Jeff A. Bilmes

Jeff A. Bilmes: Dynamic Bayesian Multinets. CoRR abs/1301.3837 (2013)

Alex Stupakov, Evan Hanusa, Deepak Vijaywargi, Dieter Fox, Jeff Bilmes: The design and collection of COSINE, a multi-microphone in situ speech corpus recorded in noisy environments. Computer Speech & Language 26(1): 52-66 (2012)

Galen Andrew, Jeff Bilmes: Memory-efficient inference in dynamic graphical models using multiple cores. Journal of Machine Learning Research - Proceedings Track 22: 47-53 (2012)

Ajit P. Singh, Andrew Guillory, Jeff Bilmes: On Bisubmodular Maximization. Journal of Machine Learning Research - Proceedings Track 22: 1055-1063 (2012)

Tetsuya Takiguchi, Mariko Yoshii, Yasuo Ariki, Jeff Bilmes: Acoustic model transformations based on random projections. ICASSP 2012: 1933-1936

Galen Andrew, Jeff A. Bilmes: Sequential Deep Belief Networks. ICASSP 2012: 4265-4268

Rishabh Iyer, Jeff A. Bilmes: Submodular-Bregman and the Lova _sz-Bregman Divergences with Applications. NIPS 2012: 2942-2950

Rishabh Iyer, Jeff Bilmes: Algorithms for Approximate Minimization of the Difference Between Submodular Functions, with Applications. UAI 2012: 407-417

Hui Lin, Jeff Bilmes: Learning Mixtures of Submodular Shells with Application to Document Summarization. UAI 2012: 479-490

Ajit P. Singh, John Halloran, Jeff Bilmes, Katrin Kirchhoff, William Stafford Noble: Spectrum Identification using a Dynamic Bayesian Network Model of Tandem Mass Spectra. UAI 2012: 775-785

Andrew Guillory, Jeff A. Bilmes: Active Semi-Supervised Learning using Submodular Functions. CoRR abs/1202.3726 (2012)

Jeff Bilmes, Andrew Y. Ng: Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence (2009). CoRR abs/1206.3959 (2012)

Marina Meila, Kapil Phadnis, Arthur Patterson, Jeff A. Bilmes: Consensus ranking under the exponential model. CoRR abs/1206.5265 (2012)

Rishabh Iyer, Jeff Bilmes: Algorithms for Approximate Minimization of the Difference Between Submodular Functions, with Applications. CoRR abs/1207.0560 (2012)

Mukund Narasimhan, Jeff A. Bilmes: A submodular-supermodular procedure with applications to discriminative structure learning. CoRR abs/1207.1404 (2012)

Mukund Narasimhan, Jeff A. Bilmes: PAC-learning bounded tree-width Graphical Models. CoRR abs/1207.4151 (2012)

Hui Lin, Jeff A. Bilmes: Learning Mixtures of Submodular Shells with Application to Document Summarization. CoRR abs/1210.4871 (2012)

Ajit P. Singh, John 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)

Jeff A. Bilmes, Chris D. Bartels: On Triangulating Dynamic Graphical Models. CoRR abs/1212.2448 (2012)

Zafer Aydin, Ajit P. Singh, Jeff Bilmes, William Stafford Noble: Learning sparse models for a dynamic Bayesian network classifier of protein secondary structure. BMC Bioinformatics 12: 154 (2011)

Jonathan Malkin, Xiao Li, Susumu Harada, James A. Landay, Jeff Bilmes: The Vocal Joystick Engine v1.0. Computer Speech & Language 25(3): 535-555 (2011)

Amarnag Subramanya, Jeff Bilmes: Semi-Supervised Learning with Measure Propagation. Journal of Machine Learning Research 12: 3311-3370 (2011)

Chris D. Bartels, Jeff A. Bilmes: Creating non-minimal triangulations for use in inference in mixed stochastic/deterministic graphical models. Machine Learning 84(3): 249-289 (2011)

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 TIST 2(1): 7 (2011)

Hui Lin, Jeff Bilmes: Word Alignment via Submodular Maximization over Matroids. ACL (Short Papers) 2011: 170-175

Hui Lin, Jeff Bilmes: A Class of Submodular Functions for Document Summarization. ACL 2011: 510-520

Stefanie Jegelka, Jeff Bilmes: Submodularity beyond submodular energies: Coupling edges in graph cuts. CVPR 2011: 1897-1904

Stefanie Jegelka, Jeff Bilmes: Online Submodular Minimization for Combinatorial Structures. ICML 2011: 345-352

Andrew Guillory, Jeff Bilmes: Simultaneous Learning and Covering with Adversarial Noise. ICML 2011: 369-376

Stefanie Jegelka, Jeff Bilmes: Approximation Bounds for Inference using Cooperative Cuts. ICML 2011: 577-584

Hui Lin, Jeff A. Bilmes: Optimal Selection of Limited Vocabulary Speech Corpora. INTERSPEECH 2011: 1489-1492

Stefanie Jegelka, Hui Lin, Jeff A. Bilmes: On fast approximate submodular minimization. NIPS 2011: 460-468

Andrew Guillory, Jeff A. Bilmes: Online Submodular Set Cover, Ranking, and Repeated Active Learning. NIPS 2011: 1107-1115

Andrew Guillory, Jeff Bilmes: Active Semi-Supervised Learning using Submodular Functions. UAI 2011: 274-282

Mausam, Stephen Soderland, Oren Etzioni, Daniel S. Weld, Kobi Reiter, Michael Skinner, Marcus Sammer, Jeff Bilmes: Panlingual lexical translation via probabilistic inference. Artif. Intell. 174(9-10): 619-637 (2010)

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. Bioinformatics [ISMB] 26(12): 334-342 (2010)

Chris D. Bartels, Jeff A. Bilmes: Graphical models for integrating syllabic information. Computer Speech & Language 24(4): 685-697 (2010)

Franz Pernkopf, Jeff A. Bilmes: Efficient Heuristics for Discriminative Structure Learning of Bayesian Network Classifiers. Journal of Machine Learning Research 11: 2323-2360 (2010)

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 Computational Biology 6(7) (2010)

Danny Wyatt, Tanzeem Choudhury, Jeff Bilmes: Discovering Long Range Properties of Social Networks with Multi-Valued Time-Inhomogeneous Models. AAAI 2010

Tetsuya Takiguchi, Jeff Bilmes, Mariko Yoshii, Yasuo Ariki: Evaluation of random-projection-based feature combination on speech recognition. ICASSP 2010: 2150-2153

Gang Ji, Jeff Bilmes: Jointly recognizing multi-speaker conversations. ICASSP 2010: 5110-5113

Andrew Guillory, Jeff Bilmes: Interactive Submodular Set Cover. ICML 2010: 415-422

Jeff Bilmes, Hui Lin: Online adaptive learning for speech recognition decoding. INTERSPEECH 2010: 1958-1961

Jonathan Malkin, Jeff A. Bilmes: Semi-supervised learning for improved expression of uncertainty in discriminative classifiers. INTERSPEECH 2010: 2990-2993

Hui Lin, Jeff Bilmes: Multi-document Summarization via Budgeted Maximization of Submodular Functions. HLT-NAACL 2010: 912-920

Sheila M. Reynolds, Zhiping Weng, Jeff A. Bilmes, William Stafford Noble: Predicting Nucleosome Positioning Using Multiple Evidence Tracks. RECOMB 2010: 441-455

Andrew Guillory, Jeff A. Bilmes: Interactive Submodular Set Cover. CoRR abs/1002.3345 (2010)

Andrew Guillory, Erick Chastain, Jeff Bilmes: Active Learning as Non-Convex Optimization. Journal of Machine Learning Research - Proceedings Track 5: 201-208 (2009)

Franz Pernkopf, Tuan Van Pham, Jeff A. Bilmes: Broad phonetic classification using discriminative Bayesian networks. Speech Communication 51(2): 151-166 (2009)

Mausam, Stephen Soderland, Oren Etzioni, Daniel S. Weld, Michael Skinner, Jeff Bilmes: Compiling a Massive, Multilingual Dictionary via Probabilistic Inference. ACL/IJCNLP 2009: 262-270

Andrew Guillory, Jeff A. Bilmes: Average-Case Active Learning with Costs. ALT 2009: 141-155

Hui Lin, Jeff A. Bilmes, Shasha Xie: Graph-based submodular selection for extractive summarization. ASRU 2009: 381-386

Brandi House, Jonathan Malkin, Jeff Bilmes: The VoiceBot: a voice controlled robot arm. CHI 2009: 183-192

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

Alex Stupakov, Evan Hanusa, Jeff A. Bilmes, Dieter Fox: COSINE - A corpus of multi-party COnversational Speech In Noisy Environments. ICASSP 2009: 4153-4156

Jonathan Malkin, Jeff Bilmes: Multi-layer ratio Semi-Definite Classifiers. ICASSP 2009: 4465-4468

Ning Ma, Chris D. Bartels, Jeff A. Bilmes, Phil Green: Modelling the prepausal lengthening effect for speech recognition: a dynamic Bayesian network approach. ICASSP 2009: 4617-4620

Hui Lin, Alex Stupakov, Jeff Bilmes: Improving multi-lattice alignment based spoken keyword spotting. ICASSP 2009: 4877-4880

Jonathan Malkin, Amarnag Subramanya, Jeff Bilmes: On the semi-supervised learning of multi-layered perceptrons. INTERSPEECH 2009: 660-663

Amarnag Subramanya, Jeff Bilmes: The semi-supervised switchboard transcription project. INTERSPEECH 2009: 1915-1918

Hui Lin, Jeff Bilmes, Koby Crammer: How to loose confidence: probabilistic linear machines for multiclass classification. INTERSPEECH 2009: 2559-2562

Hui Lin, Jeff Bilmes: How to select a good training-data subset for transcription: submodular active selection for sequences. INTERSPEECH 2009: 2859-2862

Andrew Guillory, Jeff A. Bilmes: Label Selection on Graphs. NIPS 2009: 691-699

Yoshinobu Kawahara, Kiyohito Nagano, Koji Tsuda, Jeff A. Bilmes: Submodularity Cuts and Applications. NIPS 2009: 916-924

Amarnag Subramanya, Jeff A. Bilmes: Entropic Graph Regularization in Non-Parametric Semi-Supervised Classification. NIPS 2009: 1803-1811

Sheila M. Reynolds, Jeff A. Bilmes, William Stafford Noble: On the Relationship between DNA Periodicity and Local Chromatin Structure. RECOMB 2009: 434-450

Jeff Bilmes, Andrew Y. Ng (Eds.): UAI 2009, Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence, Montreal, QC, Canada, June 18-21, 2009. AUAI Press 2009

Andrew Guillory, Jeff Bilmes: Average-Case Active Learning with Costs. CoRR abs/0905.2997 (2009)

Sheila M. Reynolds, Lukas Käll, Michael Riffle, Jeff A. Bilmes, William Stafford Noble: Transmembrane Topology and Signal Peptide Prediction Using Dynamic Bayesian Networks. PLoS Computational Biology 4(11) (2008)

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

William Pentney, Matthai Philipose, Jeff A. Bilmes: Structure Learning on Large Scale Common Sense Statistical Models of Human State. AAAI 2008: 1389-1395

Amarnag Subramanya, Jeff Bilmes: Soft-Supervised Learning for Text Classification. EMNLP 2008: 1090-1099

Danny Wyatt, Jeff A. Bilmes, Tanzeem Choudhury, James A. Kitts: Towards the automated social analysis of situated speech data. UbiComp 2008: 168-171

Hui Lin, Jeff Bilmes: Polyphase speech recognition. ICASSP 2008: 4109-4112

Jonathan Malkin, Jeff Bilmes: Ratio semi-definite classifiers. ICASSP 2008: 4113-4116

Hui Lin, Alex Stupakov, Jeff A. Bilmes: Spoken keyword spotting via multi-lattice alignment. INTERSPEECH 2008: 2191-2194

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

Amarnag Subramanya, Jeff A. Bilmes: Applications of virtual-evidence based speech recognizer training. INTERSPEECH 2008: 2562-2565

Andrew Guillory, Jeff Bilmes: Practical Methods for Exploiting Bounds on Change in the Margin. ISAIM 2008

Franz Pernkopf, Jeff Bilmes: Order-based Discriminative Structure Learning for Bayesian Network Classifiers. ISAIM 2008

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

Xiao Li, Jeff Bilmes: A Bayesian Divergence Prior for Classiffier Adaptation. Journal of Machine Learning Research - Proceedings Track 2: 275-282 (2007)

Chia-Ping Chen, Jeff A. Bilmes: MVA Processing of Speech Features. IEEE Transactions on Audio, Speech & Language Processing 15(1): 257-270 (2007)

William Pentney, Matthai Philipose, Jeff A. Bilmes, Henry A. Kautz: Learning Large Scale Common Sense Models of Everyday Life. AAAI 2007: 465-470

Jeff A. Bilmes: Submodularity and adaptation. ASRU 2007: 249

Chris D. Bartels, Jeff A. Bilmes: Use of syllable nuclei locations to improve ASR. ASRU 2007: 335-340

Hui Lin, Jeff Bilmes, Dimitra Vergyri, Katrin Kirchhoff: OOV detection by joint word/phone lattice alignment. ASRU 2007: 478-483

Amarnag Subramanya, Chris D. Bartels, Jeff Bilmes, Patrick Nguyen: Uncertainty in training large vocabulary speech recognizers. ASRU 2007: 484-489

Brandi House, Jonathan Malkin, Jeff Bilmes: Demo of VJ-Voicebot: control of robotic arm with the Vocal Joystick. ASSETS 2007: 247-248

Katherine Everitt, Susumu Harada, Jeff A. Bilmes, James A. Landay: Disambiguating speech commands using physical context. ICMI 2007: 247-254

Mukund Narasimhan, Jeff Bilmes: Local Search for Balanced Submodular Clusterings. IJCAI 2007: 981-986

Danny Wyatt, Tanzeem Choudhury, Jeff Bilmes, Henry A. Kautz: A Privacy-Sensitive Approach to Modeling Multi-Person Conversations. IJCAI 2007: 1769-1775

Danny Wyatt, Tanzeem Choudhury, Jeff Bilmes: Conversation detection and speaker segmentation in privacy-sensitive situated speech data. INTERSPEECH 2007: 586-589

Raghunandan Kumaran, Jeff Bilmes, Katrin Kirchhoff: Attention shift decoding for conversational speech recognition. INTERSPEECH 2007: 1493-1496

Karim Filali, Jeff A. Bilmes: Generalized Graphical Abstractions for Statistical Machine Translation. HLT-NAACL (Short Papers) 2007: 33-36

Amarnag Subramanya, Jeff A. Bilmes: Virtual Evidence for Training Speech Recognizers Using Partially Labeled Data. HLT-NAACL (Short Papers) 2007: 165-168

Marina Meila, Kapil Phadnis, Arthur Patterson, Jeff A. Bilmes: Consensus ranking under the exponential model. UAI 2007: 285-294

Katrin Kirchhoff, Dimitra Vergyri, Jeff Bilmes, Kevin Duh, Andreas Stolcke: Morphology-based language modeling for conversational Arabic speech recognition. Computer Speech & Language 20(4): 589-608 (2006)

Karim Filali, Xiao Li, Jeff Bilmes: Algorithms for data-driven ASR parameter quantization. Computer Speech & Language 20(4): 625-643 (2006)

Jeff A. Bilmes: What HMMs Can Do. IEICE Transactions 89-D(3): 869-891 (2006)

Xiao Li, Jonathan Malkin, Jeff A. Bilmes: A high-speed, low-resource ASR back-end based on custom arithmetic. IEEE Transactions on Audio, Speech & Language Processing 14(5): 1683-1693 (2006)

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

Kelley Kilanski, Jonathan Malkin, Xiao Li, Richard Wright, Jeff A. Bilmes: The vocal joystick data collection effort and vowel corpus. INTERSPEECH 2006

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

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

Gang Ji, Jeff Bilmes: Backoff Model Training using Partially Observed Data: Application to Dialog Act Tagging. HLT-NAACL 2006

Karim Filali, Jeff A. Bilmes: Multi-dynamic Bayesian Networks. NIPS 2006: 409-416

Gang Ji, Jeff Bilmes, Katrin Kirchhoff, Chris Manning: Graphical Model Representations of Word Lattices. SLT 2006: 162-165

Chris D. Bartels, Jeff A. Bilmes: Non-Minimal Triangulations for Mixed Stochastic/Deterministic Graphical Models. UAI 2006

Amar Subramanya, Alvin Raj, Jeff A. Bilmes, Dieter Fox: Recognizing Activities and Spatial Context Using Wearable Sensors. UAI 2006

Robert C. Moore, Jeff A. Bilmes, Jennifer Chu-Carroll, Mark Sanderson (Eds.): 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

Karim Filali, Jeff Bilmes: A Dynamic Bayesian Framework to Model Context and Memory in Edit Distance Learning: An Application to Pronunciation Classification. ACL 2005

Yi Li, Linda G. Shapiro, Jeff A. Bilmes: A Generative/Discriminative Learning Algorithm for Image Classification. ICCV 2005: 1605-1612

Franz Pernkopf, Jeff A. Bilmes: Discriminative versus generative parameter and structure learning of Bayesian network classifiers. ICML 2005: 657-664

Amarnag Subramanya, Jeff Bilmes, Chia-Ping Chen: Focused word segmentation for ASR. INTERSPEECH 2005: 393-396

Xiao Li, Jeff Bilmes, Jonathan Malkin: Maximum margin learning and adaptation of MLP classifiers. INTERSPEECH 2005: 1789-1792

Chris D. Bartels, Kevin Duh, Jeff Bilmes, Katrin Kirchhoff, Simon King: Genetic triangulation of graphical models for speech and language processing. INTERSPEECH 2005: 3329-3332

Simon King, Chris D. Bartels, Jeff Bilmes: SVitchboard 1: small vocabulary tasks from Switchboard. INTERSPEECH 2005: 3385-3388

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

Sheila M. Reynolds, Jeff A. Bilmes: Part-of-Speech Tagging using Virtual Evidence and Negative Training. HLT/EMNLP 2005

Mukund Narasimhan, Nebojsa Jojic, Jeff Bilmes: Q-Clustering. NIPS 2005

Mukund Narasimhan, Jeff A. Bilmes: A Submodular-supermodular Procedure with Applications to Discriminative Structure Learning. UAI 2005: 404-412

Richard W. Vuduc, James Demmel, Jeff A. Bilmes: Statistical Models for Empirical Search-Based Performance Tuning. IJHPCA 18(1): 65-94 (2004)

Yi Li, Jeff A. Bilmes, Linda G. Shapiro: Object Class Recognition using Images of Abstract Regions. ICPR (1) 2004: 40-43

Xiao Li, Jonathan Malkin, Jeff Bilmes: Graphical model approach to pitch tracking. INTERSPEECH 2004

Mukund Narasimhan, Jeff A. Bilmes: Optimal sub-graphical models. NIPS 2004

Mukund Narasimhan, Jeff A. Bilmes: PAC-learning Bounded Tree-width Graphical Models. UAI 2004: 410-417

Martin J. Russell, Jeff A. Bilmes: Introduction to the special issue on new computational paradigms for acoustic modeling in speech recognition. Computer Speech & Language 17(2-3): 107-112 (2003)

Jeff A. Bilmes: Buried Markov models: a graphical-modeling approach to automatic speech recognition. Computer Speech & Language 17(2-3): 213-231 (2003)

Jeff Bilmes, Katrin Kirchhoff: Generalized rules for combination and joint training of classifiers. Pattern Anal. Appl. 6(3): 201-211 (2003)

Matthew Richardson, Jeff Bilmes, Chris Diorio: Hidden-articulator Markov models for speech recognition. Speech Communication 41(2-3): 511-529 (2003)

Karen Livescu, James R. Glass, Jeff Bilmes: Hidden feature models for speech recognition using dynamic Bayesian networks. INTERSPEECH 2003

Jeff Bilmes, Katrin Kirchhoff: Factored Language Models and Generalized Parallel Backoff. HLT-NAACL 2003

Gang Ji, Jeff A. Bilmes: Necessary Intransitive Likelihood-Ratio Classifiers. NIPS 2003

Jeff A. Bilmes, Chris D. Bartels: On Triangulating Dynamic Graphical Models. UAI 2003: 47-56

Geoffrey Zweig, Jeff Bilmes, T. Richardson, Karim Filali, Karen Livescu, P. Xu, K. Jackson, Yigal Brandman, Eric D. Sandness, E. Holtz, J. Torres, B. Byrne: Structurally discriminative graphical models for automatic speech recognition - results from the 2001 Johns Hopkins Summer Workshop. ICASSP 2002: 93-96

Ivan Bulyko, Mari Ostendorf, Jeff Bilmes: Robust splicing costs and efficient search with BMM Models for concatenative speech synthesis. ICASSP 2002: 461-464

Katrin Kirchhoff, Sonia Parandekar, Jeff Bilmes: Mixed-memory Markov models for Automatic Language Identification. ICASSP 2002: 761-764

Jeff Bilmes, Geoffrey Zweig: The graphical models toolkit: An open source software system for speech and time-series processing. ICASSP 2002: 3916-3919

Özgür Çetin, Harriet J. Nock, Katrin Kirchhoff, Jeff A. Bilmes, Mari Ostendorf: The 2001 GMTK-based SPINE ASR system. INTERSPEECH 2002

Chia-Ping Chen, Jeff A. Bilmes, Katrin Kirchhoff: Low-resource noise-robust feature post-processing on Aurora 2.0. INTERSPEECH 2002

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

Karim Filali, Xiao Li, Jeff A. Bilmes: Data-driven vector clustering for low-memory footprint ASR. INTERSPEECH 2002

Rich Vuduc, James Demmel, Jeff Bilmes: Statistical Models for Automatic Performance Tuning. International Conference on Computational Science (1) 2001: 117-126

Jeff Bilmes, Gang Ji, Marina Meila: Intransitive Likelihood-Ratio Classifiers. NIPS 2001: 1141-1148

Daniel P. W. Ellis, Jeff A. Bilmes: Using mutual information to design feature combinations. INTERSPEECH 2000: 79-82

Matthew Richardson, Jeff Bilmes, Chris Diorio: Hidden-articulator Markov models: performance improvements and robustness to noise. INTERSPEECH 2000: 131-134

Jeff A. Bilmes, Katrin Kirchhoff: Directed graphical models of classifier combination: application to phone recognition. INTERSPEECH 2000: 921

Jeff Bilmes: Dynamic Bayesian Multinets. UAI 2000: 38-45

Jeff A. Bilmes: Data-driven extensions to HMM statistical dependencies. ICSLP 1998

Jeff 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

Jeff Bilmes, Nelson Morgan, Su-Lin Wu, Hervé Bourlard: Stochastic perceptual speech models with durational dependence. ICSLP 1996

Nelson Morgan, James Beck, Phil Kohn, Jeff Bilmes, Eric Allman, Joachim Beer: The Ring Array Processor: A Multiprocessing Peripheral for Connection Applications. J. Parallel Distrib. Comput. 14(3): 248-259 (1992)

Oliver Günther, Jeff Bilmes: Tree-Based Access Methods for Spatial Databases: Implementation and Performance Evaluation. IEEE Trans. Knowl. Data Eng. 3(3): 342-356 (1991)

David P. Anderson, Jeff A. Bilmes: Concurrent Real-Time Music in C++. C++ Conference 1991: 147-162

Phil Kohn, Jeff Bilmes, Nelson Morgan, James Beck: Software for ANN Training on a Ring Array Processor. NIPS 1991: 781-788

Oliver Günther, Jeff Bilmes: The Implementation of the Cell Tree: Design Alternatives and Performance Evaluation. BTW 1989: 246-265