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2020 – today
- 2023
[c62]Chaitanya Malaviya, Peter Shaw, Ming-Wei Chang, Kenton Lee, Kristina Toutanova:
QUEST: A Retrieval Dataset of Entity-Seeking Queries with Implicit Set Operations. ACL (1) 2023: 14032-14047- [c61]Zhuyun Dai, Vincent Y. Zhao, Ji Ma, Yi Luan, Jianmo Ni, Jing Lu, Anton Bakalov, Kelvin Guu, Keith B. Hall, Ming-Wei Chang:
Promptagator: Few-shot Dense Retrieval From 8 Examples. ICLR 2023 - [c60]Kenton Lee, Mandar Joshi, Iulia Raluca Turc, Hexiang Hu, Fangyu Liu, Julian Martin Eisenschlos, Urvashi Khandelwal, Peter Shaw, Ming-Wei Chang, Kristina Toutanova:
Pix2Struct: Screenshot Parsing as Pretraining for Visual Language Understanding. ICML 2023: 18893-18912 - [i38]Hexiang Hu, Yi Luan, Yang Chen, Urvashi Khandelwal, Mandar Joshi, Kenton Lee, Kristina Toutanova, Ming-Wei Chang:
Open-domain Visual Entity Recognition: Towards Recognizing Millions of Wikipedia Entities. CoRR abs/2302.11154 (2023) - [i37]Yang Chen, Hexiang Hu, Yi Luan, Haitian Sun, Soravit Changpinyo, Alan Ritter, Ming-Wei Chang:
Can Pre-trained Vision and Language Models Answer Visual Information-Seeking Questions? CoRR abs/2302.11713 (2023) - [i36]Wenhu Chen, Hexiang Hu, Yandong Li, Nataniel Ruiz, Xuhui Jia, Ming-Wei Chang, William W. Cohen:
Subject-driven Text-to-Image Generation via Apprenticeship Learning. CoRR abs/2304.00186 (2023) - [i35]Jinhyuk Lee, Zhuyun Dai, Sai Meher Karthik Duddu, Tao Lei, Iftekhar Naim, Ming-Wei Chang, Vincent Y. Zhao:
Rethinking the Role of Token Retrieval in Multi-Vector Retrieval. CoRR abs/2304.01982 (2023) - [i34]Tao Lei, Junwen Bai, Siddhartha Brahma, Joshua Ainslie, Kenton Lee, Yanqi Zhou, Nan Du, Vincent Y. Zhao, Yuexin Wu, Bo Li, Yu Zhang, Ming-Wei Chang:
Conditional Adapters: Parameter-efficient Transfer Learning with Fast Inference. CoRR abs/2304.04947 (2023) - [i33]Chaitanya Malaviya, Peter Shaw, Ming-Wei Chang, Kenton Lee, Kristina Toutanova:
QUEST: A Retrieval Dataset of Entity-Seeking Queries with Implicit Set Operations. CoRR abs/2305.11694 (2023) - 2022
- [c59]Ivan Stelmakh, Yi Luan, Bhuwan Dhingra, Ming-Wei Chang:
ASQA: Factoid Questions Meet Long-Form Answers. EMNLP 2022: 8273-8288 - [c58]Kevin Clark, Kelvin Guu, Ming-Wei Chang, Panupong Pasupat, Geoffrey E. Hinton, Mohammad Norouzi:
Meta-Learning Fast Weight Language Models. EMNLP 2022: 9751-9757 - [c57]Jianmo Ni, Chen Qu, Jing Lu, Zhuyun Dai, Gustavo Hernández Ábrego, Ji Ma, Vincent Y. Zhao, Yi Luan, Keith B. Hall, Ming-Wei Chang, Yinfei Yang:
Large Dual Encoders Are Generalizable Retrievers. EMNLP 2022: 9844-9855 - [c56]Robert L. Logan IV, Alexandre Passos, Sameer Singh, Ming-Wei Chang:
FRUIT: Faithfully Reflecting Updated Information in Text. NAACL-HLT 2022: 3670-3686 - [i32]Ivan Stelmakh, Yi Luan, Bhuwan Dhingra, Ming-Wei Chang:
ASQA: Factoid Questions Meet Long-Form Answers. CoRR abs/2204.06092 (2022) - [i31]Zhuyun Dai, Vincent Y. Zhao, Ji Ma, Yi Luan, Jianmo Ni, Jing Lu, Anton Bakalov, Kelvin Guu, Keith B. Hall
, Ming-Wei Chang:
Promptagator: Few-shot Dense Retrieval From 8 Examples. CoRR abs/2209.11755 (2022) - [i30]Kenton Lee, Mandar Joshi, Iulia Turc, Hexiang Hu, Fangyu Liu, Julian Eisenschlos, Urvashi Khandelwal, Peter Shaw, Ming-Wei Chang, Kristina Toutanova:
Pix2Struct: Screenshot Parsing as Pretraining for Visual Language Understanding. CoRR abs/2210.03347 (2022) - [i29]Kevin Clark, Kelvin Guu, Ming-Wei Chang, Panupong Pasupat, Geoffrey E. Hinton, Mohammad Norouzi:
Meta-Learning Fast Weight Language Models. CoRR abs/2212.02475 (2022) - 2021
- [c55]Peter Shaw, Ming-Wei Chang, Panupong Pasupat, Kristina Toutanova:
Compositional Generalization and Natural Language Variation: Can a Semantic Parsing Approach Handle Both? ACL/IJCNLP (1) 2021: 922-938 - [c54]Sewon Min, Kenton Lee, Ming-Wei Chang, Kristina Toutanova, Hannaneh Hajishirzi:
Joint Passage Ranking for Diverse Multi-Answer Retrieval. EMNLP (1) 2021: 6997-7008 - [c53]Wenhu Chen, Ming-Wei Chang, Eva Schlinger, William Yang Wang, William W. Cohen:
Open Question Answering over Tables and Text. ICLR 2021 - [i28]Jonathan Herzig, Peter Shaw, Ming-Wei Chang, Kelvin Guu, Panupong Pasupat, Yuan Zhang:
Unlocking Compositional Generalization in Pre-trained Models Using Intermediate Representations. CoRR abs/2104.07478 (2021) - [i27]Sewon Min, Kenton Lee, Ming-Wei Chang, Kristina Toutanova, Hannaneh Hajishirzi:
Joint Passage Ranking for Diverse Multi-Answer Retrieval. CoRR abs/2104.08445 (2021) - [i26]Iulia Turc, Kenton Lee, Jacob Eisenstein, Ming-Wei Chang, Kristina Toutanova:
Revisiting the Primacy of English in Zero-shot Cross-lingual Transfer. CoRR abs/2106.16171 (2021) - [i25]Jianmo Ni, Chen Qu, Jing Lu, Zhuyun Dai, Gustavo Hernández Ábrego, Ji Ma, Vincent Y. Zhao, Yi Luan, Keith B. Hall, Ming-Wei Chang, Yinfei Yang:
Large Dual Encoders Are Generalizable Retrievers. CoRR abs/2112.07899 (2021) - [i24]Robert L. Logan IV, Alexandre Passos, Sameer Singh, Ming-Wei Chang:
FRUIT: Faithfully Reflecting Updated Information in Text. CoRR abs/2112.08634 (2021) - 2020
- [c52]Hao Cheng, Ming-Wei Chang, Kenton Lee, Kristina Toutanova:
Probabilistic Assumptions Matter: Improved Models for Distantly-Supervised Document-Level Question Answering. ACL 2020: 5657-5667 - [c51]Alane Suhr, Ming-Wei Chang, Peter Shaw, Kenton Lee:
Exploring Unexplored Generalization Challenges for Cross-Database Semantic Parsing. ACL 2020: 8372-8388 - [c50]Adam Fisch, Kenton Lee, Ming-Wei Chang, Jonathan H. Clark, Regina Barzilay:
CapWAP: Image Captioning with a Purpose. EMNLP (1) 2020: 8755-8768 - [c49]Kelvin Guu, Kenton Lee, Zora Tung, Panupong Pasupat, Ming-Wei Chang:
Retrieval Augmented Language Model Pre-Training. ICML 2020: 3929-3938 - [i23]Kelvin Guu, Kenton Lee, Zora Tung, Panupong Pasupat, Ming-Wei Chang:
REALM: Retrieval-Augmented Language Model Pre-Training. CoRR abs/2002.08909 (2020) - [i22]Hao Cheng, Ming-Wei Chang, Kenton Lee, Kristina Toutanova:
Probabilistic Assumptions Matter: Improved Models for Distantly-Supervised Document-Level Question Answering. CoRR abs/2005.01898 (2020) - [i21]Wenhu Chen, Ming-Wei Chang, Eva Schlinger, William Yang Wang, William W. Cohen:
Open Question Answering over Tables and Text. CoRR abs/2010.10439 (2020) - [i20]Peter Shaw, Ming-Wei Chang, Panupong Pasupat, Kristina Toutanova:
Compositional Generalization and Natural Language Variation: Can a Semantic Parsing Approach Handle Both? CoRR abs/2010.12725 (2020) - [i19]Adam Fisch, Kenton Lee, Ming-Wei Chang, Jonathan H. Clark, Regina Barzilay:
CapWAP: Captioning with a Purpose. CoRR abs/2011.04264 (2020)
2010 – 2019
- 2019
- [j12]Tom Kwiatkowski, Jennimaria Palomaki, Olivia Redfield, Michael Collins, Ankur P. Parikh, Chris Alberti, Danielle Epstein, Illia Polosukhin, Jacob Devlin, Kenton Lee, Kristina Toutanova, Llion Jones, Matthew Kelcey, Ming-Wei Chang, Andrew M. Dai, Jakob Uszkoreit, Quoc Le, Slav Petrov:
Natural Questions: a Benchmark for Question Answering Research. Trans. Assoc. Comput. Linguistics 7: 452-466 (2019) - [c48]Lajanugen Logeswaran, Ming-Wei Chang, Kenton Lee, Kristina Toutanova, Jacob Devlin, Honglak Lee:
Zero-Shot Entity Linking by Reading Entity Descriptions. ACL (1) 2019: 3449-3460 - [c47]Bhuwan Dhingra, Manaal Faruqui, Ankur P. Parikh, Ming-Wei Chang, Dipanjan Das, William W. Cohen:
Handling Divergent Reference Texts when Evaluating Table-to-Text Generation. ACL (1) 2019: 4884-4895 - [c46]Kenton Lee, Ming-Wei Chang, Kristina Toutanova:
Latent Retrieval for Weakly Supervised Open Domain Question Answering. ACL (1) 2019: 6086-6096 - [c45]Christopher Clark, Kenton Lee, Ming-Wei Chang, Tom Kwiatkowski, Michael Collins, Kristina Toutanova:
BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions. NAACL-HLT (1) 2019: 2924-2936 - [c44]Jacob Devlin, Ming-Wei Chang, Kenton Lee, Kristina Toutanova:
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. NAACL-HLT (1) 2019: 4171-4186 - [i18]Ming-Wei Chang, Kristina Toutanova, Kenton Lee, Jacob Devlin:
Language Model Pre-training for Hierarchical Document Representations. CoRR abs/1901.09128 (2019) - [i17]Christopher Clark, Kenton Lee, Ming-Wei Chang, Tom Kwiatkowski, Michael Collins, Kristina Toutanova:
BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions. CoRR abs/1905.10044 (2019) - [i16]Kenton Lee, Ming-Wei Chang, Kristina Toutanova:
Latent Retrieval for Weakly Supervised Open Domain Question Answering. CoRR abs/1906.00300 (2019) - [i15]Bhuwan Dhingra, Manaal Faruqui, Ankur P. Parikh, Ming-Wei Chang, Dipanjan Das, William W. Cohen:
Handling Divergent Reference Texts when Evaluating Table-to-Text Generation. CoRR abs/1906.01081 (2019) - [i14]Lajanugen Logeswaran, Ming-Wei Chang, Kenton Lee, Kristina Toutanova, Jacob Devlin, Honglak Lee:
Zero-Shot Entity Linking by Reading Entity Descriptions. CoRR abs/1906.07348 (2019) - [i13]Iulia Turc, Ming-Wei Chang, Kenton Lee, Kristina Toutanova:
Well-Read Students Learn Better: The Impact of Student Initialization on Knowledge Distillation. CoRR abs/1908.08962 (2019) - 2018
- [c43]Marjan Ghazvininejad, Chris Brockett, Ming-Wei Chang, Bill Dolan, Jianfeng Gao, Wen-tau Yih, Michel Galley:
A Knowledge-Grounded Neural Conversation Model. AAAI 2018: 5110-5117 - [c42]Dipendra Misra, Ming-Wei Chang, Xiaodong He, Wen-tau Yih:
Policy Shaping and Generalized Update Equations for Semantic Parsing from Denotations. EMNLP 2018: 2442-2452 - [i12]Dipendra Misra, Ming-Wei Chang, Xiaodong He, Wen-tau Yih:
Policy Shaping and Generalized Update Equations for Semantic Parsing from Denotations. CoRR abs/1809.01299 (2018) - [i11]Jacob Devlin, Ming-Wei Chang, Kenton Lee, Kristina Toutanova:
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. CoRR abs/1810.04805 (2018) - [i10]Hao Cheng, Ming-Wei Chang, Kenton Lee, Ankur P. Parikh, Michael Collins, Kristina Toutanova:
Improving Span-based Question Answering Systems with Coarsely Labeled Data. CoRR abs/1811.02076 (2018) - 2017
- [c41]Mohit Iyyer, Wen-tau Yih, Ming-Wei Chang:
Search-based Neural Structured Learning for Sequential Question Answering. ACL (1) 2017: 1821-1831 - [c40]Shyam Upadhyay, Ming-Wei Chang:
Annotating Derivations: A New Evaluation Strategy and Dataset for Algebra Word Problems. EACL (1) 2017: 494-504 - [c39]Haoruo Peng, Ming-Wei Chang, Wen-tau Yih:
Maximum Margin Reward Networks for Learning from Explicit and Implicit Supervision. EMNLP 2017: 2368-2378 - [c38]Yelong Shen, Po-Sen Huang, Ming-Wei Chang, Jianfeng Gao:
Modeling Large-Scale Structured Relationships with Shared Memory for Knowledge Base Completion. Rep4NLP@ACL 2017: 57-68 - [e3]Kai-Wei Chang, Ming-Wei Chang, Vivek Srikumar, Alexander M. Rush:
Proceedings of the 2nd Workshop on Structured Prediction for Natural Language Processing, SPNLP@EMNLP, Copenhagen, Denmark, September 2017. Association for Computational Linguistics 2017, ISBN 978-1-945626-93-7 [contents] - [i9]Marjan Ghazvininejad, Chris Brockett, Ming-Wei Chang, Bill Dolan, Jianfeng Gao, Wen-tau Yih, Michel Galley:
A Knowledge-Grounded Neural Conversation Model. CoRR abs/1702.01932 (2017) - 2016
- [c37]Wen-tau Yih, Matthew Richardson, Christopher Meek, Ming-Wei Chang, Jina Suh:
The Value of Semantic Parse Labeling for Knowledge Base Question Answering. ACL (2) 2016 - [c36]Ming-Wei Chang:
From Entity Linking to Question Answering - Recent Progress on Semantic Grounding Tasks. NUT@COLING 2016: 2 - [c35]Shyam Upadhyay, Ming-Wei Chang, Kai-Wei Chang, Wen-tau Yih:
Learning from Explicit and Implicit Supervision Jointly For Algebra Word Problems. EMNLP 2016: 297-306 - [c34]Yi Yang, Ming-Wei Chang, Jacob Eisenstein:
Toward Socially-Infused Information Extraction: Embedding Authors, Mentions, and Entities. EMNLP 2016: 1452-1461 - [e2]Kai-Wei Chang, Ming-Wei Chang, Alexander M. Rush, Vivek Srikumar:
Proceedings of the Workshop on Structured Prediction for NLP@EMNLP 2016, Austin, TX, USA, November 5, 2016. Association for Computational Linguistics 2016, ISBN 978-1-945626-29-6 [contents] - [i8]Shyam Upadhyay, Ming-Wei Chang:
Annotating Derivations: A New Evaluation Strategy and Dataset for Algebra Word Problems. CoRR abs/1609.07197 (2016) - [i7]Yi Yang, Ming-Wei Chang:
S-MART: Novel Tree-based Structured Learning Algorithms Applied to Tweet Entity Linking. CoRR abs/1609.08075 (2016) - [i6]Yi Yang, Ming-Wei Chang, Jacob Eisenstein:
Toward Socially-Infused Information Extraction: Embedding Authors, Mentions, and Entities. CoRR abs/1609.08084 (2016) - [i5]Mohit Iyyer, Wen-tau Yih, Ming-Wei Chang:
Answering Complicated Question Intents Expressed in Decomposed Question Sequences. CoRR abs/1611.01242 (2016) - [i4]Yelong Shen, Po-Sen Huang, Ming-Wei Chang, Jianfeng Gao:
Implicit ReasoNet: Modeling Large-Scale Structured Relationships with Shared Memory. CoRR abs/1611.04642 (2016) - 2015
- [c33]Yi Yang, Ming-Wei Chang:
S-MART: Novel Tree-based Structured Learning Algorithms Applied to Tweet Entity Linking. ACL (1) 2015: 504-513 - [c32]Wen-tau Yih, Ming-Wei Chang, Xiaodong He, Jianfeng Gao:
Semantic Parsing via Staged Query Graph Generation: Question Answering with Knowledge Base. ACL (1) 2015: 1321-1331 - [c31]Arvind Neelakantan, Ming-Wei Chang:
Inferring Missing Entity Type Instances for Knowledge Base Completion: New Dataset and Methods. HLT-NAACL 2015: 515-525 - [c30]John Krumm, Dany Rouhana, Ming-Wei Chang:
Placer++: Semantic place labels beyond the visit. PerCom 2015: 11-19 - [c29]Huan Sun, Hao Ma, Wen-tau Yih, Chen-Tse Tsai, Jingjing Liu, Ming-Wei Chang:
Open Domain Question Answering via Semantic Enrichment. WWW 2015: 1045-1055 - [i3]Arvind Neelakantan, Ming-Wei Chang:
Inferring Missing Entity Type Instances for Knowledge Base Completion: New Dataset and Methods. CoRR abs/1504.06658 (2015) - [i2]Kai-Wei Chang, Shyam Upadhyay, Ming-Wei Chang, Vivek Srikumar, Dan Roth:
IllinoisSL: A JAVA Library for Structured Prediction. CoRR abs/1509.07179 (2015) - 2014
- [j11]David Carmel, Ming-Wei Chang, Evgeniy Gabrilovich, Bo-June Paul Hsu, Kuansan Wang:
ERD'14: Entity Recognition and Disambiguation Challenge. SIGIR Forum 48(2): 63-77 (2014) - [j10]Yuan Fang, Ming-Wei Chang:
Entity Linking on Microblogs with Spatial and Temporal Signals. Trans. Assoc. Comput. Linguistics 2: 259-272 (2014) - [c28]Dan Roth, Heng Ji, Ming-Wei Chang, Taylor Cassidy:
Wikification and Beyond: The Challenges of Entity and Concept Grounding. ACL (Tutorial Abstracts) 2014: 7 - [c27]Ming-Wei Chang, Tzi-cker Chiueh, Chia-Ming Chang:
Virtual keyboard for head mounted display-based wearable devices. ICPADS 2014: 225-232 - [c26]Ming-Wei Chang, Bo-June Paul Hsu, Hao Ma, Ricky Loynd, Kuansan Wang:
E2E: An End-to-End Entity Linking System for Short and Noisy Text. #MSM 2014: 62-63 - [c25]Hsin-Wei Wang, Ming-Wei Chang, Hong Shiang Lin, Ming Ouhyoung:
Segmentation based stereo matching using color grouping. SIGGRAPH Posters 2014: 73:1 - [c24]Hongning Wang, Yang Song, Ming-Wei Chang, Xiaodong He, Ahmed Hassan Awadallah, Ryen W. White:
Modeling action-level satisfaction for search task satisfaction prediction. SIGIR 2014: 123-132 - [c23]David Carmel, Ming-Wei Chang, Evgeniy Gabrilovich, Bo-June Paul Hsu, Kuansan Wang:
ERD'14: entity recognition and disambiguation challenge. SIGIR 2014: 1292 - [e1]David Carmel, Ming-Wei Chang, Evgeniy Gabrilovich, Bo-June Paul Hsu, Kuansan Wang:
ERD'14, Proceedings of the First ACM International Workshop on Entity Recognition & Disambiguation, July 11, 2014, Gold Coast, Queensland, Australia. ACM 2014, ISBN 978-1-4503-3023-7 [contents] - 2013
- [j9]Ming-Wei Chang, Wen-tau Yih:
Dual Coordinate Descent Algorithms for Efficient Large Margin Structured Prediction. Trans. Assoc. Comput. Linguistics 1: 207-218 (2013) - [c22]Wen-tau Yih, Ming-Wei Chang, Christopher Meek, Andrzej Pastusiak:
Question Answering Using Enhanced Lexical Semantic Models. ACL (1) 2013: 1744-1753 - [c21]Stephen Guo, Ming-Wei Chang, Emre Kiciman:
To Link or Not to Link? A Study on End-to-End Tweet Entity Linking. HLT-NAACL 2013: 1020-1030 - [c20]Hongning Wang, Xiaodong He, Ming-Wei Chang, Yang Song, Ryen W. White, Wei Chu:
Personalized ranking model adaptation for web search. SIGIR 2013: 323-332 - [c19]Hongning Wang, Yang Song, Ming-Wei Chang, Xiaodong He, Ryen W. White, Wei Chu:
Learning to extract cross-session search tasks. WWW 2013: 1353-1364 - 2012
- [j8]Ming-Wei Chang, Lev-Arie Ratinov, Dan Roth:
Structured learning with constrained conditional models. Mach. Learn. 88(3): 399-431 (2012) - [c18]Ian Endres, Vivek Srikumar, Ming-Wei Chang, Derek Hoiem:
Learning shared body plans. CVPR 2012: 3130-3137 - [c17]Rajhans Samdani, Ming-Wei Chang, Dan Roth:
Unified Expectation Maximization. HLT-NAACL 2012: 688-698 - 2011
- [b1]Ming-Wei Chang:
Structured prediction with indirect supervision. University of Illinois Urbana-Champaign, USA, 2011 - [c16]Ming-Wei Chang, James Clarke, Dan Goldwasser, Lev-Arie Ratinov, Vivek Srikumar, Dan Roth:
Structured prediction with indirect supervision. MLSLP 2011 - 2010
- [j7]Ching-En Tseng, Ching-Yu Peng, Ming-Wei Chang, Jia-Yush Yen, Chih-Kung Lee, Tse-Shih Huang:
Novel Approach to Fuzzy-Wavelet ECG Signal Analysis for a Mobile Device. J. Medical Syst. 34(1): 71-81 (2010) - [j6]Ching-En Tseng, Jia-Yush Yen, Ming-Wei Chang, Wei-Chien Chang, Chih-Kung Lee:
Modified Frequency-Partitioned Spectrum Estimation for a Wireless Health Advanced Monitoring Bio-Diagnosis System. IEEE Trans. Syst. Man Cybern. Part A 40(3): 611-622 (2010) - [c15]James Clarke, Dan Goldwasser, Ming-Wei Chang, Dan Roth:
Driving Semantic Parsing from the World's Response. CoNLL 2010: 18-27 - [c14]Ming-Wei Chang, Michael Connor, Dan Roth:
The Necessity of Combining Adaptation Methods. EMNLP 2010: 767-777 - [c13]Ming-Wei Chang, Vivek Srikumar, Dan Goldwasser, Dan Roth:
Structured Output Learning with Indirect Supervision. ICML 2010: 199-206 - [c12]Ming-Wei Chang, Dan Goldwasser, Dan Roth, Vivek Srikumar:
Discriminative Learning over Constrained Latent Representations. HLT-NAACL 2010: 429-437
2000 – 2009
- 2009
- [c11]Ming-Wei Chang, Shau-Yin Tseng, Homn Lin, Ching-Lung Su:
Implementation and Optimization of DSP Suspend Resume on Dual-Core SOC. ICESS 2009: 185-190 - [c10]Ming-Wei Chang, Dan Goldwasser, Dan Roth, Yuancheng Tu:
Unsupervised Constraint Driven Learning For Transliteration Discovery. HLT-NAACL 2009: 299-307 - [i1]Mark Sammons, V. G. Vinod Vydiswaran, Tim Vieira, Nikhil Johri, Ming-Wei Chang, Dan Goldwasser, Vivek Srikumar, Gourab Kundu, Yuancheng Tu, Kevin Small, Joshua S. Rule, Quang Do, Dan Roth:
Relation Alignment for Textual Entailment Recognition. TAC 2009 - 2008
- [c9]Ming-Wei Chang, Lev-Arie Ratinov, Dan Roth, Vivek Srikumar:
Importance of Semantic Representation: Dataless Classification. AAAI 2008: 830-835 - [c8]Ming-Wei Chang, Lev-Arie Ratinov, Nicholas Rizzolo, Dan Roth:
Learning and Inference with Constraints. AAAI 2008: 1513-1518 - [c7]Ming-Wei Chang, Scott Yih, Robert McCann:
Personalized Spam Filtering for Gray Mail. CEAS 2008 - [c6]Ming-Wei Chang, Wen-tau Yih, Christopher Meek:
Partitioned logistic regression for spam filtering. KDD 2008: 97-105 - [c5]Chien-Wei Chen, Chuan-Yue Yang, Tei-Wei Kuo, Ming-Wei Chang:
Energy-Efficient Real-Time Co-scheduling of Multimedia DSP Jobs. SUTC 2008: 225-232 - 2007
- [j5]Ching-Liang Dai, Heng-Ming Hsu, Ming-Chang Tsai, Ming-Ming Hsieh, Ming-Wei Chang:
Modeling and fabrication of a microelectromechanical microwave switch. Microelectron. J. 38(4-5): 519-524 (2007) - [j4]Ching-Liang Dai, Ming-Chao Chiang, Ming-Wei Chang:
Simulation and fabrication of HF microelectromechanical bandpass filter. Microelectron. J. 38(8-9): 828-833 (2007) - [j3]Ching-Liang Dai, Shih-Chieh Lin, Ming-Wei Chang:
Fabrication and characterization of a microelectromechanical tunable capacitor. Microelectron. J. 38(12): 1257-1262 (2007) - [c4]Ming-Wei Chang, Lev-Arie Ratinov, Dan Roth:
Guiding Semi-Supervision with Constraint-Driven Learning. ACL 2007 - 2006
- [c3]Ming-Wei Chang, Quang Do, Dan Roth:
A Pipeline Framework for Dependency Parsing. ACL 2006 - [c2]Ming-Wei Chang, Quang Do, Dan Roth:
A Pipeline Model for Bottom-Up Dependency Parsing. CoNLL 2006: 186-190 - 2005
- [j2]Ming-Wei Chang, Chih-Jen Lin:
Leave-One-Out Bounds for Support Vector Regression Model Selection. Neural Comput. 17(5): 1188-1222 (2005) - 2004
- [j1]Ming-Wei Chang, Chih-Jen Lin, Ruby Chiu-Hsing Weng:
Analysis of switching dynamics with competing support vector machines. IEEE Trans. Neural Networks 15(3): 720-727 (2004) - 2002
- [c1]Ming-Wei Chang, Chih-Jen Lin, Ruby C. Weng:
Analysis of Nonstationary Time Series Using Support Vector Machines. SVM 2002: 160-170