Jeff Bilmes

1. On Deep Multi-View Representation Learning: Objectives and Optimization
   2016/02/02 by Weiran Wang, Wang, Weiran, Raman Arora +5 · 18 citations
   Computer Science · #Advanced Image and Video Retrieval Techniques #FOS: Computer and information sciences #Image Retrieval and Classification Techniques #Machine Learning (cs.LG) #Video Analysis and Summarization
2. On Mixup Training: Improved Calibration and Predictive Uncertainty for\n Deep Neural Networks
   2019/05/27 by Sunil Thulasidasan, Thulasidasan, Sunil, Gopinath Chennupati +7 · 17 citations
   Computer Science · #Machine Learning and Data Classification #Adversarial Robustness in Machine Learning #Anomaly Detection Techniques and Applications
3. Learning Mixtures of Submodular Shells with Application to Document Summarization
   2012/10/16 by Hui Lin, Jeff Bilmes, Lin, Hui +1 · 10 citations
   Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Information Retrieval (cs.IR) #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Natural Language Processing Techniques #Text and Document Classification Technologies #Topic Modeling
4. PRISM: A Rich Class of Parameterized Submodular Information Measures for Guided Subset Selection
   2021/02/27 by Suraj Kothawade, Kothawade, Suraj, Vishal Kaushal +7 · 8 citations
   Computer Science · #Advanced Image and Video Retrieval Techniques #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Image Retrieval and Classification Techniques #Text and Document Classification Technologies
5. Submodularity In Machine Learning and Artificial Intelligence
   2022/01/31 by Jeff Bilmes, Bilmes, Jeff · 7 citations
   Computer Science · #Artificial Intelligence (cs.AI) #Data Mining Algorithms and Applications #FOS: Computer and information sciences #Imbalanced Data Classification Techniques #Machine Learning (cs.LG) #Rough Sets and Fuzzy Logic
6. Active Semi-Supervised Learning using Submodular Functions
   2012/02/14 by Andrew Guillory, Guillory, Andrew, Jeff Bilmes +1 · 4 citations
   Computer Science · #Machine Learning and Algorithms #Complexity and Algorithms in Graphs #Advanced Graph Neural Networks
7. A submodular-supermodular procedure with applications to discriminative\n structure learning
   2012/07/04 by Mukund Narasimhan, Narasimhan, Mukund, Jeff Bilmes +1 · 3 citations
   Computer Science · #Advanced Graph Theory Research #Complexity and Algorithms in Graphs #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Neural Networks and Applications #Rough Sets and Fuzzy Logic
8. Average-Case Active Learning with Costs
   2009/05/18 by Andrew Guillory, Guillory, Andrew, Jeff Bilmes +1 · 3 citations
   Computer Science · Decision Sciences · #Machine Learning and Algorithms #Optimization and Search Problems #Advanced Bandit Algorithms Research
9. Fast Semidifferential-based Submodular Function Optimization
   2013/08/05 by Rishabh Iyer, Iyer, Rishabh, Stefanie Jegelka +3 · 4 citations
   Computer Science · #Complexity and Algorithms in Graphs #Computational Geometry and Mesh Generation #Machine Learning and Algorithms
10. Submodular Mutual Information for Targeted Data Subset Selection
    2021/04/30 by Suraj Kothawade, Vishal Kaushal, Kothawade, Suraj +7 · 2 citations
    Computer Science · #Algorithms and Data Compression #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and Algorithms #Machine Learning and Data Classification
11. A Memoization Framework for Scaling Submodular Optimization to Large\n Scale Problems
    2019/02/26 by Rishabh Iyer, Iyer, Rishabh, Jeffrey A. Bilmes +2 · 2 citations
    Computer Science · #Complexity and Algorithms in Graphs #Advanced Graph Theory Research #Cryptography and Data Security
12. Curvature and Optimal Algorithms for Learning and Minimizing Submodular\n Functions
    2013/11/08 by Rishabh Iyer, Iyer, Rishabh, Stefanie Jegelka +3 · 1 citation
    Computer Science · #Complexity and Algorithms in Graphs #Cryptography and Data Security #Data Structures and Algorithms (cs.DS) #Discrete Mathematics (cs.DM) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and Algorithms #Stochastic Gradient Optimization Techniques
13. The Lovasz-Bregman Divergence and connections to rank aggregation, clustering, and web ranking
    2014/08/09 by Rishabh Iyer, Iyer, Rishabh, Jeff Bilmes +1 · 1 citation
    Computer Science · Decision Sciences · Mathematics · #Bayesian Modeling and Causal Inference #Multi-Criteria Decision Making #Advanced Statistical Methods and Models
14. How Many Images Does It Take? Estimating Imitation Thresholds in Text-to-Image Models
    2024/10/19 by Sahil Verma, Verma, Sahil, Royi Rassin +15 · 2 citations
    Medicine · Neuroscience · #Computer Vision and Pattern Recognition (cs.CV) #Empathy and Medical Education #FOS: Computer and information sciences #Neurology and Historical Studies
15. OMNIGUARD: An Efficient Approach for AI Safety Moderation Across Languages and Modalities
    2025/05/29 by Sahil Verma, Verma, Sahil, Keegan Hines +11 · 4 citations
    Computer Science · #Adversarial Robustness in Machine Learning
16. COBRA: COmBinatorial Retrieval Augmentation for Few-Shot Adaptation
    2024/12/23 by Arnav Das, Das, Arnav M., Gantavya Bhatt +7 · 1 citation
    Computer Science · Engineering · #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Geophysical Methods and Applications #Machine Learning (cs.LG) #Speech Recognition and Synthesis