gradient Method for Multi-task Sparse Learning Problem. ICDM 2009: 746-751 - [c138]Pinar Donmez, Jaime G. Carbonell, Jeff G. Schneider:
Efficiently learning the accuracy of labeling sources for selective sampling. KDD 2009: 259-268 - [c137]Vamshi Ambati, Alon Lavie, Jaime G. Carbonell:
Extraction of Syntactic Translation Models from Parallel Data using Syntax from Source and Target Languages. MTSummit 2009 - [c136]Rashmi Gangadharaiah, Ralf D. Brown, Jaime G. Carbonell:
Active Learning in Example-Based Machine Translation. NODALIDA 2009: 227-230 - [c135]Öznur Tastan, Yanjun Qi, Jaime G. Carbonell, Judith Klein-Seetharaman:
Prediction of Interactions Between HIV-1 and Human Proteins by Information Integration. Pacific Symposium on Biocomputing 2009: 516-527 - [c134]Jingrui He, Jaime G. Carbonell:
Prior-Free Rare Category Detection. SDM 2009: 155-163 - [c133]Jonathan L. Elsas, Jaime G. Carbonell:
It pays to be picky: an evaluation of thread retrieval in online forums. SIGIR 2009: 714-715 - [c132]Judith Gelernter, Dong Cao, Raymond Lu, Eugene Fink, Jaime G. Carbonell:
Creating and visualizing fuzzy document classification. SMC 2009: 672-679 - [c131]Anatole Gershman, Eugene Fink, Bin Fu, Jaime G. Carbonell:
Analysis of uncertain data: Selection of probes for information gathering. SMC 2009: 2227-2232 - [c130]Eugene Fink, Ankur Sarin, Jaime G. Carbonell:
Analysis of uncertain data: Smoothing of histograms. SMC 2009: 2549-2555 - [c129]Anatole Gershman, Eugene Fink, Bin Fu, Jaime G. Carbonell:
Analysis of uncertain data: Evaluation of given hypotheses. SMC 2009: 2556-2561 - [c128]Eugene Fink, Matt Jennings, Konstantin Salomatin, Jaime G. Carbonell:
Scheduling with uncertain resources: Representation of common knowledge. SMC 2009: 2642-2646 - [c127]Jonathan L. Elsas, Pinar Donmez, Jamie Callan, Jaime G. Carbonell:
Pairwise Document Classification for Relevance Feedback. TREC 2009 - 2008
- [c126]Michael Freed, Jaime G. Carbonell, Geoffrey J. Gordon, Jordan Hayes, Brad A. Myers, Daniel P. Siewiorek, Stephen F. Smith, Aaron Steinfeld, Anthony Tomasic:
RADAR: A Personal Assistant that Learns to Reduce Email Overload. AAAI 2008: 1287-1293 - [c125]Pinar Donmez, Jaime G. Carbonell:
Proactive learning: cost-sensitive active learning with multiple imperfect oracles. CIKM 2008: 619-628 - [c124]Monica Rogati, Yiming Yang, Jaime G. Carbonell:
Corpus microsurgery: criteria optimization for medical cross-language ir. CIKM 2008: 1365-1366 - [c123]Vitor R. Carvalho, Jonathan L. Elsas, William W. Cohen, Jaime G. Carbonell:
Suppressing outliers in pairwise preference ranking. CIKM 2008: 1487-1488 - [c122]Christian Monson, Jaime G. Carbonell, Alon Lavie, Lori S. Levin:
ParaMor and Morpho Challenge 2008. CLEF 2008: 967-974 - [c121]Christian Monson, Jaime G. Carbonell, Alon Lavie, Lori S. Levin:
ParaMor and Morpho Challenge 2008. CLEF (Working Notes) 2008 - [c120]Pinar Donmez, Jaime G. Carbonell:
Optimizing estimated loss reduction for active sampling in rank learning. ICML 2008: 248-255 - [c119]Jaime Arguello, Jonathan L. Elsas, Jamie Callan, Jaime G. Carbonell:
Document Representation and Query Expansion Models for Blog Recommendation. ICWSM 2008 - [c118]Lucian Vlad Lita, Jaime G. Carbonell:
Cluster-Based Query Expansion for Statistical Question Answering. IJCNLP 2008: 426-433 - [c117]Pinar Donmez, Jaime G. Carbonell:
Paired Sampling in Density-Sensitive Active Learning. ISAIM 2008 - [c116]Jingrui He, Jaime G. Carbonell:
Rare Class Discovery Based on Active Learning. ISAIM 2008 - [c115]Chun Jin, Jaime G. Carbonell:
Predicate Indexing for Incremental Multi-Query Optimization. ISMIS 2008: 339-350 - [c114]Christian Monson, Ariadna Font Llitjós, Vamshi Ambati, Lori S. Levin, Alon Lavie, Alison Alvarez, Roberto Aranovich, Jaime G. Carbonell, Robert E. Frederking, Erik Peterson, Katharina Probst:
Linguistic Structure and Bilingual Informants Help Induce Machine Translation of Lesser-Resourced Languages. LREC 2008 - [c113]Jonathan L. Elsas, Jaime Arguello, Jamie Callan, Jaime G. Carbonell:
Retrieval and feedback models for blog feed search. SIGIR 2008: 347-354 - [c112]Yangbo Zhu, Jamie Callan, Jaime G. Carbonell:
The impact of history length on personalized search. SIGIR 2008: 715-716 - [c111]Christian Monson, Alon Lavie, Jaime G. Carbonell, Lori S. Levin:
Evaluating an Agglutinative Segmentation Model for ParaMor. SIGMORPHON 2008: 49-58 - [c110]Alexander Carpentier, Mehrbod Sharifi, Eugene Fink, Jaime G. Carbonell:
Scheduling with uncertain resources: Learning to ask the right questions. SMC 2008: 2543-2547 - [c109]Steven Gardiner, Eugene Fink, Jaime G. Carbonell:
Scheduling with uncertain resources: Learning to make reasonable assumptions. SMC 2008: 2554-2559 - [c108]Bin Fu, Eugene Fink, Jaime G. Carbonell:
Analysis of uncertain data: Tools for representation and processing. SMC 2008: 3256-3260 - [c107]Jaime Arguello, Jonathan L. Elsas, Changkuk Yoo, Jamie Callan, Jaime G. Carbonell:
Document and Query Expansion Models for Blog Distillation. TREC 2008 - [c106]Jonathan L. Elsas, Vitor R. Carvalho, Jaime G. Carbonell:
Fast learning of document ranking functions with the committee perceptron. WSDM 2008: 55-64 - 2007
- [c105]Betty Yee Man Cheng, Jaime G. Carbonell:
Combining N-grams and Alignment in G-protein Coupling Specificity Prediction. APBC 2007: 363-372 - [c104]Jade Goldstein, Gary M. Ciany, Jaime G. Carbonell:
Genre identification and goal-focused summarization. CIKM 2007: 889-892 - [c103]Christian Monson, Jaime G. Carbonell, Alon Lavie, Lori S. Levin:
ParaMor: Finding Paradigms across Morphology. CLEF 2007: 900-907 - [c102]Christian Monson, Jaime G. Carbonell, Alon Lavie, Lori S. Levin:
ParaMor: Finding Paradigms across Morphology. CLEF (Working Notes) 2007 - [c101]Pinar Donmez, Jaime G. Carbonell, Paul N. Bennett:
Dual Strategy Active Learning. ECML 2007: 116-127 - [c100]Yan Liu, Jaime G. Carbonell, Vanathi Gopalakrishnan, Peter Weigele:
Protein Quaternary Fold Recognition Using Conditional Graphical Models. IJCAI 2007: 937-945 - [c99]Lucian Vlad Lita, Jaime G. Carbonell:
Cluster-Based Selection of Statistical Answering Strategies. IJCAI 2007: 1653-1658 - [c98]Jingrui He, Jaime G. Carbonell, Yan Liu:
Graph-Based Semi-Supervised Learning as a Generative Model. IJCAI 2007: 2492-2497 - [c97]Ariadna Font Llitjós, Jaime G. Carbonell, Alon Lavie:
Improving transfer-based MT systems with automatic refinements. MTSummit 2007 - [c96]Paul N. Bennett, Jaime G. Carbonell:
Combining Probability-Based Rankers for Action-Item Detection. HLT-NAACL 2007: 324-331 - [c95]Jingrui He, Jaime G. Carbonell:
Nearest-Neighbor-Based Active Learning for Rare Category Detection. NIPS 2007: 633-640 - [c94]Vasco Pedro, Lucian Vlad Lita, Radu Stefan Niculescu, Bharat Rao, Jaime G. Carbonell:
Federated Ontology Search for the Medical Domain. OTM Workshops (1) 2007: 554-565 - [c93]Christian Monson, Jaime G. Carbonell, Alon Lavie, Lori S. Levin:
ParaMor: Minimally Supervised Induction of Paradigm Structure and Morphological Analysis. SIGMORPHON 2007: 117-125 - [c92]Jonathan L. Elsas, Jaime Arguello, Jamie Callan, Jaime G. Carbonell:
Retrieval and Feedback Models for Blog Distillation. TREC 2007 - [c91]Yangbo Zhu, Le Zhao, Jamie Callan, Jaime G. Carbonell:
Stuctured Queries for Legal Search. TREC 2007 - 2006
- [j34]Yan Liu, Jaime G. Carbonell, Peter Weigele, Vanathi Gopalakrishnan:
Protein Fold Recognition Using Segmentation Conditional Random Fields (SCRFs). J. Comput. Biol. 13(2): 394-406 (2006) - [c90]Jaime G. Carbonell, Steve Klein, David Miller, Mike Steinbaum, Tomer Grassiany, Jochen Frei:
Context-Based Machine Translation. AMTA 2006: 19-28 - [c89]Chun Jin, Jaime G. Carbonell:
ARGUS: Efficient Scalable Continuous Query Optimization for Large-Volume Data Streams. IDEAS 2006: 256-262 - [c88]Chun Jin, Jaime G. Carbonell:
Incremental Aggregation on Multiple Continuous Queries. ISMIS 2006: 167-177 - [c87]Rashmi Gangadharaiah, Ralf D. Brown, Jaime G. Carbonell:
Spectral Clustering for Example Based Machine Translation. HLT-NAACL 2006 - [c86]Eugene Fink, Ulas Bardak, Brandon Rothrock, Jaime G. Carbonell:
Scheduling with Uncertain Resources: Collaboration with the User. SMC 2006: 11-17 - [c85]Eugene Fink, P. Matthew Jennings, Ulas Bardak, Jean Oh, Stephen F. Smith, Jaime G. Carbonell:
Scheduling with Uncertain Resources: Search for a Near-Optimal Solution. SMC 2006: 137-144 - [c84]Ulas Bardak, Eugene Fink, Jaime G. Carbonell:
Scheduling with Uncertain Resources: Representation and Utility Function. SMC 2006: 1486-1492 - [c83]Ulas Bardak, Eugene Fink, Chris R. Martens, Jaime G. Carbonell:
Scheduling with Uncertain Resources: Elicitation of Additional Data. SMC 2006: 1493-1498 - 2005
- [j33]Stanley Y. W. Su, José A. B. Fortes, Thrity R. Kasad, Manjiri Patil, Andréa M. Matsunaga, Maurício O. Tsugawa, Violetta Cavalli-Sforza, Jaime G. Carbonell, Peter J. Jansen, Wayne H. Ward, Ronald A. Cole, Donald F. Towsley, Weifeng Chen, Annie I. Antón, Qingfeng He, Charles McSweeney, Lilliam G. de Brens, José Luis Ventura, Pedro Taveras, Ruth M. Connolly, Carmen Ortega, Beatriz Piñeres, Ornel Brooks, Gareth A. Murillo, Manuel Herrera:
Transnational Information Sharing, Event Notification, Rule Enforcement and Process Coordination. Int. J. Electron. Gov. Res. 1(2): 1-26 (2005) - [c82]Ralf D. Brown, Jae Dong Kim, Peter J. Jansen, Jaime G. Carbonell:
Symmetric Probabilistic Alignment. ParallelText@ACL 2005: 87-90 - [c81]Jae Dong Kim, Ralf D. Brown, Peter J. Jansen, Jaime G. Carbonell:
Symmetric probabilistic alignment for example-based translation. EAMT 2005 - [c80]Ariadna Font Llitjós, Jaime G. Carbonell, Alon Lavie:
A framework for interactive and automatic refinement of transfer-based machine translation. EAMT 2005 - [c79]Yan Liu, Eric P. Xing, Jaime G. Carbonell:
Predicting protein folds with structural repeats using a chain graph model. ICML 2005: 513-520 - [c78]Betty Yee Man Cheng, Jaime G. Carbonell, Judith Klein-Seetharaman:
A Machine Text-Inspired Machine Learning Approach for Identification of Transmembrane Helix Boundaries. ISMIS 2005: 29-37 - [c77]Chun Jin, Jaime G. Carbonell, Philip J. Hayes:
ARGUS: Rete + DBMS = Efficient Persistent Profile Matching on Large-Volume Data Streams. ISMIS 2005: 142-151 - [c76]Yan Liu, Jaime G. Carbonell, Peter Weigele, Vanathi Gopalakrishnan:
Segmentation Conditional Random Fields (SCRFs): A New Approach for Protein Fold Recognition. RECOMB 2005: 408-422 - [c75]Paul N. Bennett, Jaime G. Carbonell:
Detecting action-items in e-mail. SIGIR 2005: 585-586 - 2004
- [j32]Yan Liu, Jaime G. Carbonell, Judith Klein-Seetharaman, Vanathi Gopalakrishnan:
Comparison of probabilistic combination methods for protein secondary structure prediction. Bioinform. 20(17): 3099-3107 (2004) - [c74]Ariadna Font Llitjós, Katharina Probst, Jaime G. Carbonell:
Error Analysis of Two Types of Grammar for the Purpose of Automatic Rule Refinement. AMTA 2004: 187-196 - [c73]Lucian Vlad Lita, Jaime G. Carbonell:
Unsupervised question answering data acquisition from local corpora. CIKM 2004: 607-614 - [c72]Stanley Y. W. Su, José A. B. Fortes, Thrity R. Kasad, Manjiri Patil, Andréa M. Matsunaga, Maurício O. Tsugawa, Violetta Cavalli-Sforza, Jaime G. Carbonell, Peter J. Jansen, Wayne H. Ward, Ronald A. Cole, Donald F. Towsley, Weifeng Chen, Annie I. Antón, Qingfeng He, Charles McSweeney, Lilliam G. de Brens, José Luis Ventura, Pedro Taveras, Ruth M. Connolly, Carmen Ortega, Beatriz Piñeres, Ornel Brooks, Manuel Herrera:
A Prototype System for Transnational Information Sharing and Process Coordination. DG.O 2004 - [c71]Stanley Y. W. Su, José A. B. Fortes, Thrity R. Kasad, Manjiri Patil, Andréa M. Matsunaga, Maurício O. Tsugawa, Violetta Cavalli-Sforza, Jaime G. Carbonell, Peter J. Jansen, Wayne H. Ward, Ronald A. Cole, Donald F. Towsley, Weifeng Chen, Annie I. Antón, Qingfeng He, Charles McSweeney, Lilliam G. de Brens, José Luis Ventura, Pedro Taveras, Ruth M. Connolly, Carmen Ortega, Beatriz Piñeres, Ornel Brooks, Manuel Herrera:
A Prototype System for Transnational Information Sharing and Process Coordination: System Demo. DG.O 2004 - [c70]Violetta Cavalli-Sforza, Ralf D. Brown, Jaime G. Carbonell, Peter G. Jansen, Jae Dong Kim:
Challenges in using an example-based MT system for a transnational digital government project. EAMT 2004 - [c69]Alon Lavie, Katharina Probst, Erik Peterson, Stephan Vogel, Lori S. Levin, Ariadna Font Llitjós, Jaime G. Carbonell:
A trainable transfer-based MT approach for languages with limited resources. EAMT 2004 - [c68]Lucian Vlad Lita, Jaime G. Carbonell:
Instance-Based Question Answering: A Data-Driven Approach. EMNLP 2004: 396-403 - [c67]Violetta Cavalli-Sforza, Jaime G. Carbonell, Peter J. Jansen:
Developing Language Resources for a Transnational Digital Government System. LREC 2004 - [c66]Ariadna Font Llitjós, Jaime G. Carbonell:
The Translation Correction Tool: English-Spanish User Studies. LREC 2004 - [c65]Christian Monson, Lori S. Levin, Rodolfo Vega, Ralf D. Brown, Ariadna Font Llitjós, Alon Lavie, Jaime G. Carbonell, Eliseo Cañulef, Rosendo Huisca:
Data Collection and Analysis of Mapudungun Morphology for Spelling Correction. LREC 2004 - [c64]Yan Liu, Jaime G. Carbonell, Judith Klein-Seetharaman, Vanathi Gopalakrishnan:
Context sensitive vocabulary and its application in protein secondary structure prediction. SIGIR 2004: 538-539 - [c63]Christian Monson, Alon Lavie, Jaime G. Carbonell, Lori S. Levin:
Unsupervised Induction of Natural Language Morphology Inflection Classes. SIGMORPHON@ACL 2004 - [c62]Eugene Fink, Aaron Goldstein, Philip J. Hayes, Jaime G. Carbonell:
Search for approximate matches in large databases. SMC (2) 2004: 1431-1435 - 2003
- [j31]Alon Lavie, Stephan Vogel, Lori S. Levin, Erik Peterson, Katharina Probst, Ariadna Font Llitjós, Rachel Reynolds, Jaime G. Carbonell, Richard Cohen:
Experiments with a Hindi-to-English transfer-based MT system under a miserly data scenario. ACM Trans. Asian Lang. Inf. Process. 2(2): 143-163 (2003) - [c61]Jaime G. Carbonell:
Grand challenges for information management. CIKM 2003: 1 - [c60]Lucian Vlad Lita, Monica Rogati, Jaime G. Carbonell:
Cross Lingual QA: A Modular Baseline in CLEF 2003. CLEF 2003: 535-540 - [c59]Lucian Vlad Lita, Monica Rogati, Jaime G. Carbonell:
Cross Lingual QA: A Modular Baseline. CLEF (Working Notes) 2003 - [c58]Yan Liu, Jaime G. Carbonell, Rong Jin:
A New Pairwise Ensemble Approach for Text Classification. ECML 2003: 277-288 - [c57]Ralf D. Brown, Rebecca Hutchinson, Paul N. Bennett, Jaime G. Carbonell, Peter J. Jansen:
Reducing boundary friction using translation-fragment overlap. MTSummit 2003 - [c56]Eric Nyberg, Teruko Mitamura, James P. Callan, Jaime G. Carbonell, Robert E. Frederking, Kevyn Collins-Thompson, Laurie Hiyakumoto, Yifen Huang, Curtis Huttenhower, Scott Judy, Jeongwoo Ko, Anna Kupsc, Lucian Vlad Lita, Vasco Pedro, David Svoboda, Benjamin Van Durme:
The JAVELIN Question-Answering System at TREC 2003: A Multi-Strategh Approach with Dynamic Planning. TREC 2003 - 2002
- [j30]Katharina Probst, Lori S. Levin, Erik Peterson, Alon Lavie, Jaime G. Carbonell:
MT for Minority Languages Using Elicitation-Based Learning of Syntactic Transfer Rules. Mach. Transl. 17(4): 245-270 (2002) - [c55]Jaime G. Carbonell, Katharina Probst, Erik Peterson, Christian Monson, Alon Lavie, Ralf D. Brown, Lori S. Levin:
Automatic Rule Learning for Resource-Limited MT. AMTA 2002: 1-10 - [c54]Yan Liu, Yiming Yang, Jaime G. Carbonell:
Boosting to correct inductive bias in text classification. CIKM 2002: 348-355 - [c53]Yiming Yang, Jian Zhang, Jaime G. Carbonell, Chun Jin:
Topic-conditioned novelty detection. KDD 2002: 688-693 - [c52]Eric Nyberg, Teruko Mitamura, Jaime G. Carbonell, James P. Callan, Kevyn Collins-Thompson, Krzysztof Czuba, Michael Duggan, Laurie Hiyakumoto, N. Hu, Yifen Huang, Jeongwoo Ko, Lucian Vlad Lita, S. Murtagh, Vasco Pedro, David Svoboda:
The JAVELIN Question-Answering System at TREC 2002. TREC 2002 - 2000
- [j29]Jaime G. Carbonell, Yiming Yang, William W. Cohen:
Special Issue of Machine Learning on Information Retrieval - Introduction. Mach. Learn. 39(2/3): 99-101 (2000) - [c51]Jade Goldstein, Vibhu O. Mittal, Jaime G. Carbonell, James P. Callan:
Creating and Evaluating Multi-Document Sentence Extract Summaries. CIKM 2000: 165-172
1990 – 1999
- 1999
- [j28]Yiming Yang, Jaime G. Carbonell, Ralf D. Brown, Thomas Pierce, Blair Archibald, Xin Liu:
Learning approaches for detecting and tracking news events. IEEE Intell. Syst. 14(4): 32-43 (1999) - [c50]Vibhu O. Mittal, Mark Kantrowitz, Jade Goldstein, Jaime G. Carbonell:
Selecting Text Spans for Document Summaries: Heuristics and Metrics. AAAI/IAAI 1999: 467-473 - [c49]Jade Goldstein, Mark Kantrowitz, Vibhu O. Mittal, Jaime G. Carbonell:
Summarizing Text Documents: Sentence Selection and Evaluation Metrics. SIGIR 1999: 121-128 - 1998
- [j27]Yiming Yang, Jaime G. Carbonell, Ralf D. Brown, Robert E. Frederking:
Translingual Information Retrieval: Learning from Bilingual Corpora. Artif. Intell. 103(1-2): 323-345 (1998) - [c48]Yiming Yang, Thomas Pierce, Jaime G. Carbonell:
A Study of Retrospective and On-Line Event Detection. SIGIR 1998: 28-36 - [c47]Jaime G. Carbonell, Jade Goldstein:
The Use of MMR, Diversity-Based Reranking for Reordering Documents and Producing Summaries. SIGIR 1998: 335-336 - [c46]Jade Goldstein, Jaime G. Carbonell:
Summarization: (1) Using MMR for Diversity- Based Reranking and (2) Evaluating Summaries. TIPSTER 1998: 181-195 - 1997
- [c45]Jaime G. Carbonell, Yiming Yang, Robert E. Frederking, Ralf D. Brown, Yibing Geng, Danny Lee:
Translingual Information Retrieval: A Comparative Evaluation. IJCAI (1) 1997: 708-715 - 1996
- [c44]Lynn Carlson, Jaime G. Carbonell, David Farwell, Pierre Isabelle, Jackie Murgida, John O'Hara, Dekai Wu:
Panel: Next steps in MT research. AMTA 1996 - 1995
- [j26]Manuela M. Veloso, Jaime G. Carbonell, M. Alicia Pérez, Daniel Borrajo, Eugene Fink, Jim Blythe:
Integrating planning and learning: the PRODIGY architecture. J. Exp. Theor. Artif. Intell. 7(1): 81-120 (1995) - [c43]James A. Hendler, Jaime G. Carbonell, Douglas B. Lenat, Riichiro Mizoguchi, Paul S. Rosenbloom:
VERY Large Knowledge Bases - Architecture vs Engineering. IJCAI 1995: 2033-2036 - 1994
- [c42]M. Alicia Pérez, Jaime G. Carbonell:
Control Knowledge to Improve Plan Quality. AIPS 1994: 323-328 - [c41]Jaime G. Carbonell, David Farwell, Robert E. Frederking, Stephen Helmreich, Eduard H. Hovy, Kevin Knight, Lori S. Levin, Sergei Nirenburg:
PANGLOSS. AMTA 1994 - [c40]Teruko Mitamura, Eric Nyberg, Jaime G. Carbonell:
KANT: Knowledge-Based, Accurate Natural Language Translation. AMTA 1994 - [c39]Joseph Pentheroudakis, Jaime G. Carbonell, Lutz Graunitz, Pierre Isabelle, Chris Montgomery, Alex Waibel:
Future Directions. AMTA 1994 - [c38]Eric Nyberg, Teruko Mitamura, Jaime G. Carbonell:
Evaluation Metrics for Knowledge-Based Machine Translation. COLING 1994: 95-99 - [c37]Jaime G. Carbonell:
Knowledge Representation Issues in Integrated Planning and Learning Systems (Abstract). KR 1994: 633 - 1993
- [j25]Manuela M. Veloso, Jaime G. Carbonell:
Derivational Analogy in Prodigy: Automating Case Acquisition, Storage, and Utilization. Mach. Learn. 10: 249-278 (1993) - [c36]Jaime G. Carbonell:
Lessons from TIPSTER/SHOGUN/JANUS. SIGIR 1993: 225 - 1992
- [b1]Sergei Nirenburg, Jaime G. Carbonell, Masaru Tomita, Kenneth Goodman:
Machine translation - a knowledge-based approach. Morgan Kaufmann 1992, ISBN 978-1-55860-128-4, pp. I-XIV, 1-258 - [j24]Jaime G. Carbonell:
Machine Learning: A Maturing Field. Mach. Learn. 9: 5-7 (1992) - [c35]Mark Perlin, Jaime G. Carbonell, Daniel P. Miranker, Salvatore J. Stolfo, Milind Tambe:
Is Production System Match Interesting? ICTAI 1992: 2-3 - 1991
- [j23]Jaime G. Carbonell:
Editorial. Mach. Learn. 6: 5 (1991) - [j22]Jaime G. Carbonell:
Editorial. Mach. Learn. 7: 5 (1991) - [j21]Jaime G. Carbonell, Oren Etzioni, Yolanda Gil, Robert Joseph, Craig A. Knoblock, Steven Minton, Manuela M. Veloso:
PRODIGY: An Integrated Architecture for Planning and Learning. SIGART Bull. 2(4): 51-55 (1991) - [c34]Manuela M. Veloso, Jaime G. Carbonell:
Learning by Analogical Replay in PRODIGY: First Results. EWSL 1991: 375-390 - [c33]Jaime G. Carbonell:
Session 3: Machine Translation. HLT 1991 - 1990
- [c32]Yorick Wilks, Jaime G. Carbonell, David Farwell, Eduard H. Hovy, Sergei Nirenburg:
Machine Translation Again? HLT 1990
1980 – 1989
- 1989
- [j20]Jaime G. Carbonell:
Introduction: Paradigms for Machine Learning. Artif. Intell. 40(1-3): 1-9 (1989) - [j19]Steven Minton, Jaime G. Carbonell, Craig A. Knoblock, Daniel Kuokka, Oren Etzioni, Yolanda Gil:
Explanation-Based Learning: A Problem Solving Perspective. Artif. Intell. 40(1-3): 63-118 (1989) - [j18]Jaime G. Carbonell:
Editorial. Mach. Learn. 4: 5-6 (1989) - [j17]Jaime G. Carbonell:
Editorial. Mach. Learn. 4: 113-115 (1989) - [c31]Peter Shell, Jaime G. Carbonell:
Towards a General Framework for Composing Disjunctive and Iterative Macro-operators. IJCAI 1989: 596-602 - [c30]Ralph Weiscbedel, Jaime G. Carbonell, Barbara J. Grosz, Wendy Lehnert, Mitchell Marcus, Ray Perrault, Robert Wilensky:
White Paper on Natural Language Processing. HLT (2) 1989 - 1988
- [j16]Jill H. Larkin, Frederick Reif, Jaime G. Carbonell, Angela Gugliotta:
FERMI: A Flexible Expert Reasoner with Multi-Domain Inferencing. Cogn. Sci. 12(1): 101-138 (1988) - [c29]Jaime G. Carbonell, Ralf D. Brown:
Anaphora resolution: a multy-strategy approach. COLING 1988: 96-101 - 1987
- [j15]Ira Monarch, Jaime G. Carbonell:
CoalSORT: A Knowledge-Based Interface. IEEE Expert 2(1): 39-53 (1987) - [j14]Sergei Nirenburg, Jaime G. Carbonell:
Integrating discourse pragmatics and propositional knowledge for multilingual natural language processing. Mach. Transl. 2(2-3): 105-116 (1987) - [c28]Steven Minton, Jaime G. Carbonell:
Strategies for Learning Search Control Rules: An Explanation-based Approach. IJCAI 1987: 228-235 - [c27]Masaru Tomita, Jaime G. Carbonell:
The Universal Parser Architecture for Knowledge-based Machine Translation. IJCAI 1987: 718-721 - 1986
- [c26]Patricia Cheng, Jaime G. Carbonell:
The FERMI System: Inducing Iterative Macro-Operators from Experience. AAAI 1986: 490-495 - [c25]Wolfgang Wahlster, Jaime G. Carbonell, Gary G. Hendrix, Harry R. Tennant:
Natural Language Interfaces - Ready for Commercial Success? COLING 1986: 161-167 - [c24]Philip J. Hayes, Alexander G. Hauptmann, Jaime G. Carbonell, Masaru Tomita:
Parsing Spoken Language: A Semantic Caseframe Approach. COLING 1986: 587-592 - [c23]Masaru Tomita, Jaime G. Carbonell:
Another Stride Towards Knowledge-Based Machine Translation. COLING 1986: 633-638 - [c22]Jaime G. Carbonell:
Analogical reasoning in planning and decision making. ISMIS 1986: 288 - 1984
- [j13]Pat Langley, Jaime G. Carbonell:
Approaches to machine learning. J. Am. Soc. Inf. Sci. 35(5): 306-316 (1984) - [c21]Jaime G. Carbonell:
Is There Natural Language after Data Bases? COLING 1984: 186-187 - [c20]Jaime G. Carbonell, Philip J. Hayes:
Coping with Extragrammaticality. COLING 1984: 437-443 - 1983
- [j12]Jaime G. Carbonell, Ryszard S. Michalski, Tom M. Mitchell:
Machine Learning: A Historical and Methodological Analysis. AI Mag. 4(3): 69-79 (1983) - [j11]Jaime G. Carbonell, Philip J. Hayes:
Recovery Strategies for Parsing Extragrammatical Language. Am. J. Comput. Linguistics 9(3-4): 123-146 (1983) - [c19]Jaime G. Carbonell:
Derivational Analogy and Its Role in Problem Solving. AAAI 1983: 64-69 - [c18]Jaime G. Carbonell:
Discourse Pragmatics and Ellipsis Resolution in Task-Oriented Natural Language Interfaces. ACL 1983: 164-168 - [c17]Jaime G. Carbonell, W. Mark Boggs, Michael L. Mauldin, Peter G. Anick:
The XCALIBUR Project: A Natural Language Interface to Expert Systems. IJCAI 1983: 653-656 - [c16]Philip J. Hayes, Jaime G. Carbonell:
A Framework for Processing Corrections in Task-Oriented Dialogues. IJCAI 1983: 668-670 - [c15]Jaime G. Carbonell:
User Modelling and Natural Language Interface Design. Software-Ergonomie 1983: 21-29 - 1982
- [j10]Jaime G. Carbonell, Derek H. Sleeman:
Artificial Intelligence Techniques and Methodology. AI Mag. 3(2): 47 (1982) - [j9]W. Mark Boggs, Jaime G. Carbonell, Robert E. Frederking, Philip J. Hayes, George V. Mouradian, Donald W. Kosy, Michael L. Mauldin, Hiromichi Fujisawa:
Robust man-machine interfaces and dialog modelling: Carnegie-Mellon University. SIGART Newsl. 79: 39-42 (1982) - [j8]Jaime G. Carbonell:
A note on the AI tutorial at the ACM. SIGART Newsl. 81: 18 (1982) - [c14]Jaime G. Carbonell:
Experiential Learning in Analogical Problem Solving. AAAI 1982: 168-171 - 1981
- [j7]Jaime G. Carbonell:
Counterplanning: A Strategy-Based Model of Adversary Planning in Real-World Situations. Artif. Intell. 16(3): 295-329 (1981) - [j6]Jaime G. Carbonell, Richard E. Cullingford, Anatole Gershman:
Steps Toward Knowledge-Based Machine Translation. IEEE Trans. Pattern Anal. Mach. Intell. 3(4): 376-392 (1981) - [j5]Jaime G. Carbonell:
Machine learning research. SIGART Newsl. 77: 29 (1981) - [c13]Jaime G. Carbonell, Philip J. Hayes:
Dynamic Strategy Selection in Flexible Parsing. ACL 1981: 143-147 - [c12]Gary G. Hendrix, Jaime G. Carbonell:
A tutorial on natural-language processing. ACM Annual Conference 1981: 4-8 - [c11]Jaime G. Carbonell:
A Computational Model of Analogical Problem Solving. IJCAI 1981: 147-152 - [c10]Philip J. Hayes, Jaime G. Carbonell:
Multi-Strategy Construction-Specific Parsing for Flexible Data Base Query and Update. IJCAI 1981: 432-439 - 1980
- [j4]Jaime G. Carbonell:
Towards a Process Model of Human Personality Traits. Artif. Intell. 15(1-2): 49-74 (1980) - [j3]Jaime G. Carbonell:
Artificial Intelligence Research at Carnegie-Mellon University. AI Mag. 2(1): 29-34 (1980) - [c9]Jaime G. Carbonell:
DELTA-MIN: A Search-Control Method for Information-Gathering Problems. AAAI 1980: 124-127 - [c8]Jaime G. Carbonell:
Metapher - A Key to Extensible Semantic Analysis. ACL 1980 - [c7]L. Peter Deutsch, Jaime G. Carbonell, Charles Rich, Raymond Reiter, Hartmut Wedekind, Patrick J. Hayes:
Presentation (discussion). Workshop on Data Abstraction, Databases and Conceptual Modelling 1980: 62-71 - [c6]John Miles Smith, Charles Rich, Jonathan J. King, Peter Hitchcock, Alexander Borgida, Jaime G. Carbonell:
Consistency of Models (discussion). Workshop on Data Abstraction, Databases and Conceptual Modelling 1980: 72-76 - [c5]Jaime G. Carbonell:
Default Reasoning and Inheritance Mechanisms on Type Hierarchies. Workshop on Data Abstraction, Databases and Conceptual Modelling 1980: 107-109
1970 – 1979
- 1979
- [c4]Jaime G. Carbonell:
Towards a Self-Extending Parser. ACL 1979 - [c3]Jaime G. Carbonell:
Computer Models of Human Personality Traits. IJCAI 1979: 121-123 - [c2]Jaime G. Carbonell:
The Counterplanning Process: Reasoning under Adversity. IJCAI 1979: 124-130 - 1978
- [j2]Jaime G. Carbonell:
POLITICS: Automated Ideological Reasoning. Cogn. Sci. 2(1): 27-51 (1978) - [j1]Jaime G. Carbonell, Roger C. Schank:
Comments on the paper of Cherniavsky: "On artificial intelligence and attempts to disprove its existance". Inf. Syst. 3(3): 227-230 (1978) - [c1]Jaime G. Carbonell:
Intentlonallty and Human Conversations. TINLAP 1978: 141-148
Coauthor Index
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