Bilmes, Jeff

40 publications

CVPR 2025 COBRA: COmBinatorial Retrieval Augmentation for Few-Shot Adaptation Arnav M. Das, Gantavya Bhatt, Lilly Kumari, Sahil Verma, Jeff Bilmes

TMLR 2025 Effective Backdoor Mitigation in Vision-Language Models Depends on the Pre-Training Objective Sahil Verma, Gantavya Bhatt, Avi Schwarzschild, Soumye Singhal, Arnav Mohanty Das, Chirag Shah, John P Dickerson, Pin-Yu Chen, Jeff Bilmes

TMLR 2025 How Many Images Does It Take? Estimating Imitation Thresholds in Text-to-Image Models Sahil Verma, Royi Rassin, Arnav Mohanty Das, Gantavya Bhatt, Preethi Seshadri, Chirag Shah, Jeff Bilmes, Hannaneh Hajishirzi, Yanai Elazar

ICLR 2025 Many-Objective Multi-Solution Transport Ziyue Li, Tian Li, Virginia Smith, Jeff Bilmes, Tianyi Zhou

ICML 2025 Tilted Sharpness-Aware Minimization Tian Li, Tianyi Zhou, Jeff Bilmes

UAI 2024 Efficient Interactive Maximization of BP and Weakly Submodular Objectives Adhyyan Narang, Omid Sadeghi, Lillian Ratliff, Maryam Fazel, Jeff Bilmes

NeurIPSW 2024 How Many Van Goghs Does It Take to Van Gogh? Finding the Imitation Threshold Sahil Verma, Royi Rassin, Arnav Mohanty Das, Gantavya Bhatt, Preethi Seshadri, Chirag Shah, Jeff Bilmes, Hannaneh Hajishirzi, Yanai Elazar

NeurIPSW 2024 How Many Van Goghs Does It Take to Van Gogh? Finding the Imitation Threshold Sahil Verma, Royi Rassin, Arnav Mohanty Das, Gantavya Bhatt, Preethi Seshadri, Chirag Shah, Jeff Bilmes, Hannaneh Hajishirzi, Yanai Elazar

DMLR 2024 LabelBench: A Comprehensive Framework for Benchmarking Adaptive Label-Efficient Learning Jifan Zhang, Yifang Chen, Gregory Canal, Arnav Mohanty Das, Gantavya Bhatt, Stephen Mussmann, Yinglun Zhu, Jeff Bilmes, Simon Shaolei Du, Kevin Jamieson, Robert D Nowak

TMLR 2023 Accelerating Batch Active Learning Using Continual Learning Techniques Arnav Mohanty Das, Gantavya Bhatt, Megh Manoj Bhalerao, Vianne R. Gao, Rui Yang, Jeff Bilmes

NeurIPSW 2023 Effective Backdoor Mitigation Depends on the Pre-Training Objective Sahil Verma, Gantavya Bhatt, Soumye Singhal, Arnav Mohanty Das, Chirag Shah, John P Dickerson, Jeff Bilmes

NeurIPSW 2023 LabelBench: A Comprehensive Framework for Benchmarking Adaptive Label-Efficient Learning Jifan Zhang, Yifang Chen, Gregory Canal, Arnav Mohanty Das, Gantavya Bhatt, Yinglun Zhu, Stephen Mussmann, Simon Shaolei Du, Jeff Bilmes, Kevin Jamieson, Robert D Nowak

ICLR 2022 Diverse Client Selection for Federated Learning via Submodular Maximization Ravikumar Balakrishnan, Tian Li, Tianyi Zhou, Nageen Himayat, Virginia Smith, Jeff Bilmes

AISTATS 2021 Curriculum Learning by Optimizing Learning Dynamics Tianyi Zhou, Shengjie Wang, Jeff Bilmes

ICLR 2021 Robust Curriculum Learning: From Clean Label Detection to Noisy Label Self-Correction Tianyi Zhou, Shengjie Wang, Jeff Bilmes

ALT 2021 Submodular Combinatorial Information Measures with Applications in Machine Learning Rishabh Iyer, Ninad Khargoankar, Jeff Bilmes, Himanshu Asanani

ICML 2020 Coresets for Data-Efficient Training of Machine Learning Models Baharan Mirzasoleiman, Jeff Bilmes, Jure Leskovec

ICML 2020 Time-Consistent Self-Supervision for Semi-Supervised Learning Tianyi Zhou, Shengjie Wang, Jeff Bilmes

ICML 2019 Bias Also Matters: Bias Attribution for Deep Neural Network Explanation Shengjie Wang, Tianyi Zhou, Jeff Bilmes

ICML 2019 Combating Label Noise in Deep Learning Using Abstention Sunil Thulasidasan, Tanmoy Bhattacharya, Jeff Bilmes, Gopinath Chennupati, Jamal Mohd-Yusof

AISTATS 2019 Fixing Mini-Batch Sequences with Hierarchical Robust Partitioning Shengjie Wang, Wenruo Bai, Chandrashekhar Lavania, Jeff Bilmes

ICML 2019 Jumpout : Improved Dropout for Deep Neural Networks with ReLUs Shengjie Wang, Tianyi Zhou, Jeff Bilmes

ICML 2018 Constrained Interacting Submodular Groupings Andrew Cotter, Mahdi Milani Fard, Seungil You, Maya Gupta, Jeff Bilmes

ICML 2018 Greed Is Still Good: Maximizing Monotone Submodular+Supermodular (BP) Functions Wenruo Bai, Jeff Bilmes

ICLR 2018 Minimax Curriculum Learning: Machine Teaching with Desirable Difficulties and Scheduled Diversity Tianyi Zhou, Jeff Bilmes

ICML 2016 Algorithms for Optimizing the Ratio of Submodular Functions Wenruo Bai, Rishabh Iyer, Kai Wei, Jeff Bilmes

ICML 2016 Analysis of Deep Neural Networks with Extended Data Jacobian Matrix Shengjie Wang, Abdel-rahman Mohamed, Rich Caruana, Jeff Bilmes, Matthai Plilipose, Matthew Richardson, Krzysztof Geras, Gregor Urban, Ozlem Aslan

ICML 2015 Entropic Graph-Based Posterior Regularization Maxwell Libbrecht, Michael Hoffman, Jeff Bilmes, William Noble

ICML 2015 On Deep Multi-View Representation Learning Weiran Wang, Raman Arora, Karen Livescu, Jeff Bilmes

ICML 2015 Submodularity in Data Subset Selection and Active Learning Kai Wei, Rishabh Iyer, Jeff Bilmes

ICML 2014 Fast Multi-Stage Submodular Maximization Kai Wei, Rishabh Iyer, Jeff Bilmes

ICML 2013 Deep Canonical Correlation Analysis Galen Andrew, Raman Arora, Jeff Bilmes, Karen Livescu

ICML 2013 Fast Semidifferential-Based Submodular Function Optimization Rishabh Iyer, Stefanie Jegelka, Jeff Bilmes

AISTATS 2012 Memory-Efficient Inference in Dynamic Graphical Models Using Multiple Cores Galen Andrew, Jeff Bilmes

AISTATS 2012 On Bisubmodular Maximization Ajit Singh, Andrew Guillory, Jeff Bilmes

JMLR 2011 Semi-Supervised Learning with Measure Propagation Amarnag Subramanya, Jeff Bilmes

AISTATS 2009 Active Learning as Non-Convex Optimization Andrew Guillory, Erick Chastain, Jeff Bilmes

AISTATS 2007 A Bayesian Divergence Prior for Classiffier Adaptation Xiao Li, Jeff Bilmes

NeurIPS 2001 Intransitive Likelihood-Ratio Classifiers Jeff Bilmes, Gang Ji, Marina Meila

NeurIPS 1991 Software for ANN Training on a Ring Array Processor Phil Kohn, Jeff Bilmes, Nelson Morgan, James Beck