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ORCIDJeff A. Bilmes
Jeffrey A. Bilmes
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- affiliation: University of Washington, Seattle, WA, USA
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2020 – today
- 2024
[c215]Gantavya Bhatt, Yifang Chen, Arnav Mohanty Das, Jifan Zhang, Sang T. Truong, Stephen Mussmann, Yinglun Zhu, Jeff A. Bilmes, Simon S. Du, Kevin G. Jamieson, Jordan T. Ash, Robert D. Nowak:
An Experimental Design Framework for Label-Efficient Supervised Finetuning of Large Language Models. ACL (Findings) 2024: 6549-6560- [c214]Lilly Kumari, Shengjie Wang, Arnav Das, Tianyi Zhou, Jeff A. Bilmes:
An End-to-End Submodular Framework for Data-Efficient In-Context Learning. NAACL-HLT (Findings) 2024: 3293-3308 - [i52]Gantavya Bhatt, Yifang Chen, Arnav Mohanty Das, Jifan Zhang, Sang T. Truong, Stephen Mussmann, Yinglun Zhu, Jeffrey A. Bilmes, Simon S. Du, Kevin G. Jamieson, Jordan T. Ash, Robert D. Nowak:
An Experimental Design Framework for Label-Efficient Supervised Finetuning of Large Language Models. CoRR abs/2401.06692 (2024) - [i51]Gantavya Bhatt, Arnav Das, Jeff A. Bilmes:
Deep Submodular Peripteral Networks. CoRR abs/2403.08199 (2024) - 2023
- [j40]Andy Lin, Brooke L. Deatherage Kaiser, Janine R. Hutchison, Jeffrey A. Bilmes, William Stafford Noble
:
MS1Connect: a mass spectrometry run similarity measure. Bioinform. 39(2) (2023) - [j39]Arnav Mohanty Das, Gantavya Bhatt, Megh Manoj Bhalerao, Vianne R. Gao, Rui Yang, Jeff A. Bilmes:
Accelerating Batch Active Learning Using Continual Learning Techniques. Trans. Mach. Learn. Res. 2023 (2023) - [c213]Akarsh Prabhakara, Tao Jin, Arnav Das, Gantavya Bhatt, Lilly Kumari, Elahe Soltanaghai, Jeff A. Bilmes, Swarun Kumar, Anthony Rowe:
High Resolution Point Clouds from mmWave Radar. ICRA 2023: 4135-4142 - [c212]Akarsh Prabhakara, Tao Jin, Arnav Das, Gantavya Bhatt, Lilly Kumari, Elahe Soltanaghai, Jeff A. Bilmes, Swarun Kumar, Anthony Rowe:
RadarHD: Demonstrating Lidar-like Point Clouds from mmWave Radar. MobiCom 2023: 106:1-106:3 - [i50]Arnav Mohanty Das, Gantavya Bhatt, Megh Bhalerao, Vianne R. Gao, Rui Yang, Jeff A. Bilmes:
Accelerating Batch Active Learning Using Continual Learning Techniques. CoRR abs/2305.06408 (2023) - [i49]Sahil Verma, Gantavya Bhatt, Avi Schwarzschild, Soumye Singhal, Arnav Mohanty Das, Chirag Shah, John P. Dickerson, Jeff A. Bilmes:
Effective Backdoor Mitigation Depends on the Pre-training Objective. CoRR abs/2311.14948 (2023) - 2022
- [j38]Rishabh K. Iyer, Ninad Khargonkar, Jeff A. Bilmes, Himanshu Asnani:
Generalized Submodular Information Measures: Theoretical Properties, Examples, Optimization Algorithms, and Applications. IEEE Trans. Inf. Theory 68(2): 752-781 (2022) - [c211]Suraj Kothawade, Vishal Kaushal, Ganesh Ramakrishnan, Jeff A. Bilmes, Rishabh K. Iyer:
PRISM: A Rich Class of Parameterized Submodular Information Measures for Guided Data Subset Selection. AAAI 2022: 10238-10246 - [c210]Ravikumar Balakrishnan, Tian Li, Tianyi Zhou, Nageen Himayat, Virginia Smith, Jeff A. Bilmes:
Diverse Client Selection for Federated Learning via Submodular Maximization. ICLR 2022 - [c209]Lilly Kumari, Shengjie Wang, Tianyi Zhou, Jeff A. Bilmes:
Retrospective Adversarial Replay for Continual Learning. NeurIPS 2022 - [i48]Jeff A. Bilmes:
Submodularity In Machine Learning and Artificial Intelligence. CoRR abs/2202.00132 (2022) - [i47]Akarsh Prabhakara, Tao Jin, Arnav Das, Gantavya Bhatt, Lilly Kumari, Elahe Soltanaghaei, Jeff A. Bilmes, Swarun Kumar, Anthony G. Rowe:
High Resolution Point Clouds from mmWave Radar. CoRR abs/2206.09273 (2022) - [i46]Adhyyan Narang, Omid Sadeghi, Lillian J. Ratliff, Maryam Fazel, Jeff A. Bilmes:
Interactive Combinatorial Bandits: Balancing Competitivity and Complementarity. CoRR abs/2207.03091 (2022) - 2021
- [j37]Jacob M. Schreiber, Jeffrey A. Bilmes, William Stafford Noble:
Prioritizing transcriptomic and epigenomic experiments using an optimization strategy that leverages imputed data. Bioinform. 37(4): 439-447 (2021) - [j36]Yang Young Lu, Jeff A. Bilmes, Ricard A. Rodriguez-Mias, Judit Villén, William Stafford Noble:
DIAmeter: matching peptides to data-independent acquisition mass spectrometry data. Bioinform. 37(Supplement): 434-432 (2021) - [c208]Lilly Kumari, Jeff A. Bilmes:
Submodular Span, with Applications to Conditional Data Summarization. AAAI 2021: 12344-12352 - [c207]Tianyi Zhou, Shengjie Wang, Jeff A. Bilmes:
Curriculum Learning by Optimizing Learning Dynamics. AISTATS 2021: 433-441 - [c206]Rishabh K. Iyer, Ninad Khargoankar, Jeff A. Bilmes, Himanshu Asanani:
Submodular combinatorial information measures with applications in machine learning. ALT 2021: 722-754 - [c205]Tianyi Zhou, Shengjie Wang, Jeff A. Bilmes:
Robust Curriculum Learning: from clean label detection to noisy label self-correction. ICLR 2021 - [c204]Sunil Thulasidasan, Sushil Thapa, Sayera Dhaubhadel, Gopinath Chennupati, Tanmoy Bhattacharya, Jeff A. Bilmes:
An Effective Baseline for Robustness to Distributional Shift. ICMLA 2021: 278-285 - [c203]Himanshu Asnani, Jeff A. Bilmes, Rishabh K. Iyer:
Independence Properties of Generalized Submodular Information Measures. ISIT 2021: 999-1004 - [c202]Shengjie Wang, Tianyi Zhou, Chandrashekhar Lavania, Jeff A. Bilmes:
Constrained Robust Submodular Partitioning. NeurIPS 2021: 2721-2732 - [c201]Chandrashekhar Lavania, Kai Wei, Rishabh K. Iyer, Jeff A. Bilmes:
A Practical Online Framework for Extracting Running Video Summaries under a Fixed Memory Budget. SDM 2021: 226-234 - [i45]Vishal Kaushal, Suraj Kothawade, Ganesh Ramakrishnan, Jeff A. Bilmes, Rishabh K. Iyer:
PRISM: A Unified Framework of Parameterized Submodular Information Measures for Targeted Data Subset Selection and Summarization. CoRR abs/2103.00128 (2021) - [i44]Suraj Kothawade, Vishal Kaushal, Ganesh Ramakrishnan, Jeff A. Bilmes, Rishabh K. Iyer:
Submodular Mutual Information for Targeted Data Subset Selection. CoRR abs/2105.00043 (2021) - [i43]Sunil Thulasidasan, Sushil Thapa, Sayera Dhaubhadel, Gopinath Chennupati, Tanmoy Bhattacharya, Jeff A. Bilmes:
An Effective Baseline for Robustness to Distributional Shift. CoRR abs/2105.07107 (2021) - [i42]Himanshu Asnani, Jeff A. Bilmes, Rishabh K. Iyer:
Independence Properties of Generalized Submodular Information Measures. CoRR abs/2108.03154 (2021) - 2020
- [j35]Jacob M. Schreiber, Jeffrey A. Bilmes, William Stafford Noble:
apricot: Submodular selection for data summarization in Python. J. Mach. Learn. Res. 21: 161:1-161:6 (2020) - [c200]Jacob M. Schreiber, Timothy J. Durham, William S. Noble, Jeffrey A. Bilmes:
Avocado: Deep tensor factorization characterizes the human epigenome via imputation of tens of thousands of functional experiments. BCB 2020: 37:1 - [c199]Wei Yang, Jeffrey A. Bilmes, William Stafford Noble:
Submodular sketches of single-cell RNA-seq measurements. BCB 2020: 61:1-61:6 - [c198]Baharan Mirzasoleiman, Jeff A. Bilmes, Jure Leskovec:
Coresets for Data-efficient Training of Machine Learning Models. ICML 2020: 6950-6960 - [c197]Tianyi Zhou, Shengjie Wang, Jeff A. Bilmes:
Time-Consistent Self-Supervision for Semi-Supervised Learning. ICML 2020: 11523-11533 - [c196]Rishabh K. Iyer, Jeff A. Bilmes:
Concave Aspects of Submodular Functions. ISIT 2020: 72-77 - [c195]Tianyi Zhou, Shengjie Wang, Jeff A. Bilmes:
Curriculum Learning by Dynamic Instance Hardness. NeurIPS 2020 - [i41]Rishabh K. Iyer, Ninad Khargoankar, Jeff A. Bilmes, Himanshu Asanani:
Submodular Combinatorial Information Measures with Applications in Machine Learning. CoRR abs/2006.15412 (2020) - [i40]Rishabh K. Iyer, Jeff A. Bilmes:
Concave Aspects of Submodular Functions. CoRR abs/2006.16784 (2020) - [i39]Vishal Kaushal, Suraj Kothawade, Ganesh Ramakrishnan, Jeff A. Bilmes, Himanshu Asnani, Rishabh K. Iyer:
A Unified Framework for Generic, Query-Focused, Privacy Preserving and Update Summarization using Submodular Information Measures. CoRR abs/2010.05631 (2020)
2010 – 2019
- 2019
- [j34]Wenruo Bai, Jeffrey A. Bilmes, William S. Noble:
Submodular Generalized Matching for Peptide Identification in Tandem Mass Spectrometry. IEEE ACM Trans. Comput. Biol. Bioinform. 16(4): 1168-1181 (2019) - [c194]Rishabh K. Iyer, Jeffrey A. Bilmes:
Near Optimal Algorithms for Hard Submodular Programs with Discounted Cooperative Costs. AISTATS 2019: 276-285 - [c193]Rishabh K. Iyer, Jeffrey A. Bilmes:
A Memoization Framework for Scaling Submodular Optimization to Large Scale Problems. AISTATS 2019: 2340-2349 - [c192]Shengjie Wang, Wenruo Bai, Chandrashekhar Lavania, Jeff A. Bilmes:
Fixing Mini-batch Sequences with Hierarchical Robust Partitioning. AISTATS 2019: 3352-3361 - [c191]Sunil Thulasidasan, Tanmoy Bhattacharya, Jeff A. Bilmes, Gopinath Chennupati, Jamal Mohd-Yusof:
Combating Label Noise in Deep Learning using Abstention. ICML 2019: 6234-6243 - [c190]Shengjie Wang, Tianyi Zhou, Jeff A. Bilmes:
Bias Also Matters: Bias Attribution for Deep Neural Network Explanation. ICML 2019: 6659-6667 - [c189]Shengjie Wang, Tianyi Zhou, Jeff A. Bilmes:
Jumpout : Improved Dropout for Deep Neural Networks with ReLUs. ICML 2019: 6668-6676 - [c188]Sunil Thulasidasan, Gopinath Chennupati, Jeff A. Bilmes, Tanmoy Bhattacharya, Sarah Michalak:
On Mixup Training: Improved Calibration and Predictive Uncertainty for Deep Neural Networks. NeurIPS 2019: 13888-13899 - [c187]Chandrashekhar Lavania, Jeff A. Bilmes:
Auto-Summarization: A Step Towards Unsupervised Learning of a Submodular Mixture. SDM 2019: 396-404 - [i38]Rishabh K. Iyer, Jeff A. Bilmes:
Near Optimal Algorithms for Hard Submodular Programs with Discounted Cooperative Costs. CoRR abs/1902.10172 (2019) - [i37]Rishabh K. Iyer, Jeff A. Bilmes:
A Memoization Framework for Scaling Submodular Optimization to Large Scale Problems. CoRR abs/1902.10176 (2019) - [i36]Sunil Thulasidasan, Tanmoy Bhattacharya, Jeff A. Bilmes, Gopinath Chennupati, Jamal Mohd-Yusof:
Combating Label Noise in Deep Learning Using Abstention. CoRR abs/1905.10964 (2019) - [i35]Sunil Thulasidasan, Gopinath Chennupati, Jeff A. Bilmes, Tanmoy Bhattacharya, Sarah Michalak:
On Mixup Training: Improved Calibration and Predictive Uncertainty for Deep Neural Networks. CoRR abs/1905.11001 (2019) - [i34]Baharan Mirzasoleiman, Jeff A. Bilmes, Jure Leskovec:
Data Sketching for Faster Training of Machine Learning Models. CoRR abs/1906.01827 (2019) - [i33]Jacob M. Schreiber, Jeffrey A. Bilmes, William Stafford Noble:
apricot: Submodular selection for data summarization in Python. CoRR abs/1906.03543 (2019) - 2018
- [j33]Rachel C. W. Chan, Maxwell W. Libbrecht, Eric G. Roberts, Jeffrey A. Bilmes, William Stafford Noble, Michael M. Hoffman:
Segway 2.0: Gaussian mixture models and minibatch training. Bioinform. 34(4): 669-671 (2018) - [c186]Maxwell W. Libbrecht, Jeffrey A. Bilmes, William Stafford Noble:
Choosing Non-redundant Representative Subsets Of Protein Sequence Data Sets Using Submodular Optimization. BCB 2018: 566 - [c185]Tianyi Zhou, Jeff A. Bilmes:
Minimax Curriculum Learning: Machine Teaching with Desirable Difficulties and Scheduled Diversity. ICLR (Poster) 2018 - [c184]Wenruo Bai, Jeffrey A. Bilmes:
Greed is Still Good: Maximizing Monotone Submodular+Supermodular (BP) Functions. ICML 2018: 314-323 - [c183]Andrew Cotter, Mahdi Milani Fard, Seungil You, Maya R. Gupta, Jeff A. Bilmes:
Constrained Interacting Submodular Groupings. ICML 2018: 1076-1085 - [c182]Tianyi Zhou, Shengjie Wang, Jeff A. Bilmes:
Diverse Ensemble Evolution: Curriculum Data-Model Marriage. NeurIPS 2018: 5909-5920 - [c181]Wenruo Bai, William Stafford Noble, Jeff A. Bilmes:
Submodular Maximization via Gradient Ascent: The Case of Deep Submodular Functions. NeurIPS 2018: 7989-7999 - [i32]Wenruo Bai, Jeffrey A. Bilmes:
Greed is Still Good: Maximizing Monotone Submodular+Supermodular Functions. CoRR abs/1801.07413 (2018) - 2017
- [j32]Yuzong Liu, Rishabh K. Iyer, Katrin Kirchhoff, Jeff A. Bilmes:
SVitchboard-II and FiSVer-I: Crafting high quality and low complexity conversational english speech corpora using submodular function optimization. Comput. Speech Lang. 42: 122-142 (2017) - [j31]Stefanie Jegelka, Jeff A. Bilmes:
Graph cuts with interacting edge weights: examples, approximations, and algorithms. Math. Program. 162(1-2): 241-282 (2017) - [c180]Tianyi Zhou, Hua Ouyang, Jeff A. Bilmes, Yi Chang, Carlos Guestrin:
Scaling Submodular Maximization via Pruned Submodularity Graphs. AISTATS 2017: 316-324 - [c179]Sunil Thulasidasan, Jeffrey A. Bilmes:
Acoustic classification using semi-supervised Deep Neural Networks and stochastic entropy-regularization over nearest-neighbor graphs. ICASSP 2017: 2731-2735 - [c178]Chandrashekhar Lavania, Jeff A. Bilmes:
Reducing total latency in online real-time inference and decoding via combined context window and model smoothing latencies. ICASSP 2017: 2791-2795 - [c177]Shengjie Wang, Haoran Cai, Jeff A. Bilmes, William S. Noble:
Training Compressed Fully-Connected Networks with a Density-Diversity Penalty. ICLR (Poster) 2017 - [d2]Rachel C. W. Chan, Maxwell W. Libbrecht, Eric G. Roberts, Jeffrey A. Bilmes, William Stafford Noble, Michael M. Hoffman:
Segway 2.0 Application Note Datasets. Zenodo, 2017
- [d1]Rachel C. W. Chan, Maxwell W. Libbrecht, Eric G. Roberts, Jeffrey A. Bilmes, William Stafford Noble, Michael M. Hoffman:
Segway 2.0 Application Note Scripts. Zenodo, 2017 - [i31]Jeffrey A. Bilmes, Wenruo Bai:
Deep Submodular Functions. CoRR abs/1701.08939 (2017) - 2016
- [j30]Shengjie Wang, John T. Halloran, Jeff A. Bilmes, William S. Noble:
Faster and more accurate graphical model identification of tandem mass spectra using trellises. Bioinform. 32(12): 322-331 (2016) - [j29]Karen Livescu, Frank Rudzicz, Eric Fosler-Lussier, Mark Hasegawa-Johnson, Jeff A. Bilmes:
Speech Production in Speech Technologies: Introduction to the CSL Special Issue. Comput. Speech Lang. 36: 165-172 (2016) - [c176]Wenruo Bai, Jeffrey A. Bilmes, William S. Noble:
Bipartite matching generalizations for peptide identification in tandem mass spectrometry. BCB 2016: 327-336 - [c175]Thomas Powers, Jeff A. Bilmes, David W. Krout, Les E. Atlas:
Constrained robust submodular sensor selection with applications to multistatic sonar arrays. FUSION 2016: 2179-2185 - [c174]Chandrashekhar Lavania, Sunil Thulasidasan, Anthony LaMarca, Jeffrey Scofield, Jeff A. Bilmes:
A weakly supervised activity recognition framework for real-time synthetic biology laboratory assistance. UbiComp 2016: 37-48 - [c173]Shengjie Wang, Abdel-rahman Mohamed, Rich Caruana, Jeff A. Bilmes, Matthai Philipose, Matthew Richardson, Krzysztof J. Geras, Gregor Urban, Özlem Aslan:
Analysis of Deep Neural Networks with Extended Data Jacobian Matrix. ICML 2016: 718-726 - [c172]Wenruo Bai, Rishabh K. Iyer, Kai Wei, Jeff A. Bilmes:
Algorithms for Optimizing the Ratio of Submodular Functions. ICML 2016: 2751-2759 - [c171]Brian W. Dolhansky, Jeff A. Bilmes:
Deep Submodular Functions: Definitions and Learning. NIPS 2016: 3396-3404 - [i30]Weiran Wang, Raman Arora, Karen Livescu, Jeff A. Bilmes:
On Deep Multi-View Representation Learning: Objectives and Optimization. CoRR abs/1602.01024 (2016) - [i29]Tianyi Zhou, Jeff A. Bilmes:
Stream Clipper: Scalable Submodular Maximization on Stream. CoRR abs/1606.00389 (2016) - [i28]Tianyi Zhou, Hua Ouyang, Yi Chang, Jeff A. Bilmes, Carlos Guestrin:
Scaling Submodular Maximization via Pruned Submodularity Graphs. CoRR abs/1606.00399 (2016) - [i27]Sunil Thulasidasan, Jeffrey A. Bilmes, Garrett T. Kenyon:
Efficient Distributed Semi-Supervised Learning using Stochastic Regularization over Affinity Graphs. CoRR abs/1612.04898 (2016) - [i26]Sunil Thulasidasan, Jeffrey A. Bilmes:
Semi-Supervised Phone Classification using Deep Neural Networks and Stochastic Graph-Based Entropic Regularization. CoRR abs/1612.04899 (2016) - 2015
- [c170]Ramakrishna Bairi, Rishabh K. Iyer, Ganesh Ramakrishnan, Jeff A. Bilmes:
Summarization of Multi-Document Topic Hierarchies using Submodular Mixtures. ACL (1) 2015: 553-563 - [c169]Rishabh K. Iyer, Jeff A. Bilmes:
Submodular Point Processes with Applications to Machine learning. AISTATS 2015 - [c168]Yoshinobu Kawahara, Rishabh K. Iyer, Jeff A. Bilmes:
On Approximate Non-submodular Minimization via Tree-Structured Supermodularity. AISTATS 2015 - [c167]Weiran Wang, Raman Arora, Karen Livescu, Jeff A. Bilmes:
Unsupervised learning of acoustic features via deep canonical correlation analysis. ICASSP 2015: 4590-4594 - [c166]Weiran Wang, Raman Arora, Karen Livescu, Jeff A. Bilmes:
On Deep Multi-View Representation Learning. ICML 2015: 1083-1092 - [c165]Kai Wei, Rishabh K. Iyer, Jeff A. Bilmes:
Submodularity in Data Subset Selection and Active Learning. ICML 2015: 1954-1963 - [c164]Maxwell W. Libbrecht, Michael M. Hoffman, Jeff A. Bilmes, William Stafford Noble:
Entropic Graph-based Posterior Regularization. ICML 2015: 1992-2001 - [c163]Yuzong Liu, Rishabh K. Iyer, Katrin Kirchhoff, Jeff A. Bilmes:
SVitchboard II and fiSVer i: high-quality limited-complexity corpora of conversational English speech. INTERSPEECH 2015: 673-677 - [c162]Kai Wei, Rishabh K. Iyer, Shengjie Wang, Wenruo Bai, Jeff A. Bilmes:
Mixed Robust/Average Submodular Partitioning: Fast Algorithms, Guarantees, and Applications. NIPS 2015: 2233-2241 - [c161]Jennifer Gillenwater, Rishabh K. Iyer, Bethany Lusch, Rahul Kidambi, Jeff A. Bilmes:
Submodular Hamming Metrics. NIPS 2015: 3141-3149 - [i25]Rishabh K. Iyer, Jeff A. Bilmes:
Polyhedral aspects of Submodularity, Convexity and Concavity. CoRR abs/1506.07329 (2015) - [i24]Kai Wei, Rishabh K. Iyer, Shengjie Wang, Wenruo Bai, Jeff A. Bilmes:
Mixed Robust/Average Submodular Partitioning: Fast Algorithms, Guarantees, and Applications to Parallel Machine Learning and Multi-Label Image Segmentation. CoRR abs/1510.08865 (2015) - [i23]Jennifer Gillenwater, Rishabh K. Iyer, Bethany Lusch, Rahul Kidambi, Jeff A. Bilmes:
Submodular Hamming Metrics. CoRR abs/1511.02163 (2015) - 2014
- [c160]Katrin Kirchhoff, Jeff A. Bilmes:
Submodularity for Data Selection in Machine Translation. EMNLP 2014: 131-141 - [c159]Kai Wei, Yuzong Liu, Katrin Kirchhoff, Chris D. Bartels, Jeff A. Bilmes:
Submodular subset selection for large-scale speech training data. ICASSP 2014: 3311-3315 - [c158]Kai Wei, Yuzong Liu, Katrin Kirchhoff, Jeff A. Bilmes:
Unsupervised submodular subset selection for speech data. ICASSP 2014: 4107-4111 - [c157]Kai Wei, Rishabh K. Iyer, Jeff A. Bilmes:
Fast Multi-stage Submodular Maximization. ICML 2014: 1494-1502 - [c156]Jeff A. Bilmes, Krste Asanovic, Chee-Whye Chin, Jim Demmel:
Author retrospective for optimizing matrix multiply using PHiPAC: a portable high-performance ANSI C coding methodology. ICS 25th Anniversary 2014: 42-44 - [c155]Tianyi Zhou, Jeff A. Bilmes, Carlos Guestrin:
Divide-and-Conquer Learning by Anchoring a Conical Hull. NIPS 2014: 1242-1250 - [c154]Sebastian Tschiatschek, Rishabh K. Iyer, Haochen Wei, Jeff A. Bilmes:
Learning Mixtures of Submodular Functions for Image Collection Summarization. NIPS 2014: 1413-1421 - [c153]John T. Halloran, Jeff A. Bilmes, William Stafford Noble:
Learning Peptide-Spectrum Alignment Models for Tandem Mass Spectrometry. UAI 2014: 320-329 - [c152]Rishabh K. Iyer, Stefanie Jegelka, Jeff A. Bilmes:
Monotone Closure of Relaxed Constraints in Submodular Optimization: Connections Between Minimization and Maximization. UAI 2014: 360-369 - [i22]Stefanie Jegelka, Jeff A. Bilmes:
Graph Cuts with Interacting Edge Costs - Examples, Approximations, and Algorithms. CoRR abs/1402.0240 (2014) - [i21]Tianyi Zhou, Jeff A. Bilmes, Carlos Guestrin:
Divide-and-Conquer Learning by Anchoring a Conical Hull. CoRR abs/1406.5752 (2014) - [i20]Rishabh K. Iyer, Jeff A. Bilmes:
Algorithms for Approximate Minimization of the Difference Between Submodular Functions, with Applications. CoRR abs/1408.2051 (2014) - [i19]Rishabh K. Iyer, Jeff A. Bilmes:
The Lovasz-Bregman Divergence and connections to rank aggregation, clustering, and web ranking. CoRR abs/1408.2062 (2014) - 2013
- [c151]Michael M. Hoffman, Orion J. Buske, Jie Wang, Zhiping Weng, Jeff A. Bilmes, William Stafford Noble:
Unsupervised pattern discovery in human chromatin structure through genomic segmentation. BCB 2013: 813 - [c150]Yuzong Liu, Kai Wei, Katrin Kirchhoff, Yisong Song, Jeff A. Bilmes:
Submodular feature selection for high-dimensional acoustic score spaces. ICASSP 2013: 7184-7188 - [c149]Rishabh K. Iyer, Stefanie Jegelka, Jeff A. Bilmes:
Fast Semidifferential-based Submodular Function Optimization. ICML (3) 2013: 855-863 - [c148]Galen Andrew, Raman Arora, Jeff A. Bilmes, Karen Livescu:
Deep Canonical Correlation Analysis. ICML (3) 2013: 1247-1255 - [c147]Katrin Kirchhoff, Yuzong Liu, Jeff A. Bilmes:
Classification of developmental disorders from speech signals using submodular feature selection. INTERSPEECH 2013: 187-190 - [c146]Kai Wei, Yuzong Liu, Katrin Kirchhoff, Jeff A. Bilmes:
Using Document Summarization Techniques for Speech Data Subset Selection. HLT-NAACL 2013: 721-726 - [c145]Rishabh K. Iyer, Jeff A. Bilmes:
Submodular Optimization with Submodular Cover and Submodular Knapsack Constraints. NIPS 2013: 2436-2444 - [c144]Rishabh K. Iyer, Stefanie Jegelka, Jeff A. Bilmes:
Curvature and Optimal Algorithms for Learning and Minimizing Submodular Functions. NIPS 2013: 2742-2750 - [c143]Rishabh K. Iyer, Jeff A. Bilmes:
The Lovasz-Bregman Divergence and connections to rank aggregation, clustering, and web ranking. UAI 2013 - [i18]Jeff A. Bilmes:
Dynamic Bayesian Multinets. CoRR abs/1301.3837 (2013) - [i17]Rishabh K. Iyer, Stefanie Jegelka, Jeff A. Bilmes:
Fast Semidifferential-based Submodular Function Optimization. CoRR abs/1308.1006 (2013) - [i16]Rishabh K. Iyer, Jeff A. Bilmes:
The Lovasz-Bregman Divergence and connections to rank aggregation, clustering, and web ranking. CoRR abs/1308.5275 (2013)