The Implementation of the Cell Tree: Design Alternatives and Performance Evaluation. - Oliver Günther 001; Jeff A. Bilmes (BTW, 1989)

The RAP: a ring array processor for layered network calculations. - Nelson Morgan; James Beck; Phil Kohn; Jeffrey A. Bilmes; Eric Allman; Joachim Beer (ASAP, 1990)

Concurrent Real-Time Music in C++. - David P. Anderson; Jeff A. Bilmes (C++ Conference, 1991)

Software for ANN Training on a Ring Array Processor. - Phil Kohn; Jeff A. Bilmes; Nelson Morgan; James Beck (NIPS, 1991)

Tree-Based Access Methods for Spatial Databases: Implementation and Performance Evaluation. - Oliver Günther 001; Jeff A. Bilmes (IEEE Trans. Knowl. Data Eng., 1991)

A Model for Musical Rhythm. - Jeff A. Bilmes (ICMC, 1992)

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

Techniques to Foster Drum Machine Expressivity. - Jeff A. Bilmes (ICMC, 1993)

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

Using PHiPAC to speed error back-propagation learning. - Jeff A. Bilmes; Krste Asanovic; Chee-Whye Chin; James Demmel (ICASSP, 1997)

Optimizing Matrix Multiply Using PHiPAC: A Portable, High-Performance, ANSI C Coding Methodology. - Jeff A. Bilmes; Krste Asanovic; Chee-Whye Chin; James Demmel (International Conference on Supercomputing, 1997)

Maximum mutual information based reduction strategies for cross-correlation based joint distributional modeling. - Jeff A. Bilmes (ICASSP, 1998)

Data-driven extensions to HMM statistical dependencies. - Jeff A. Bilmes (ICSLP, 1998)

Buried Markov models for speech recognition. - Jeff A. Bilmes (ICASSP, 1999)

Dynamic classifier combination in hybrid speech recognition systems using utterance-level confidence values. - Katrin Kirchhoff; Jeff A. Bilmes (ICASSP, 1999)

Factored sparse inverse covariance matrices. - Jeff A. Bilmes (ICASSP, 2000)

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

Using mutual information to design feature combinations. - Daniel P. W. Ellis; Jeff A. Bilmes (INTERSPEECH, 2000)

Hidden-articulator Markov models: performance improvements and robustness to noise. - Matthew Richardson; Jeff A. Bilmes; Chris Diorio (INTERSPEECH, 2000)

Dynamic Bayesian Multinets. - Jeff A. Bilmes (UAI, 2000)

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

Intransitive Likelihood-Ratio Classifiers. - Jeff A. Bilmes; Gang Ji; Marina Meila (NIPS, 2001)

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

Robust splicing costs and efficient search with BMM Models for concatenative speech synthesis. - Ivan Bulyko; Mari Ostendorf; Jeff A. Bilmes (ICASSP, 2002)

Mixed-memory Markov models for Automatic Language Identification. - Katrin Kirchhoff; Sonia Parandekar; Jeff A. Bilmes (ICASSP, 2002)

Structurally discriminative graphical models for automatic speech recognition - results from the 2001 Johns Hopkins Summer Workshop. - Geoffrey Zweig; Jeff A. Bilmes; Thomas Richardson 001; Karim Filali; Karen Livescu; Peng Xu; Kirk Jackson; Yigal Brandman; Eric D. Sandness; Eva Holtz; Jerry Torres; Bill Byrne (ICASSP, 2002)

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

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

Frontend post-processing and backend model enhancement on the Aurora 2.0/3.0 databases. - Chia-Ping Chen; Karim Filali; Jeff A. Bilmes (INTERSPEECH, 2002)

Data-driven vector clustering for low-memory footprint ASR. - Karim Filali; Xiao Li 006; Jeff A. Bilmes (INTERSPEECH, 2002)

DBN based multi-stream models for speech. - Yimin Zhang 002; Qian Diao; Shan Huang; Wei Hu 002; Chris D. Bartels; Jeff A. Bilmes (ICASSP (1), 2003)

Novel approaches to Arabic speech recognition: report from the 2002 Johns-Hopkins Summer Workshop. - 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; et al. (ICASSP (1), 2003)

Hidden feature models for speech recognition using dynamic Bayesian networks. - Karen Livescu; James R. Glass; Jeff A. Bilmes (INTERSPEECH, 2003)

Factored Language Models and Generalized Parallel Backoff. - Jeff A. Bilmes; Katrin Kirchhoff (HLT-NAACL, 2003)

Necessary Intransitive Likelihood-Ratio Classifiers. - Gang Ji; Jeff A. Bilmes (NIPS, 2003)

On Triangulating Dynamic Graphical Models. - Jeff A. Bilmes; Chris D. Bartels (UAI, 2003)

Buried Markov models: a graphical-modeling approach to automatic speech recognition. - Jeff A. Bilmes (Comput. Speech Lang., 2003)

Introduction to the special issue on new computational paradigms for acoustic modeling in speech recognition. - Martin J. Russell; Jeff A. Bilmes (Comput. Speech Lang., 2003)

Generalized rules for combination and joint training of classifiers. - Jeff A. Bilmes; Katrin Kirchhoff (Pattern Anal. Appl., 2003)

Hidden-articulator Markov models for speech recognition. - Matthew Richardson; Jeff A. Bilmes; Chris Diorio (Speech Commun., 2003)

DBN based multi-stream models for audio-visual speech recognition. - John N. Gowdy; Amarnag Subramanya; Chris D. Bartels; Jeff A. Bilmes (ICASSP (1), 2004)

Codebook design for ASR systems using custom arithmetic units. - Xiao Li 006; Jonathan Malkin; Jeff A. Bilmes (ICASSP (1), 2004)

Custom arithmetic for high-speed, low-resource ASR systems. - Jonathan Malkin; Xiao Li 006; Jeff A. Bilmes (ICASSP (5), 2004)

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

Graphical model approach to pitch tracking. - Xiao Li 006; Jonathan Malkin; Jeff A. Bilmes (INTERSPEECH, 2004)

Multi-Speaker Language Modeling. - Gang Ji; Jeff A. Bilmes (HLT-NAACL (Short Papers), 2004)

Optimal sub-graphical models. - Mukund Narasimhan; Jeff A. Bilmes (NIPS, 2004)

PAC-learning Bounded Tree-width Graphical Models. - Mukund Narasimhan; Jeff A. Bilmes (UAI, 2004)

Statistical Models for Empirical Search-Based Performance Tuning. - Richard W. Vuduc; James Demmel; Jeff A. Bilmes (Int. J. High Perform. Comput. Appl., 2004)

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

Speech Feature Smoothing for Robust ASR. - Chia-Ping Chen; Jeff A. Bilmes; Daniel P. W. Ellis (ICASSP (1), 2005)

Dialog Act Tagging Using Graphical Models. - Gang Ji; Jeff A. Bilmes (ICASSP (1), 2005)

DBN-Based Multi-stream Models for Mandarin Toneme Recognition. - Xin Lei; Gang Ji; Tim Ng; Jeff A. Bilmes; Mari Ostendorf (ICASSP (1), 2005)

A Graphical Model for Formant Tracking. - Jonathan Malkin; Xiao Li 006; Jeff A. Bilmes (ICASSP (1), 2005)

A Generative/Discriminative Learning Algorithm for Image Classification. - Yi Li; Linda G. Shapiro; Jeff A. Bilmes (ICCV, 2005)

Discriminative versus generative parameter and structure learning of Bayesian network classifiers. - Franz Pernkopf; Jeff A. Bilmes (ICML, 2005)

Genetic triangulation of graphical models for speech and language processing. - Chris D. Bartels; Kevin Duh; Jeff A. Bilmes; Katrin Kirchhoff; Simon King 001 (INTERSPEECH, 2005)

SVitchboard 1: small vocabulary tasks from Switchboard. - Simon King 001; Chris D. Bartels; Jeff A. Bilmes (INTERSPEECH, 2005)

Maximum margin learning and adaptation of MLP classifiers. - Xiao Li 006; Jeff A. Bilmes; Jonathan Malkin (INTERSPEECH, 2005)

Focused word segmentation for ASR. - Amarnag Subramanya; Jeff A. Bilmes; Chia-Ping Chen (INTERSPEECH, 2005)

The Vocal Joystick: A Voice-Based Human-Computer Interface for Individuals with Motor Impairments. - Jeff A. Bilmes; Xiao Li 006; Jonathan Malkin; Kelley Kilanski; Richard Wright; Katrin Kirchhoff; Amar Subramanya; Susumu Harada; James A. Landay; Patricia Dowden; Howard Chizeck (HLT/EMNLP, 2005)

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

Q-Clustering. - Mukund Narasimhan; Nebojsa Jojic; Jeff A. Bilmes (NIPS, 2005)

A Submodular-supermodular Procedure with Applications to Discriminative Structure Learning. - Mukund Narasimhan; Jeff A. Bilmes (UAI, 2005)

Feature pruning for low-power ASR systems in clean and noisy environments. - Xiao Li 006; Jeff A. Bilmes (IEEE Signal Process. Lett., 2005)

Graphical model architectures for speech recognition. - Jeff A. Bilmes; Chris D. Bartels (IEEE Signal Process. Mag., 2005)

The vocal joystick: : evaluation of voice-based cursor control techniques. - Susumu Harada; James A. Landay; Jonathan Malkin; Xiao Li 006; Jeff A. Bilmes (ASSETS, 2006)

The Vocal Joystick. - Jeff A. Bilmes; Jonathan Malkin; Xiao Li 006; Susumu Harada; Kelley Kilanski; Katrin Kirchhoff; Richard Wright; Amarnag Subramanya; James A. Landay; Patricia Dowden; Howard Chizeck (ICASSP (1), 2006)

Regularized Adaptation of Discriminative Classifiers. - Xiao Li 006; Jeff A. Bilmes (ICASSP (1), 2006)

A Factored Language Model of Quantized Pitch and Duration. - Xiao Li 006; Gang Ji; Jeff A. Bilmes (ICMC, 2006)

The vocal joystick data collection effort and vowel corpus. - Kelley Kilanski; Jonathan Malkin; Xiao Li 006; Richard Wright; Jeff A. Bilmes (INTERSPEECH, 2006)

An online adaptive filtering algorithm for the vocal joystick. - Xiao Li 006; Jonathan Malkin; Susumu Harada; Jeff A. Bilmes; Richard Wright; James A. Landay (INTERSPEECH, 2006)

Rao-Blackwellized Particle Filters for Recognizing Activities and Spatial Context from Wearable Sensors. - Alvin Raj; Amarnag Subramanya; Dieter Fox; Jeff A. Bilmes (ISER, 2006)

Hierarchical Models for Activity Recognition. - Amarnag Subramanya; Alvin Raj; Jeff A. Bilmes; Dieter Fox (MMSP, 2006)

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

Multi-dynamic Bayesian Networks. - Karim Filali; Jeff A. Bilmes (NIPS, 2006)

Graphical Model Representations of Word Lattices. - Gang Ji; Jeff A. Bilmes; Jeff Michels; Katrin Kirchhoff; Christopher D. Manning (SLT, 2006)

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

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

Algorithms for data-driven ASR parameter quantization. - Karim Filali; Xiao Li 006; Jeff A. Bilmes (Comput. Speech Lang., 2006)

Morphology-based language modeling for conversational Arabic speech recognition. - Katrin Kirchhoff; Dimitra Vergyri; Jeff A. Bilmes; Kevin Duh; Andreas Stolcke (Comput. Speech Lang., 2006)

What HMMs Can Do. - Jeff A. Bilmes (IEICE Trans. Inf. Syst., 2006)

A high-speed, low-resource ASR back-end based on custom arithmetic. - Xiao Li 006; Jonathan Malkin; Jeff A. Bilmes (IEEE Trans. Speech Audio Process., 2006)

Learning Large Scale Common Sense Models of Everyday Life. - William Pentney; Matthai Philipose; Jeff A. Bilmes; Henry A. Kautz (AAAI, 2007)

Use of syllable nuclei locations to improve ASR. - Chris D. Bartels; Jeff A. Bilmes (ASRU, 2007)

Submodularity and adaptation. - Jeff A. Bilmes (ASRU, 2007)

OOV detection by joint word/phone lattice alignment. - Hui Lin 001; Jeff A. Bilmes; Dimitra Vergyri; Katrin Kirchhoff (ASRU, 2007)

Uncertainty in training large vocabulary speech recognizers. - Amarnag Subramanya; Chris D. Bartels; Jeff A. Bilmes; Patrick Nguyen (ASRU, 2007)

Demo of VJ-Voicebot: control of robotic arm with the Vocal Joystick. - Brandi House; Jonathan Malkin; Jeff A. Bilmes (ASSETS, 2007)

Disambiguating speech commands using physical context. - Katherine Everitt; Susumu Harada; Jeff A. Bilmes; James A. Landay (ICMI, 2007)

Local Search for Balanced Submodular Clusterings. - Mukund Narasimhan; Jeff A. Bilmes (IJCAI, 2007)

A Privacy-Sensitive Approach to Modeling Multi-Person Conversations. - Danny Wyatt; Tanzeem Choudhury; Jeff A. Bilmes; Henry A. Kautz (IJCAI, 2007)

Attention shift decoding for conversational speech recognition. - Raghunandan Kumaran; Jeff A. Bilmes; Katrin Kirchhoff (INTERSPEECH, 2007)

Conversation detection and speaker segmentation in privacy-sensitive situated speech data. - Danny Wyatt; Tanzeem Choudhury; Jeff A. Bilmes (INTERSPEECH, 2007)

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

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

Consensus ranking under the exponential model. - Marina Meila; Kapil Phadnis; Arthur Patterson; Jeff A. Bilmes (UAI, 2007)

A Bayesian Divergence Prior for Classiffier Adaptation. - Xiao Li 006; Jeff A. Bilmes (AISTATS, 2007)

MVA Processing of Speech Features. - Chia-Ping Chen; Jeff A. Bilmes (IEEE Trans. Speech Audio Process., 2007)

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

Learning Hidden Curved Exponential Family Models to Infer Face-to-Face Interaction Networks from Situated Speech Data. - Danny Wyatt; Tanzeem Choudhury; Jeff A. Bilmes (AAAI, 2008)

Soft-Supervised Learning for Text Classification. - Amarnag Subramanya; Jeff A. Bilmes (EMNLP, 2008)

Towards the automated social analysis of situated speech data. - Danny Wyatt; Jeff A. Bilmes; Tanzeem Choudhury; James A. Kitts (UbiComp, 2008)

Polyphase speech recognition. - Hui Lin 001; Jeff A. Bilmes (ICASSP, 2008)

Ratio semi-definite classifiers. - Jonathan Malkin; Jeff A. Bilmes (ICASSP, 2008)

Using syllable nuclei locations to improve automatic speech recognition in the presence of burst noise. - Chris D. Bartels; Jeff A. Bilmes (INTERSPEECH, 2008)

Spoken keyword spotting via multi-lattice alignment. - Hui Lin 001; Alex Stupakov; Jeff A. Bilmes (INTERSPEECH, 2008)

Applications of virtual-evidence based speech recognizer training. - Amarnag Subramanya; Jeff A. Bilmes (INTERSPEECH, 2008)

Practical Methods for Exploiting Bounds on Change in the Margin. - Andrew Guillory; Jeff A. Bilmes (ISAIM, 2008)

Order-based Discriminative Structure Learning for Bayesian Network Classifiers. - Franz Pernkopf; Jeff A. Bilmes (ISAIM, 2008)

Modeling peptide fragmentation with dynamic Bayesian networks for peptide identification. - Aaron A. Klammer; Sheila M. Reynolds; Jeff A. Bilmes; Michael J. MacCoss; William Stafford Noble (ISMB, 2008)

Transmembrane Topology and Signal Peptide Prediction Using Dynamic Bayesian Networks. - Sheila M. Reynolds; Lukas Käll; Michael Riffle; Jeff A. Bilmes; William Stafford Noble (PLoS Comput. Biol., 2008)

Compiling a Massive, Multilingual Dictionary via Probabilistic Inference. - Mausam; Stephen Soderland; Oren Etzioni; Daniel S. Weld; Michael Skinner; Jeff A. Bilmes (ACL/IJCNLP, 2009)

Average-Case Active Learning with Costs. - Andrew Guillory; Jeff A. Bilmes (ALT, 2009)

Graph-based submodular selection for extractive summarization. - Hui Lin 001; Jeff A. Bilmes; Shasha Xie (ASRU, 2009)

Longitudinal study of people learning to use continuous voice-based cursor control. - Susumu Harada; Jacob O. Wobbrock; Jonathan Malkin; Jeff A. Bilmes; James A. Landay (CHI, 2009)

The VoiceBot: a voice controlled robot arm. - Brandi House; Jonathan Malkin; Jeff A. Bilmes (CHI, 2009)

Improving multi-lattice alignment based spoken keyword spotting. - Hui Lin 001; Alex Stupakov; Jeff A. Bilmes (ICASSP, 2009)

Modelling the prepausal lengthening effect for speech recognition: a dynamic Bayesian network approach. - Ning Ma 002; Chris D. Bartels; Jeff A. Bilmes; Phil D. Green (ICASSP, 2009)

Multi-layer ratio Semi-Definite Classifiers. - Jonathan Malkin; Jeff A. Bilmes (ICASSP, 2009)

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

How to select a good training-data subset for transcription: submodular active selection for sequences. - Hui Lin 001; Jeff A. Bilmes (INTERSPEECH, 2009)

How to loose confidence: probabilistic linear machines for multiclass classification. - Hui Lin 001; Jeff A. Bilmes; Koby Crammer (INTERSPEECH, 2009)

On the semi-supervised learning of multi-layered perceptrons. - Jonathan Malkin; Amarnag Subramanya; Jeff A. Bilmes (INTERSPEECH, 2009)

The semi-supervised switchboard transcription project. - Amarnag Subramanya; Jeff A. Bilmes (INTERSPEECH, 2009)

Label Selection on Graphs. - Andrew Guillory; Jeff A. Bilmes (NIPS, 2009)

Submodularity Cuts and Applications. - Yoshinobu Kawahara; Kiyohito Nagano; Koji Tsuda; Jeff A. Bilmes (NIPS, 2009)

Entropic Graph Regularization in Non-Parametric Semi-Supervised Classification. - Amarnag Subramanya; Jeff A. Bilmes (NIPS, 2009)

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

Active Learning as Non-Convex Optimization. - Andrew Guillory; Erick Chastain; Jeff A. Bilmes (AISTATS, 2009)

Broad phonetic classification using discriminative Bayesian networks. - Franz Pernkopf; Tuan Van Pham; Jeff A. Bilmes (Speech Commun., 2009)

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

Jointly recognizing multi-speaker conversations. - Gang Ji; Jeff A. Bilmes (ICASSP, 2010)

Evaluation of random-projection-based feature combination on speech recognition. - Tetsuya Takiguchi; Jeff A. Bilmes; Mariko Yoshii; Yasuo Ariki (ICASSP, 2010)

Interactive Submodular Set Cover. - Andrew Guillory; Jeff A. Bilmes (ICML, 2010)

Online adaptive learning for speech recognition decoding. - Jeff A. Bilmes; Hui Lin 001 (INTERSPEECH, 2010)

Semi-supervised learning for improved expression of uncertainty in discriminative classifiers. - Jonathan Malkin; Jeff A. Bilmes (INTERSPEECH, 2010)

Multi-document Summarization via Budgeted Maximization of Submodular Functions. - Hui Lin 001; Jeff A. Bilmes (HLT-NAACL, 2010)

Predicting Nucleosome Positioning Using Multiple Evidence Tracks. - Sheila M. Reynolds; Zhiping Weng; Jeff A. Bilmes; William Stafford Noble (RECOMB, 2010)

Panlingual lexical translation via probabilistic inference. - Mausam; Stephen Soderland; Oren Etzioni; Daniel S. Weld; Kobi Reiter; Michael Skinner; Marcus Sammer; Jeff A. Bilmes (Artif. Intell., 2010)

A dynamic Bayesian network for identifying protein-binding footprints from single molecule-based sequencing data. - Xiaoyu Chen; Michael M. Hoffman; Jeff A. Bilmes; Jay R. Hesselberth; William Stafford Noble (Bioinform., 2010)

Graphical models for integrating syllabic information. - Chris D. Bartels; Jeff A. Bilmes (Comput. Speech Lang., 2010)

Efficient Heuristics for Discriminative Structure Learning of Bayesian Network Classifiers. - Franz Pernkopf; Jeff A. Bilmes (J. Mach. Learn. Res., 2010)

Learning a Weighted Sequence Model of the Nucleosome Core and Linker Yields More Accurate Predictions in Saccharomyces cerevisiae and Homo sapiens. - Sheila M. Reynolds; Jeff A. Bilmes; William Stafford Noble (PLoS Comput. Biol., 2010)

Dynamic Graphical Models. - Jeff A. Bilmes (IEEE Signal Process. Mag., 2010)

A Class of Submodular Functions for Document Summarization. - Hui Lin 001; Jeff A. Bilmes (ACL, 2011)

Word Alignment via Submodular Maximization over Matroids. - Hui Lin 001; Jeff A. Bilmes (ACL (2), 2011)

Submodularity beyond submodular energies: Coupling edges in graph cuts. - Stefanie Jegelka; Jeff A. Bilmes (CVPR, 2011)

Simultaneous Learning and Covering with Adversarial Noise. - Andrew Guillory; Jeff A. Bilmes (ICML, 2011)

Online Submodular Minimization for Combinatorial Structures. - Stefanie Jegelka; Jeff A. Bilmes (ICML, 2011)

Approximation Bounds for Inference using Cooperative Cuts. - Stefanie Jegelka; Jeff A. Bilmes (ICML, 2011)

Optimal Selection of Limited Vocabulary Speech Corpora. - Hui Lin 001; Jeff A. Bilmes (INTERSPEECH, 2011)

Applications of submodular functions in speech and NLP. - Jeff A. Bilmes; Hui Lin 001; Andrew Guillory (MLSLP, 2011)

Online Submodular Set Cover, Ranking, and Repeated Active Learning. - Andrew Guillory; Jeff A. Bilmes (NIPS, 2011)

On fast approximate submodular minimization. - Stefanie Jegelka; Hui Lin 001; Jeff A. Bilmes (NIPS, 2011)

Active Semi-Supervised Learning using Submodular Functions. - Andrew Guillory; Jeff A. Bilmes (UAI, 2011)

Learning sparse models for a dynamic Bayesian network classifier of protein secondary structure. - Zafer Aydin; Ajit P. Singh; Jeff A. Bilmes; William Stafford Noble (BMC Bioinform., 2011)

The Vocal Joystick Engine v1.0. - Jonathan Malkin; Xiao Li 006; Susumu Harada; James A. Landay; Jeff A. Bilmes (Comput. Speech Lang., 2011)

Semi-Supervised Learning with Measure Propagation. - Amarnag Subramanya; Jeff A. Bilmes (J. Mach. Learn. Res., 2011)

Creating non-minimal triangulations for use in inference in mixed stochastic/deterministic graphical models. - Chris D. Bartels; Jeff A. Bilmes (Mach. Learn., 2011)

Inferring colocation and conversation networks from privacy-sensitive audio with implications for computational social science. - Danny Wyatt; Tanzeem Choudhury; Jeff A. Bilmes; James A. Kitts (ACM Trans. Intell. Syst. Technol., 2011)

Sequential Deep Belief Networks. - Galen Andrew; Jeff A. Bilmes (ICASSP, 2012)

Acoustic model transformations based on random projections. - Tetsuya Takiguchi; Mariko Yoshii; Yasuo Ariki; Jeff A. Bilmes (ICASSP, 2012)

Submodular-Bregman and the Lovász-Bregman Divergences with Applications. - Rishabh K. Iyer; Jeff A. Bilmes (NIPS, 2012)

Algorithms for Approximate Minimization of the Difference Between Submodular Functions, with Applications. - Rishabh K. Iyer; Jeff A. Bilmes (UAI, 2012)

Learning Mixtures of Submodular Shells with Application to Document Summarization. - Hui Lin 001; Jeff A. Bilmes (UAI, 2012)

Spectrum Identification using a Dynamic Bayesian Network Model of Tandem Mass Spectra. - Ajit P. Singh; John T. Halloran; Jeff A. Bilmes; Katrin Kirchhoff; William Stafford Noble (UAI, 2012)

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

The design and collection of COSINE, a multi-microphone in situ speech corpus recorded in noisy environments. - Alex Stupakov; Evan Hanusa; Deepak Vijaywargi; Dieter Fox; Jeff A. Bilmes (Comput. Speech Lang., 2012)

Memory-efficient inference in dynamic graphical models using multiple cores. - Galen Andrew; Jeff A. Bilmes (AISTATS, 2012)

On Bisubmodular Maximization. - Ajit P. Singh; Andrew Guillory; Jeff A. Bilmes (AISTATS, 2012)

Unsupervised pattern discovery in human chromatin structure through genomic segmentation. - Michael M. Hoffman; Orion J. Buske; Jie Wang; Zhiping Weng; Jeff A. Bilmes; William Stafford Noble (BCB, 2013)

Submodular feature selection for high-dimensional acoustic score spaces. - Yuzong Liu; Kai Wei; Katrin Kirchhoff; Yisong Song; Jeff A. Bilmes (ICASSP, 2013)

Deep Canonical Correlation Analysis. - Galen Andrew; Raman Arora; Jeff A. Bilmes; Karen Livescu (ICML (3), 2013)

Fast Semidifferential-based Submodular Function Optimization. - Rishabh K. Iyer; Stefanie Jegelka; Jeff A. Bilmes (ICML (3), 2013)

Classification of developmental disorders from speech signals using submodular feature selection. - Katrin Kirchhoff; Yuzong Liu; Jeff A. Bilmes (INTERSPEECH, 2013)

Using Document Summarization Techniques for Speech Data Subset Selection. - Kai Wei; Yuzong Liu; Katrin Kirchhoff; Jeff A. Bilmes (HLT-NAACL, 2013)

Submodular Optimization with Submodular Cover and Submodular Knapsack Constraints. - Rishabh K. Iyer; Jeff A. Bilmes (NIPS, 2013)

Curvature and Optimal Algorithms for Learning and Minimizing Submodular Functions. - Rishabh K. Iyer; Stefanie Jegelka; Jeff A. Bilmes (NIPS, 2013)

The Lovasz-Bregman Divergence and connections to rank aggregation, clustering, and web ranking. - Rishabh K. Iyer; Jeff A. Bilmes (UAI, 2013)

Submodularity for Data Selection in Machine Translation. - Katrin Kirchhoff; Jeff A. Bilmes (EMNLP, 2014)

Unsupervised submodular subset selection for speech data. - Kai Wei; Yuzong Liu; Katrin Kirchhoff; Jeff A. Bilmes (ICASSP, 2014)

Submodular subset selection for large-scale speech training data. - Kai Wei; Yuzong Liu; Katrin Kirchhoff; Chris D. Bartels; Jeff A. Bilmes (ICASSP, 2014)

Fast Multi-stage Submodular Maximization. - Kai Wei; Rishabh K. Iyer; Jeff A. Bilmes (ICML, 2014)

Author retrospective for optimizing matrix multiply using PHiPAC: a portable high-performance ANSI C coding methodology. - Jeff A. Bilmes; Krste Asanovic; Chee-Whye Chin; Jim Demmel (ICS 25th Anniversary, 2014)

Learning Mixtures of Submodular Functions for Image Collection Summarization. - Sebastian Tschiatschek; Rishabh K. Iyer; Haochen Wei; Jeff A. Bilmes (NIPS, 2014)

Divide-and-Conquer Learning by Anchoring a Conical Hull. - Tianyi Zhou 001; Jeff A. Bilmes; Carlos Guestrin (NIPS, 2014)

Learning Peptide-Spectrum Alignment Models for Tandem Mass Spectrometry. - John T. Halloran; Jeff A. Bilmes; William Stafford Noble (UAI, 2014)

Monotone Closure of Relaxed Constraints in Submodular Optimization: Connections Between Minimization and Maximization. - Rishabh K. Iyer; Stefanie Jegelka; Jeff A. Bilmes (UAI, 2014)

Graph Cuts with Interacting Edge Costs - Examples, Approximations, and Algorithms. - Stefanie Jegelka; Jeff A. Bilmes (CoRR, 2014)

Summarization of Multi-Document Topic Hierarchies using Submodular Mixtures. - Ramakrishna Bairi; Rishabh K. Iyer; Ganesh Ramakrishnan; Jeff A. Bilmes (ACL (1), 2015)

Submodular Point Processes with Applications to Machine learning. - Rishabh K. Iyer; Jeff A. Bilmes (AISTATS, 2015)

On Approximate Non-submodular Minimization via Tree-Structured Supermodularity. - Yoshinobu Kawahara; Rishabh K. Iyer; Jeff A. Bilmes (AISTATS, 2015)

Unsupervised learning of acoustic features via deep canonical correlation analysis. - Weiran Wang; Raman Arora; Karen Livescu; Jeff A. Bilmes (ICASSP, 2015)

Entropic Graph-based Posterior Regularization. - Maxwell W. Libbrecht; Michael M. Hoffman; Jeff A. Bilmes; William Stafford Noble (ICML, 2015)

On Deep Multi-View Representation Learning. - Weiran Wang; Raman Arora; Karen Livescu; Jeff A. Bilmes (ICML, 2015)

Submodularity in Data Subset Selection and Active Learning. - Kai Wei; Rishabh K. Iyer; Jeff A. Bilmes (ICML, 2015)

SVitchboard II and fiSVer i: high-quality limited-complexity corpora of conversational English speech. - Yuzong Liu; Rishabh K. Iyer; Katrin Kirchhoff; Jeff A. Bilmes (INTERSPEECH, 2015)

Submodular Hamming Metrics. - Jennifer Gillenwater; Rishabh K. Iyer; Bethany Lusch; Rahul Kidambi; Jeff A. Bilmes (NIPS, 2015)

Mixed Robust/Average Submodular Partitioning: Fast Algorithms, Guarantees, and Applications. - Kai Wei; Rishabh K. Iyer; Shengjie Wang; Wenruo Bai; Jeff A. Bilmes (NIPS, 2015)

Polyhedral aspects of Submodularity, Convexity and Concavity. - Rishabh K. Iyer; Jeff A. Bilmes (CoRR, 2015)

Mixed Robust/Average Submodular Partitioning: Fast Algorithms, Guarantees, and Applications to Parallel Machine Learning and Multi-Label Image Segmentation. - Kai Wei; Rishabh K. Iyer; Shengjie Wang; Wenruo Bai; Jeff A. Bilmes (CoRR, 2015)

Bipartite matching generalizations for peptide identification in tandem mass spectrometry. - Wenruo Bai; Jeffrey A. Bilmes; William S. Noble (BCB, 2016)

Constrained robust submodular sensor selection with applications to multistatic sonar arrays. - Thomas Powers; Jeff A. Bilmes; David W. Krout; Les E. Atlas (FUSION, 2016)

A weakly supervised activity recognition framework for real-time synthetic biology laboratory assistance. - Chandrashekhar Lavania; Sunil Thulasidasan; Anthony LaMarca; Jeffrey Scofield; Jeff A. Bilmes (UbiComp, 2016)

Algorithms for Optimizing the Ratio of Submodular Functions. - Wenruo Bai; Rishabh K. Iyer; Kai Wei; Jeff A. Bilmes (ICML, 2016)

Analysis of Deep Neural Networks with Extended Data Jacobian Matrix. - Shengjie Wang; Abdel-rahman Mohamed; Rich Caruana; Jeff A. Bilmes; Matthai Philipose; Matthew Richardson; Krzysztof J. Geras; Gregor Urban; Özlem Aslan (ICML, 2016)

Deep Submodular Functions: Definitions and Learning. - Brian W. Dolhansky; Jeff A. Bilmes (NIPS, 2016)

Faster and more accurate graphical model identification of tandem mass spectra using trellises. - Shengjie Wang; John T. Halloran; Jeff A. Bilmes; William S. Noble (Bioinform., 2016)

Semi-Supervised Phone Classification using Deep Neural Networks and Stochastic Graph-Based Entropic Regularization. - Sunil Thulasidasan; Jeffrey A. Bilmes (CoRR, 2016)

Efficient Distributed Semi-Supervised Learning using Stochastic Regularization over Affinity Graphs. - Sunil Thulasidasan; Jeffrey A. Bilmes; Garrett T. Kenyon (CoRR, 2016)

On Deep Multi-View Representation Learning: Objectives and Optimization. - Weiran Wang; Raman Arora; Karen Livescu; Jeff A. Bilmes (CoRR, 2016)

Stream Clipper: Scalable Submodular Maximization on Stream. - Tianyi Zhou 001; Jeff A. Bilmes (CoRR, 2016)

Speech Production in Speech Technologies: Introduction to the CSL Special Issue. - Karen Livescu; Frank Rudzicz; Eric Fosler-Lussier; Mark Hasegawa-Johnson; Jeff A. Bilmes (Comput. Speech Lang., 2016)

Scaling Submodular Maximization via Pruned Submodularity Graphs. - Tianyi Zhou 001; Hua Ouyang; Jeff A. Bilmes; Yi Chang 001; Carlos Guestrin (AISTATS, 2017)

Reducing total latency in online real-time inference and decoding via combined context window and model smoothing latencies. - Chandrashekhar Lavania; Jeff A. Bilmes (ICASSP, 2017)

Acoustic classification using semi-supervised Deep Neural Networks and stochastic entropy-regularization over nearest-neighbor graphs. - Sunil Thulasidasan; Jeffrey A. Bilmes (ICASSP, 2017)

Training Compressed Fully-Connected Networks with a Density-Diversity Penalty. - Shengjie Wang; Haoran Cai; Jeff A. Bilmes; William S. Noble (ICLR (Poster), 2017)

Deep Submodular Functions. - Jeffrey A. Bilmes; Wenruo Bai (CoRR, 2017)

SVitchboard-II and FiSVer-I: Crafting high quality and low complexity conversational english speech corpora using submodular function optimization. - Yuzong Liu; Rishabh K. Iyer; Katrin Kirchhoff; Jeff A. Bilmes (Comput. Speech Lang., 2017)

Graph cuts with interacting edge weights: examples, approximations, and algorithms. - Stefanie Jegelka; Jeff A. Bilmes (Math. Program., 2017)

Segway 2.0 Application Note Datasets. - Rachel C. W. Chan; Maxwell W. Libbrecht; Eric G. Roberts; Jeffrey A. Bilmes; William Stafford Noble; Michael M. Hoffman (Zenodo, 2017)

Segway 2.0 Application Note Scripts. - Rachel C. W. Chan; Maxwell W. Libbrecht; Eric G. Roberts; Jeffrey A. Bilmes; William Stafford Noble; Michael M. Hoffman (Zenodo, 2017)

Choosing Non-redundant Representative Subsets Of Protein Sequence Data Sets Using Submodular Optimization. - Maxwell W. Libbrecht; Jeffrey A. Bilmes; William Stafford Noble (BCB, 2018)

Minimax Curriculum Learning: Machine Teaching with Desirable Difficulties and Scheduled Diversity. - Tianyi Zhou 001; Jeff A. Bilmes (ICLR (Poster), 2018)

Greed is Still Good: Maximizing Monotone Submodular+Supermodular (BP) Functions. - Wenruo Bai; Jeffrey A. Bilmes (ICML, 2018)

Constrained Interacting Submodular Groupings. - Andrew Cotter; Mahdi Milani Fard; Seungil You; Maya R. Gupta; Jeff A. Bilmes (ICML, 2018)

Submodular Maximization via Gradient Ascent: The Case of Deep Submodular Functions. - Wenruo Bai; William Stafford Noble; Jeff A. Bilmes (NeurIPS, 2018)

Diverse Ensemble Evolution: Curriculum Data-Model Marriage. - Tianyi Zhou 001; Shengjie Wang; Jeff A. Bilmes (NeurIPS, 2018)

Segway 2.0: Gaussian mixture models and minibatch training. - Rachel C. W. Chan; Maxwell W. Libbrecht; Eric G. Roberts; Jeffrey A. Bilmes; William Stafford Noble; Michael M. Hoffman (Bioinform., 2018)

Greed is Still Good: Maximizing Monotone Submodular+Supermodular Functions. - Wenruo Bai; Jeffrey A. Bilmes (CoRR, 2018)

Near Optimal Algorithms for Hard Submodular Programs with Discounted Cooperative Costs. - Rishabh K. Iyer; Jeffrey A. Bilmes (AISTATS, 2019)

A Memoization Framework for Scaling Submodular Optimization to Large Scale Problems. - Rishabh K. Iyer; Jeffrey A. Bilmes (AISTATS, 2019)

Fixing Mini-batch Sequences with Hierarchical Robust Partitioning. - Shengjie Wang; Wenruo Bai; Chandrashekhar Lavania; Jeff A. Bilmes (AISTATS, 2019)

Combating Label Noise in Deep Learning using Abstention. - Sunil Thulasidasan; Tanmoy Bhattacharya 001; Jeff A. Bilmes; Gopinath Chennupati; Jamal Mohd-Yusof (ICML, 2019)

Bias Also Matters: Bias Attribution for Deep Neural Network Explanation. - Shengjie Wang; Tianyi Zhou 001; Jeff A. Bilmes (ICML, 2019)

Jumpout : Improved Dropout for Deep Neural Networks with ReLUs. - Shengjie Wang; Tianyi Zhou 001; Jeff A. Bilmes (ICML, 2019)

On Mixup Training: Improved Calibration and Predictive Uncertainty for Deep Neural Networks. - Sunil Thulasidasan; Gopinath Chennupati; Jeff A. Bilmes; Tanmoy Bhattacharya 001; Sarah Michalak (NeurIPS, 2019)

Auto-Summarization: A Step Towards Unsupervised Learning of a Submodular Mixture. - Chandrashekhar Lavania; Jeff A. Bilmes (SDM, 2019)

Data Sketching for Faster Training of Machine Learning Models. - Baharan Mirzasoleiman; Jeff A. Bilmes; Jure Leskovec (CoRR, 2019)

Submodular Generalized Matching for Peptide Identification in Tandem Mass Spectrometry. - Wenruo Bai; Jeffrey A. Bilmes; William S. Noble (IEEE ACM Trans. Comput. Biol. Bioinform., 2019)

Avocado: Deep tensor factorization characterizes the human epigenome via imputation of tens of thousands of functional experiments. - Jacob M. Schreiber; Timothy J. Durham; William S. Noble; Jeffrey A. Bilmes (BCB, 2020)

Submodular sketches of single-cell RNA-seq measurements. - Wei Yang; Jeffrey A. Bilmes; William Stafford Noble (BCB, 2020)

Coresets for Data-efficient Training of Machine Learning Models. - Baharan Mirzasoleiman; Jeff A. Bilmes; Jure Leskovec (ICML, 2020)

Time-Consistent Self-Supervision for Semi-Supervised Learning. - Tianyi Zhou 001; Shengjie Wang; Jeff A. Bilmes (ICML, 2020)

Concave Aspects of Submodular Functions. - Rishabh K. Iyer; Jeff A. Bilmes (ISIT, 2020)

Curriculum Learning by Dynamic Instance Hardness. - Tianyi Zhou 001; Shengjie Wang; Jeff A. Bilmes (NeurIPS, 2020)

A Unified Framework for Generic, Query-Focused, Privacy Preserving and Update Summarization using Submodular Information Measures. - Vishal Kaushal; Suraj Kothawade; Ganesh Ramakrishnan; Jeff A. Bilmes; Himanshu Asnani; Rishabh K. Iyer (CoRR, 2020)

apricot: Submodular selection for data summarization in Python. - Jacob M. Schreiber; Jeffrey A. Bilmes; William Stafford Noble (J. Mach. Learn. Res., 2020)

Submodular Span, with Applications to Conditional Data Summarization. - Lilly Kumari; Jeff A. Bilmes (AAAI, 2021)

Curriculum Learning by Optimizing Learning Dynamics. - Tianyi Zhou 001; Shengjie Wang; Jeff A. Bilmes (AISTATS, 2021)

Submodular combinatorial information measures with applications in machine learning. - Rishabh K. Iyer; Ninad Khargoankar; Jeff A. Bilmes; Himanshu Asanani (ALT, 2021)

Robust Curriculum Learning: from clean label detection to noisy label self-correction. - Tianyi Zhou 001; Shengjie Wang; Jeff A. Bilmes (ICLR, 2021)

An Effective Baseline for Robustness to Distributional Shift. - Sunil Thulasidasan; Sushil Thapa; Sayera Dhaubhadel; Gopinath Chennupati; Tanmoy Bhattacharya 001; Jeff A. Bilmes (ICMLA, 2021)

Independence Properties of Generalized Submodular Information Measures. - Himanshu Asnani; Jeff A. Bilmes; Rishabh K. Iyer (ISIT, 2021)

Constrained Robust Submodular Partitioning. - Shengjie Wang; Tianyi Zhou 001; Chandrashekhar Lavania; Jeff A. Bilmes (NeurIPS, 2021)

A Practical Online Framework for Extracting Running Video Summaries under a Fixed Memory Budget. - Chandrashekhar Lavania; Kai Wei; Rishabh K. Iyer; Jeff A. Bilmes (SDM, 2021)

DIAmeter: matching peptides to data-independent acquisition mass spectrometry data. - Yang Young Lu; Jeff A. Bilmes; Ricard A. Rodriguez-Mias; Judit Villén; William Stafford Noble (Bioinform., 2021)

Prioritizing transcriptomic and epigenomic experiments using an optimization strategy that leverages imputed data. - Jacob M. Schreiber; Jeffrey A. Bilmes; William Stafford Noble (Bioinform., 2021)

PRISM: A Unified Framework of Parameterized Submodular Information Measures for Targeted Data Subset Selection and Summarization. - Vishal Kaushal; Suraj Kothawade; Ganesh Ramakrishnan; Jeff A. Bilmes; Rishabh K. Iyer (CoRR, 2021)

Submodular Mutual Information for Targeted Data Subset Selection. - Suraj Kothawade; Vishal Kaushal; Ganesh Ramakrishnan; Jeff A. Bilmes; Rishabh K. Iyer (CoRR, 2021)

PRISM: A Rich Class of Parameterized Submodular Information Measures for Guided Data Subset Selection. - Suraj Kothawade; Vishal Kaushal; Ganesh Ramakrishnan; Jeff A. Bilmes; Rishabh K. Iyer (AAAI, 2022)

Diverse Client Selection for Federated Learning via Submodular Maximization. - Ravikumar Balakrishnan; Tian Li 005; Tianyi Zhou 001; Nageen Himayat; Virginia Smith; Jeff A. Bilmes (ICLR, 2022)

Retrospective Adversarial Replay for Continual Learning. - Lilly Kumari; Shengjie Wang; Tianyi Zhou 001; Jeff A. Bilmes (NeurIPS, 2022)

Linking cells across single-cell modalities by synergistic matching of neighborhood structure. - Borislav H. Hristov; Jeff A. Bilmes; William Stafford Noble (Bioinform., 2022)

Submodularity In Machine Learning and Artificial Intelligence. - Jeff A. Bilmes (CoRR, 2022)

Interactive Combinatorial Bandits: Balancing Competitivity and Complementarity. - Adhyyan Narang; Omid Sadeghi; Lillian J. Ratliff; Maryam Fazel; Jeff A. Bilmes (CoRR, 2022)

Generalized Submodular Information Measures: Theoretical Properties, Examples, Optimization Algorithms, and Applications. - Rishabh K. Iyer; Ninad Khargonkar; Jeff A. Bilmes; Himanshu Asnani (IEEE Trans. Inf. Theory, 2022)

High Resolution Point Clouds from mmWave Radar. - Akarsh Prabhakara; Tao Jin; Arnav Das 001; Gantavya Bhatt; Lilly Kumari; Elahe Soltanaghai; Jeff A. Bilmes; Swarun Kumar; Anthony Rowe 001 (ICRA, 2023)

RadarHD: Demonstrating Lidar-like Point Clouds from mmWave Radar. - Akarsh Prabhakara; Tao Jin; Arnav Das 001; Gantavya Bhatt; Lilly Kumari; Elahe Soltanaghai; Jeff A. Bilmes; Swarun Kumar; Anthony Rowe 001 (MobiCom, 2023)

Effective Backdoor Mitigation Depends on the Pre-training Objective. - Sahil Verma; Gantavya Bhatt; Avi Schwarzschild; Soumye Singhal; Arnav Mohanty Das; Chirag Shah 001; John P. Dickerson; Jeff A. Bilmes (CoRR, 2023)

Accelerating Batch Active Learning Using Continual Learning Techniques. - Arnav Mohanty Das; Gantavya Bhatt; Megh Manoj Bhalerao; Vianne R. Gao; Rui Yang; Jeff A. Bilmes (Trans. Mach. Learn. Res., 2023)

MS1Connect: a mass spectrometry run similarity measure. - Andy Lin; Brooke L. Deatherage Kaiser; Janine R. Hutchison; Jeffrey A. Bilmes; William Stafford Noble (Bioinform., 2023)

An Experimental Design Framework for Label-Efficient Supervised Finetuning of Large Language Models. - Gantavya Bhatt; Yifang Chen 001; 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 (ACL (Findings), 2024)

An End-to-End Submodular Framework for Data-Efficient In-Context Learning. - Lilly Kumari; Shengjie Wang; Arnav Das 001; Tianyi Zhou 001; Jeff A. Bilmes (NAACL-HLT (Findings), 2024)

Deep Submodular Peripteral Networks. - Gantavya Bhatt; Arnav Das 001; Jeff A. Bilmes (NeurIPS, 2024)

Efficient Interactive Maximization of BP and Weakly Submodular Objectives. - Adhyyan Narang; Omid Sadeghi; Lillian J. Ratliff; Maryam Fazel; Jeff A. Bilmes (UAI, 2024)

How Many Van Goghs Does It Take to Van Gogh? Finding the Imitation Threshold. - Sahil Verma; Royi Rassin; Arnav Das 001; Gantavya Bhatt; Preethi Seshadri; Chirag Shah 001; Jeff A. Bilmes; Hannaneh Hajishirzi; Yanai Elazar (CoRR, 2024)

Reweighting Local Mimina with Tilted SAM. - Tian Li 005; Tianyi Zhou 001; Jeffrey A. Bilmes (CoRR, 2024)