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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) - [i15]Rishabh K. Iyer, Jeff A. Bilmes:
Submodular Optimization with Submodular Cover and Submodular Knapsack Constraints. CoRR abs/1311.2106 (2013) - [i14]Rishabh K. Iyer, Stefanie Jegelka, Jeff A. Bilmes:
Curvature and Optimal Algorithms for Learning and Minimizing Submodular Functions. CoRR abs/1311.2110 (2013) - 2012
- [j28]Alex Stupakov, Evan Hanusa, Deepak Vijaywargi, Dieter Fox, Jeff A. Bilmes:
The design and collection of COSINE, a multi-microphone in situ speech corpus recorded in noisy environments. Comput. Speech Lang. 26(1): 52-66 (2012) - [c142]Tetsuya Takiguchi, Mariko Yoshii, Yasuo Ariki, Jeff A. Bilmes:
Acoustic model transformations based on random projections. ICASSP 2012: 1933-1936 - [c141]Galen Andrew, Jeff A. Bilmes:
Sequential Deep Belief Networks. ICASSP 2012: 4265-4268 - [c140]Rishabh K. Iyer, Jeff A. Bilmes:
Submodular-Bregman and the Lovász-Bregman Divergences with Applications. NIPS 2012: 2942-2950 - [c139]Rishabh K. Iyer, Jeff A. Bilmes:
Algorithms for Approximate Minimization of the Difference Between Submodular Functions, with Applications. UAI 2012: 407-417 - [c138]Hui Lin, Jeff A. Bilmes:
Learning Mixtures of Submodular Shells with Application to Document Summarization. UAI 2012: 479-490 - [c137]Ajit P. Singh, John T. Halloran, Jeff A. Bilmes, Katrin Kirchhoff, William Stafford Noble:
Spectrum Identification using a Dynamic Bayesian Network Model of Tandem Mass Spectra. UAI 2012: 775-785 - [c136]Galen Andrew, Jeff A. Bilmes:
Memory-efficient inference in dynamic graphical models using multiple cores. AISTATS 2012: 47-53 - [c135]Ajit P. Singh, Andrew Guillory, Jeff A. Bilmes:
On Bisubmodular Maximization. AISTATS 2012: 1055-1063 - [i13]Andrew Guillory, Jeff A. Bilmes:
Active Semi-Supervised Learning using Submodular Functions. CoRR abs/1202.3726 (2012) - [i12]Jeff A. Bilmes, Andrew Y. Ng:
Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence (2009). CoRR abs/1206.3959 (2012) - [i11]Marina Meila, Kapil Phadnis, Arthur Patterson, Jeff A. Bilmes:
Consensus ranking under the exponential model. CoRR abs/1206.5265 (2012) - [i10]Chris D. Bartels, Jeff A. Bilmes:
Non-Minimal Triangulations for Mixed Stochastic/Deterministic Graphical Models. CoRR abs/1206.6825 (2012) - [i9]Amarnag Subramanya, Alvin Raj, Jeff A. Bilmes, Dieter Fox:
Recognizing Activities and Spatial Context Using Wearable Sensors. CoRR abs/1206.6869 (2012) - [i8]Rishabh K. Iyer, Jeff A. Bilmes:
Algorithms for Approximate Minimization of the Difference Between Submodular Functions, with Applications. CoRR abs/1207.0560 (2012) - [i7]Mukund Narasimhan, Jeff A. Bilmes:
A submodular-supermodular procedure with applications to discriminative structure learning. CoRR abs/1207.1404 (2012) - [i6]Mukund Narasimhan, Jeff A. Bilmes:
PAC-learning bounded tree-width Graphical Models. CoRR abs/1207.4151 (2012) - [i5]Hui Lin, Jeff A. Bilmes:
Learning Mixtures of Submodular Shells with Application to Document Summarization. CoRR abs/1210.4871 (2012) - [i4]Ajit P. Singh, John T. Halloran, Jeff A. Bilmes, Katrin Kirchhoff, William Stafford Noble:
Spectrum Identification using a Dynamic Bayesian Network Model of Tandem Mass Spectra. CoRR abs/1210.4904 (2012) - [i3]Jeff A. Bilmes, Chris D. Bartels:
On Triangulating Dynamic Graphical Models. CoRR abs/1212.2448 (2012) - 2011
- [j27]Zafer Aydin, Ajit P. Singh, Jeff A. Bilmes, William Stafford Noble:
Learning sparse models for a dynamic Bayesian network classifier of protein secondary structure. BMC Bioinform. 12: 154 (2011) - [j26]Jonathan Malkin, Xiao Li, Susumu Harada, James A. Landay, Jeff A. Bilmes:
The Vocal Joystick Engine v1.0. Comput. Speech Lang. 25(3): 535-555 (2011) - [j25]Amarnag Subramanya, Jeff A. Bilmes:
Semi-Supervised Learning with Measure Propagation. J. Mach. Learn. Res. 12: 3311-3370 (2011) - [j24]Chris D. Bartels, Jeff A. Bilmes:
Creating non-minimal triangulations for use in inference in mixed stochastic/deterministic graphical models. Mach. Learn. 84(3): 249-289 (2011) - [j23]Danny Wyatt, Tanzeem Choudhury, Jeff A. Bilmes, James A. Kitts:
Inferring colocation and conversation networks from privacy-sensitive audio with implications for computational social science. ACM Trans. Intell. Syst. Technol. 2(1): 7:1-7:41 (2011) - [c134]Hui Lin, Jeff A. Bilmes:
Word Alignment via Submodular Maximization over Matroids. ACL (2) 2011: 170-175 - [c133]Hui Lin, Jeff A. Bilmes:
A Class of Submodular Functions for Document Summarization. ACL 2011: 510-520 - [c132]Stefanie Jegelka, Jeff A. Bilmes:
Submodularity beyond submodular energies: Coupling edges in graph cuts. CVPR 2011: 1897-1904 - [c131]Stefanie Jegelka, Jeff A. Bilmes:
Online Submodular Minimization for Combinatorial Structures. ICML 2011: 345-352 - [c130]Andrew Guillory, Jeff A. Bilmes:
Simultaneous Learning and Covering with Adversarial Noise. ICML 2011: 369-376 - [c129]Stefanie Jegelka, Jeff A. Bilmes:
Approximation Bounds for Inference using Cooperative Cuts. ICML 2011: 577-584 - [c128]Hui Lin, Jeff A. Bilmes:
Optimal Selection of Limited Vocabulary Speech Corpora. INTERSPEECH 2011: 1489-1492 - [c127]Jeff A. Bilmes, Hui Lin, Andrew Guillory:
Applications of submodular functions in speech and NLP. MLSLP 2011 - [c126]Stefanie Jegelka, Hui Lin, Jeff A. Bilmes:
On fast approximate submodular minimization. NIPS 2011: 460-468 - [c125]Andrew Guillory, Jeff A. Bilmes:
Online Submodular Set Cover, Ranking, and Repeated Active Learning. NIPS 2011: 1107-1115 - [c124]Andrew Guillory, Jeff A. Bilmes:
Active Semi-Supervised Learning using Submodular Functions. UAI 2011: 274-282 - 2010
- [j22]Mausam, Stephen Soderland, Oren Etzioni, Daniel S. Weld, Kobi Reiter, Michael Skinner, Marcus Sammer, Jeff A. Bilmes:
Panlingual lexical translation via probabilistic inference. Artif. Intell. 174(9-10): 619-637 (2010) - [j21]Xiaoyu Chen, Michael M. Hoffman, Jeff A. Bilmes, Jay R. Hesselberth, William Stafford Noble:
A dynamic Bayesian network for identifying protein-binding footprints from single molecule-based sequencing data. Bioinform. 26(12): 334-342 (2010) - [j20]Chris D. Bartels, Jeff A. Bilmes:
Graphical models for integrating syllabic information. Comput. Speech Lang. 24(4): 685-697 (2010) - [j19]Franz Pernkopf, Jeff A. Bilmes:
Efficient Heuristics for Discriminative Structure Learning of Bayesian Network Classifiers. J. Mach. Learn. Res. 11: 2323-2360 (2010) - [j18]Sheila M. Reynolds, Jeff A. Bilmes, William Stafford Noble:
Learning a Weighted Sequence Model of the Nucleosome Core and Linker Yields More Accurate Predictions in Saccharomyces cerevisiae and Homo sapiens. PLoS Comput. Biol. 6(7) (2010) - [j17]Jeff A. Bilmes:
Dynamic Graphical Models. IEEE Signal Process. Mag. 27(6): 29-42 (2010) - [c123]Danny Wyatt, Tanzeem Choudhury, Jeff A. Bilmes:
Discovering Long Range Properties of Social Networks with Multi-Valued Time-Inhomogeneous Models. AAAI 2010: 630-636 - [c122]Tetsuya Takiguchi, Jeff A. Bilmes, Mariko Yoshii, Yasuo Ariki:
Evaluation of random-projection-based feature combination on speech recognition. ICASSP 2010: 2150-2153 - [c121]Gang Ji, Jeff A. Bilmes:
Jointly recognizing multi-speaker conversations. ICASSP 2010: 5110-5113 - [c120]Andrew Guillory, Jeff A. Bilmes:
Interactive Submodular Set Cover. ICML 2010: 415-422 - [c119]Jeff A. Bilmes, Hui Lin:
Online adaptive learning for speech recognition decoding. INTERSPEECH 2010: 1958-1961 - [c118]Jonathan Malkin, Jeff A. Bilmes:
Semi-supervised learning for improved expression of uncertainty in discriminative classifiers. INTERSPEECH 2010: 2990-2993 - [c117]Hui Lin, Jeff A. Bilmes:
Multi-document Summarization via Budgeted Maximization of Submodular Functions. HLT-NAACL 2010: 912-920 - [c116]Sheila M. Reynolds, Zhiping Weng, Jeff A. Bilmes, William Stafford Noble:
Predicting Nucleosome Positioning Using Multiple Evidence Tracks. RECOMB 2010: 441-455 - [i2]Andrew Guillory, Jeff A. Bilmes:
Interactive Submodular Set Cover. CoRR abs/1002.3345 (2010)
2000 – 2009
- 2009
- [j16]Franz Pernkopf, Tuan Van Pham, Jeff A. Bilmes:
Broad phonetic classification using discriminative Bayesian networks. Speech Commun. 51(2): 151-166 (2009) - [c115]Mausam, Stephen Soderland, Oren Etzioni, Daniel S. Weld, Michael Skinner, Jeff A. Bilmes:
Compiling a Massive, Multilingual Dictionary via Probabilistic Inference. ACL/IJCNLP 2009: 262-270 - [c114]Andrew Guillory, Jeff A. Bilmes:
Average-Case Active Learning with Costs. ALT 2009: 141-155 - [c113]Hui Lin, Jeff A. Bilmes, Shasha Xie:
Graph-based submodular selection for extractive summarization. ASRU 2009: 381-386 - [c112]Brandi House, Jonathan Malkin, Jeff A. Bilmes:
The VoiceBot: a voice controlled robot arm. CHI 2009: 183-192 - [c111]Susumu Harada, Jacob O. Wobbrock, Jonathan Malkin, Jeff A. Bilmes, James A. Landay:
Longitudinal study of people learning to use continuous voice-based cursor control. CHI 2009: 347-356 - [c110]Alex Stupakov, Evan Hanusa, Jeff A. Bilmes, Dieter Fox:
COSINE - A corpus of multi-party COnversational Speech In Noisy Environments. ICASSP 2009: 4153-4156 - [c109]Jonathan Malkin, Jeff A. Bilmes:
Multi-layer ratio Semi-Definite Classifiers. ICASSP 2009: 4465-4468 - [c108]Ning Ma, Chris D. Bartels, Jeff A. Bilmes, Phil D. Green:
Modelling the prepausal lengthening effect for speech recognition: a dynamic Bayesian network approach. ICASSP 2009: 4617-4620 - [c107]Hui Lin, Alex Stupakov, Jeff A. Bilmes:
Improving multi-lattice alignment based spoken keyword spotting. ICASSP 2009: 4877-4880 - [c106]Jonathan Malkin, Amarnag Subramanya, Jeff A. Bilmes:
On the semi-supervised learning of multi-layered perceptrons. INTERSPEECH 2009: 660-663 - [c105]Amarnag Subramanya, Jeff A. Bilmes:
The semi-supervised switchboard transcription project. INTERSPEECH 2009: 1915-1918 - [c104]Hui Lin, Jeff A. Bilmes, Koby Crammer:
How to loose confidence: probabilistic linear machines for multiclass classification. INTERSPEECH 2009: 2559-2562 - [c103]Hui Lin, Jeff A. Bilmes:
How to select a good training-data subset for transcription: submodular active selection for sequences. INTERSPEECH 2009: 2859-2862 - [c102]Andrew Guillory, Jeff A. Bilmes:
Label Selection on Graphs. NIPS 2009: 691-699 - [c101]Yoshinobu Kawahara, Kiyohito Nagano, Koji Tsuda, Jeff A. Bilmes:
Submodularity Cuts and Applications. NIPS 2009: 916-924 - [c100]Amarnag Subramanya, Jeff A. Bilmes:
Entropic Graph Regularization in Non-Parametric Semi-Supervised Classification. NIPS 2009: 1803-1811 - [c99]Sheila M. Reynolds, Jeff A. Bilmes, William Stafford Noble:
On the Relationship between DNA Periodicity and Local Chromatin Structure. RECOMB 2009: 434-450 - [c98]Andrew Guillory, Erick Chastain, Jeff A. Bilmes:
Active Learning as Non-Convex Optimization. AISTATS 2009: 201-208 - [e2]Jeff A. Bilmes, Andrew Y. Ng:
UAI 2009, Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence, Montreal, QC, Canada, June 18-21, 2009. AUAI Press 2009 [contents] - [i1]Andrew Guillory, Jeff A. Bilmes:
Average-Case Active Learning with Costs. CoRR abs/0905.2997 (2009) - 2008
- [j15]Sheila M. Reynolds, Lukas Käll, Michael Riffle, Jeff A. Bilmes, William Stafford Noble:
Transmembrane Topology and Signal Peptide Prediction Using Dynamic Bayesian Networks. PLoS Comput. Biol. 4(11) (2008) - [c97]Danny Wyatt, Tanzeem Choudhury, Jeff A. Bilmes:
Learning Hidden Curved Exponential Family Models to Infer Face-to-Face Interaction Networks from Situated Speech Data. AAAI 2008: 732-738 - [c96]William Pentney, Matthai Philipose, Jeff A. Bilmes:
Structure Learning on Large Scale Common Sense Statistical Models of Human State. AAAI 2008: 1389-1395 - [c95]Amarnag Subramanya, Jeff A. Bilmes:
Soft-Supervised Learning for Text Classification. EMNLP 2008: 1090-1099 - [c94]Danny Wyatt, Jeff A. Bilmes, Tanzeem Choudhury, James A. Kitts:
Towards the automated social analysis of situated speech data. UbiComp 2008: 168-171 - [c93]Hui Lin, Jeff A. Bilmes:
Polyphase speech recognition. ICASSP 2008: 4109-4112 - [c92]Jonathan Malkin, Jeff A. Bilmes:
Ratio semi-definite classifiers. ICASSP 2008: 4113-4116 - [c91]Hui Lin, Alex Stupakov, Jeff A. Bilmes:
Spoken keyword spotting via multi-lattice alignment. INTERSPEECH 2008: 2191-2194 - [c90]Chris D. Bartels, Jeff A. Bilmes:
Using syllable nuclei locations to improve automatic speech recognition in the presence of burst noise. INTERSPEECH 2008: 2406-2409 - [c89]Amarnag Subramanya, Jeff A. Bilmes:
Applications of virtual-evidence based speech recognizer training. INTERSPEECH 2008: 2562-2565 - [c88]Andrew Guillory, Jeff A. Bilmes:
Practical Methods for Exploiting Bounds on Change in the Margin. ISAIM 2008 - [c87]Franz Pernkopf, Jeff A. Bilmes:
Order-based Discriminative Structure Learning for Bayesian Network Classifiers. ISAIM 2008 - [c86]Aaron A. Klammer, Sheila M. Reynolds, Jeff A. Bilmes, Michael J. MacCoss, William Stafford Noble:
Modeling peptide fragmentation with dynamic Bayesian networks for peptide identification. ISMB 2008: 348-356 - 2007
- [j14]Chia-Ping Chen, Jeff A. Bilmes:
MVA Processing of Speech Features. IEEE Trans. Speech Audio Process. 15(1): 257-270 (2007) - [c85]William Pentney, Matthai Philipose, Jeff A. Bilmes, Henry A. Kautz:
Learning Large Scale Common Sense Models of Everyday Life. AAAI 2007: 465-470 - [c84]Jeff A. Bilmes:
Submodularity and adaptation. ASRU 2007: 249 - [c83]Chris D. Bartels, Jeff A. Bilmes:
Use of syllable nuclei locations to improve ASR. ASRU 2007: 335-340 - [c82]Hui Lin, Jeff A. Bilmes, Dimitra Vergyri, Katrin Kirchhoff:
OOV detection by joint word/phone lattice alignment. ASRU 2007: 478-483 - [c81]Amarnag Subramanya, Chris D. Bartels, Jeff A. Bilmes, Patrick Nguyen:
Uncertainty in training large vocabulary speech recognizers. ASRU 2007: 484-489 - [c80]Brandi House, Jonathan Malkin, Jeff A. Bilmes:
Demo of VJ-Voicebot: control of robotic arm with the Vocal Joystick. ASSETS 2007: 247-248 - [c79]Katherine Everitt, Susumu Harada, Jeff A. Bilmes, James A. Landay:
Disambiguating speech commands using physical context. ICMI 2007: 247-254 - [c78]Mukund Narasimhan, Jeff A. Bilmes:
Local Search for Balanced Submodular Clusterings. IJCAI 2007: 981-986 - [c77]Danny Wyatt, Tanzeem Choudhury, Jeff A. Bilmes, Henry A. Kautz:
A Privacy-Sensitive Approach to Modeling Multi-Person Conversations. IJCAI 2007: 1769-1775 - [c76]Danny Wyatt, Tanzeem Choudhury, Jeff A. Bilmes:
Conversation detection and speaker segmentation in privacy-sensitive situated speech data. INTERSPEECH 2007: 586-589 - [c75]Raghunandan Kumaran, Jeff A. Bilmes, Katrin Kirchhoff:
Attention shift decoding for conversational speech recognition. INTERSPEECH 2007: 1493-1496 - [c74]Karim Filali, Jeff A. Bilmes:
Generalized Graphical Abstractions for Statistical Machine Translation. HLT-NAACL (Short Papers) 2007: 33-36 - [c73]Amarnag Subramanya, Jeff A. Bilmes:
Virtual Evidence for Training Speech Recognizers Using Partially Labeled Data. HLT-NAACL (Short Papers) 2007: 165-168 - [c72]Marina Meila, Kapil Phadnis, Arthur Patterson, Jeff A. Bilmes:
Consensus ranking under the exponential model. UAI 2007: 285-294 - [c71]Xiao Li, Jeff A. Bilmes:
A Bayesian Divergence Prior for Classiffier Adaptation. AISTATS 2007: 275-282 - 2006
- [j13]Katrin Kirchhoff, Dimitra Vergyri, Jeff A. Bilmes, Kevin Duh, Andreas Stolcke:
Morphology-based language modeling for conversational Arabic speech recognition. Comput. Speech Lang. 20(4): 589-608 (2006) - [j12]Karim Filali, Xiao Li, Jeff A. Bilmes:
Algorithms for data-driven ASR parameter quantization. Comput. Speech Lang. 20(4): 625-643 (2006) - [j11]Jeff A. Bilmes:
What HMMs Can Do. IEICE Trans. Inf. Syst. 89-D(3): 869-891 (2006) - [j10]Xiao Li, Jonathan Malkin, Jeff A. Bilmes:
A high-speed, low-resource ASR back-end based on custom arithmetic. IEEE Trans. Speech Audio Process. 14(5): 1683-1693 (2006) - [c70]Susumu Harada, James A. Landay, Jonathan Malkin, Xiao Li, Jeff A. Bilmes:
The vocal joystick: : evaluation of voice-based cursor control techniques. ASSETS 2006: 197-204 - [c69]Xiao Li, Jeff A. Bilmes:
Regularized Adaptation of Discriminative Classifiers. ICASSP (1) 2006: 237-240 - [c68]Jeff A. Bilmes, Jonathan Malkin, Xiao Li, Susumu Harada, Kelley Kilanski, Katrin Kirchhoff, Richard Wright, Amarnag Subramanya, James A. Landay, Patricia Dowden, Howard Chizeck:
The Vocal Joystick. ICASSP (1) 2006: 625-628 - [c67]Xiao Li, Gang Ji, Jeff A. Bilmes:
A Factored Language Model of Quantized Pitch and Duration. ICMC 2006 - [c66]Kelley Kilanski, Jonathan Malkin, Xiao Li, Richard Wright, Jeff A. Bilmes:
The vocal joystick data collection effort and vowel corpus. INTERSPEECH 2006 - [c65]Xiao Li, Jonathan Malkin, Susumu Harada, Jeff A. Bilmes, Richard Wright, James A. Landay:
An online adaptive filtering algorithm for the vocal joystick. INTERSPEECH 2006 - [c64]Alvin Raj, Amarnag Subramanya, Dieter Fox, Jeff A. Bilmes:
Rao-Blackwellized Particle Filters for Recognizing Activities and Spatial Context from Wearable Sensors. ISER 2006: 211-221 - [c63]Amarnag Subramanya, Alvin Raj, Jeff A. Bilmes, Dieter Fox:
Hierarchical Models for Activity Recognition. MMSP 2006: 233-237 - [c62]Gang Ji, Jeff A. Bilmes:
Backoff Model Training using Partially Observed Data: Application to Dialog Act Tagging. HLT-NAACL 2006 - [c61]Karim Filali, Jeff A. Bilmes:
Multi-dynamic Bayesian Networks. NIPS 2006: 409-416 - [c60]Gang Ji, Jeff A. Bilmes, Jeff Michels, Katrin Kirchhoff, Christopher D. Manning:
Graphical Model Representations of Word Lattices. SLT 2006: 162-165 - [c59]Chris D. Bartels, Jeff A. Bilmes:
Non-Minimal Triangulations for Mixed Stochastic/Deterministic Graphical Models. UAI 2006 - [c58]Amar Subramanya, Alvin Raj, Jeff A. Bilmes, Dieter Fox:
Recognizing Activities and Spatial Context Using Wearable Sensors. UAI 2006 - [e1]Robert C. Moore, Jeff A. Bilmes, Jennifer Chu-Carroll, Mark Sanderson:
Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics, Proceedings, June 4-9, 2006, New York, New York, USA. The Association for Computational Linguistics 2006 [contents] - 2005
- [j9]Xiao Li, Jeff A. Bilmes:
Feature pruning for low-power ASR systems in clean and noisy environments. IEEE Signal Process. Lett. 12(7): 489-492 (2005) - [j8]Jeff A. Bilmes, Chris D. Bartels:
Graphical model architectures for speech recognition. IEEE Signal Process. Mag. 22(5): 89-100 (2005) - [c57]Karim Filali, Jeff A. Bilmes:
A Dynamic Bayesian Framework to Model Context and Memory in Edit Distance Learning: An Application to Pronunciation Classification. ACL 2005: 338-345 - [c56]Gang Ji, Jeff A. Bilmes:
Dialog Act Tagging Using Graphical Models. ICASSP (1) 2005: 33-36 - [c55]Xin Lei, Gang Ji, Tim Ng, Jeff A. Bilmes, Mari Ostendorf:
DBN-Based Multi-stream Models for Mandarin Toneme Recognition. ICASSP (1) 2005: 349-352 - [c54]Chia-Ping Chen, Jeff A. Bilmes, Daniel P. W. Ellis:
Speech Feature Smoothing for Robust ASR. ICASSP (1) 2005: 525-528 - [c53]Jonathan Malkin, Xiao Li, Jeff A. Bilmes:
A Graphical Model for Formant Tracking. ICASSP (1) 2005: 913-916 - [c52]Yi Li, Linda G. Shapiro, Jeff A. Bilmes:
A Generative/Discriminative Learning Algorithm for Image Classification. ICCV 2005: 1605-1612 - [c51]Franz Pernkopf, Jeff A. Bilmes:
Discriminative versus generative parameter and structure learning of Bayesian network classifiers. ICML 2005: 657-664 - [c50]Amarnag Subramanya, Jeff A. Bilmes, Chia-Ping Chen:
Focused word segmentation for ASR. INTERSPEECH 2005: 393-396 - [c49]Xiao Li, Jeff A. Bilmes, Jonathan Malkin:
Maximum margin learning and adaptation of MLP classifiers. INTERSPEECH 2005: 1789-1792 - [c48]Chris D. Bartels, Kevin Duh, Jeff A. Bilmes, Katrin Kirchhoff, Simon King:
Genetic triangulation of graphical models for speech and language processing. INTERSPEECH 2005: 3329-3332 - [c47]Simon King, Chris D. Bartels, Jeff A. Bilmes:
SVitchboard 1: small vocabulary tasks from Switchboard. INTERSPEECH 2005: 3385-3388 - [c46]Sheila M. Reynolds, Jeff A. Bilmes:
Part-of-Speech Tagging using Virtual Evidence and Negative Training. HLT/EMNLP 2005: 459-466 - [c45]Jeff A. Bilmes, Xiao Li, Jonathan Malkin, Kelley Kilanski, Richard Wright, Katrin Kirchhoff, Amar Subramanya, Susumu Harada, James A. Landay, Patricia Dowden, Howard Chizeck:
The Vocal Joystick: A Voice-Based Human-Computer Interface for Individuals with Motor Impairments. HLT/EMNLP 2005: 995-1002 - [c44]Mukund Narasimhan, Nebojsa Jojic, Jeff A. Bilmes:
Q-Clustering. NIPS 2005: 979-986 - [c43]Mukund Narasimhan, Jeff A. Bilmes:
A Submodular-supermodular Procedure with Applications to Discriminative Structure Learning. UAI 2005: 404-412 - 2004
- [j7]Richard W. Vuduc, James Demmel, Jeff A. Bilmes:
Statistical Models for Empirical Search-Based Performance Tuning. Int. J. High Perform. Comput. Appl. 18(1): 65-94 (2004) - [c42]Jonathan Malkin, Xiao Li, Jeff A. Bilmes:
Custom arithmetic for high-speed, low-resource ASR systems. ICASSP (5) 2004: 305-308 - [c41]Xiao Li, Jonathan Malkin, Jeff A. Bilmes:
Codebook design for ASR systems using custom arithmetic units. ICASSP (1) 2004: 845-848 - [c40]John N. Gowdy, Amarnag Subramanya, Chris D. Bartels, Jeff A. Bilmes:
DBN based multi-stream models for audio-visual speech recognition. ICASSP (1) 2004: 993-996 - [c39]Yi Li, Jeff A. Bilmes, Linda G. Shapiro:
Object Class Recognition using Images of Abstract Regions. ICPR (1) 2004: 40-43 - [c38]Xiao Li, Jonathan Malkin, Jeff A. Bilmes:
Graphical model approach to pitch tracking. INTERSPEECH 2004: 1101-1104 - [c37]Gang Ji, Jeff A. Bilmes:
Multi-Speaker Language Modeling. HLT-NAACL (Short Papers) 2004 - [c36]Mukund Narasimhan, Jeff A. Bilmes:
Optimal sub-graphical models. NIPS 2004: 961-968 - [c35]Mukund Narasimhan, Jeff A. Bilmes:
PAC-learning Bounded Tree-width Graphical Models. UAI 2004: 410-417 - 2003
- [j6]Martin J. Russell, Jeff A. Bilmes:
Introduction to the special issue on new computational paradigms for acoustic modeling in speech recognition. Comput. Speech Lang. 17(2-3): 107-112 (2003) - [j5]Jeff A. Bilmes:
Buried Markov models: a graphical-modeling approach to automatic speech recognition. Comput. Speech Lang. 17(2-3): 213-231 (2003) - [j4]Jeff A. Bilmes, Katrin Kirchhoff:
Generalized rules for combination and joint training of classifiers. Pattern Anal. Appl. 6(3): 201-211 (2003) - [j3]Matthew Richardson, Jeff A. Bilmes, Chris Diorio:
Hidden-articulator Markov models for speech recognition. Speech Commun. 41(2-3): 511-529 (2003) - [c34]Katrin Kirchhoff, Jeff A. Bilmes, Sourin Das, Nicolae Duta, Melissa Egan, Gang Ji, Feng He, John Henderson, Daben Liu, Mohammed Noamany, Patrick Schone, Richard M. Schwartz, Dimitra Vergyri:
Novel approaches to Arabic speech recognition: report from the 2002 Johns-Hopkins Summer Workshop. ICASSP (1) 2003: 344-347 - [c33]Yimin Zhang, Qian Diao, Shan Huang, Wei Hu, Chris D. Bartels, Jeff A. Bilmes:
DBN based multi-stream models for speech. ICASSP (1) 2003: 836-839 - [c32]Karen Livescu, James R. Glass, Jeff A. Bilmes:
Hidden feature models for speech recognition using dynamic Bayesian networks. INTERSPEECH 2003: 2529-2532 - [c31]Jeff A. Bilmes, Katrin Kirchhoff:
Factored Language Models and Generalized Parallel Backoff. HLT-NAACL 2003 - [c30]Gang Ji, Jeff A. Bilmes:
Necessary Intransitive Likelihood-Ratio Classifiers. NIPS 2003: 537-544 - [c29]Jeff A. Bilmes, Chris D. Bartels:
On Triangulating Dynamic Graphical Models. UAI 2003: 47-56 - 2002
- [c28]Geoffrey Zweig, Jeff A. Bilmes, Thomas Richardson, Karim Filali, Karen Livescu, Peng Xu, Kirk Jackson, Yigal Brandman, Eric D. Sandness, Eva Holtz, Jerry Torres, Bill Byrne:
Structurally discriminative graphical models for automatic speech recognition - results from the 2001 Johns Hopkins Summer Workshop. ICASSP 2002: 93-96 - [c27]Ivan Bulyko, Mari Ostendorf, Jeff A. Bilmes:
Robust splicing costs and efficient search with BMM Models for concatenative speech synthesis. ICASSP 2002: 461-464 - [c26]Katrin Kirchhoff, Sonia Parandekar, Jeff A. Bilmes:
Mixed-memory Markov models for Automatic Language Identification. ICASSP 2002: 761-764 - [c25]Jeff A. Bilmes, Geoffrey Zweig:
The graphical models toolkit: An open source software system for speech and time-series processing. ICASSP 2002: 3916-3919 - [c24]Chia-Ping Chen, Karim Filali, Jeff A. Bilmes:
Frontend post-processing and backend model enhancement on the Aurora 2.0/3.0 databases. INTERSPEECH 2002: 241-244 - [c23]Özgür Çetin, Harriet J. Nock, Katrin Kirchhoff, Jeff A. Bilmes, Mari Ostendorf:
The 2001 GMTK-based SPINE ASR system. INTERSPEECH 2002: 1037-1040 - [c22]Karim Filali, Xiao Li, Jeff A. Bilmes:
Data-driven vector clustering for low-memory footprint ASR. INTERSPEECH 2002: 1601-1604 - [c21]Chia-Ping Chen, Jeff A. Bilmes, Katrin Kirchhoff:
Low-resource noise-robust feature post-processing on Aurora 2.0. INTERSPEECH 2002: 2445-2448 - 2001
- [c20]Rich Vuduc, James Demmel, Jeff A. Bilmes:
Statistical Models for Automatic Performance Tuning. International Conference on Computational Science (1) 2001: 117-126 - [c19]Jeff A. Bilmes, Gang Ji, Marina Meila:
Intransitive Likelihood-Ratio Classifiers. NIPS 2001: 1141-1148 - 2000
- [c18]Jeff A. Bilmes:
Factored sparse inverse covariance matrices. ICASSP 2000: 1009-1012 - [c17]Daniel P. W. Ellis, Jeff A. Bilmes:
Using mutual information to design feature combinations. INTERSPEECH 2000: 79-82 - [c16]Matthew Richardson, Jeff A. Bilmes, Chris Diorio:
Hidden-articulator Markov models: performance improvements and robustness to noise. INTERSPEECH 2000: 131-134 - [c15]Jeff A. Bilmes, Katrin Kirchhoff:
Directed graphical models of classifier combination: application to phone recognition. INTERSPEECH 2000: 921 - [c14]Jeff A. Bilmes:
Dynamic Bayesian Multinets. UAI 2000: 38-45
1990 – 1999
- 1999
- [c13]Katrin Kirchhoff, Jeff A. Bilmes:
Dynamic classifier combination in hybrid speech recognition systems using utterance-level confidence values. ICASSP 1999: 693-696 - [c12]Jeff A. Bilmes:
Buried Markov models for speech recognition. ICASSP 1999: 713-716 - 1998
- [c11]Jeff A. Bilmes:
Maximum mutual information based reduction strategies for cross-correlation based joint distributional modeling. ICASSP 1998: 469-472 - [c10]Jeff A. Bilmes:
Data-driven extensions to HMM statistical dependencies. ICSLP 1998 - 1997
- [c9]Jeff A. Bilmes, Krste Asanovic, Chee-Whye Chin, James Demmel:
Using PHiPAC to speed error back-propagation learning. ICASSP 1997: 4153-4156 - [c8]Jeff A. Bilmes, Krste Asanovic, Chee-Whye Chin, James Demmel:
Optimizing Matrix Multiply Using PHiPAC: A Portable, High-Performance, ANSI C Coding Methodology. International Conference on Supercomputing 1997: 340-347 - 1996
- [c7]Jeff A. Bilmes, Nelson Morgan, Su-Lin Wu, Hervé Bourlard:
Stochastic perceptual speech models with durational dependence. ICSLP 1996: 1301-1304 - 1993
- [c6]Jeff A. Bilmes:
Techniques to Foster Drum Machine Expressivity. ICMC 1993 - 1992
- [j2]Nelson Morgan, James Beck, Phil Kohn, Jeff A. Bilmes, Eric Allman, Joachim Beer:
The Ring Array Processor: A Multiprocessing Peripheral for Connection Applications. J. Parallel Distributed Comput. 14(3): 248-259 (1992) - [c5]Jeff A. Bilmes:
A Model for Musical Rhythm. ICMC 1992 - 1991
- [j1]Oliver Günther, Jeff A. Bilmes:
Tree-Based Access Methods for Spatial Databases: Implementation and Performance Evaluation. IEEE Trans. Knowl. Data Eng. 3(3): 342-356 (1991) - [c4]David P. Anderson, Jeff A. Bilmes:
Concurrent Real-Time Music in C++. C++ Conference 1991: 147-162 - [c3]Phil Kohn, Jeff A. Bilmes, Nelson Morgan, James Beck:
Software for ANN Training on a Ring Array Processor. NIPS 1991: 781-788 - 1990
- [c2]Nelson Morgan, James Beck, Phil Kohn, Jeffrey A. Bilmes, Eric Allman, Joachim Beer:
The RAP: a ring array processor for layered network calculations. ASAP 1990: 296-308
1980 – 1989
- 1989
- [c1]Oliver Günther, Jeff A. Bilmes:
The Implementation of the Cell Tree: Design Alternatives and Performance Evaluation. BTW 1989: 246-265
Coauthor Index
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