Learning Theory

Bias-Variance Trade-Off in Hierarchical Probabilistic Models Using Higher-Order Feature Interactions AAAI 2019 Big Generalizations with Small Data: Exploring the Role of Training Samples in Learning Adjectives of Size EMNLP 2019 Bilinear Bandits with Low-rank Structure ICML 2019 Block Belief Propagation for Parameter Learning in Markov Random Fields AAAI 2019 Boosted Kernel Ridge Regression: Optimal Learning Rates and Early Stopping JMLR 2019 Can SGD Learn Recurrent Neural Networks with Provable Generalization? NeurIPS 2019 Capacity Bounded Differential Privacy NeurIPS 2019 Capacity Control of ReLU Neural Networks by Basis-Path Norm AAAI 2019 CapsAndRuns: An Improved Method for Approximately Optimal Algorithm Configuration ICML 2019 Categorized Bandits NeurIPS 2019 Cautious Regret Minimization: Online Optimization with Long-Term Budget Constraints ICML 2019 Censored Semi-Bandits: A Framework for Resource Allocation with Censored Feedback NeurIPS 2019 Certified Adversarial Robustness with Additive Noise NeurIPS 2019 Certifying the True Error: Machine Learning in Coq with Verified Generalization Guarantees AAAI 2019 Characterizing the Sample Complexity of Pure Private Learners JMLR 2019 Characterizing Well-Behaved vs. Pathological Deep Neural Networks ICML 2019 Classification using margin pursuit AISTATS 2019 Classification with unknown class-conditional label noise on non-compact feature spaces COLT 2019 CNNs found to jump around more skillfully than RNNs: Compositional Generalization in Seq2seq Convolutional Networks ACL 2019 Combinatorial Bandits with Relative Feedback NeurIPS 2019 Combining Online Learning Guarantees COLT 2019 Communication and Memory Efficient Testing of Discrete Distributions COLT 2019 Comparing Sample-Wise Learnability across Deep Neural Network Models AAAI 2019 Complexity of Linear Regions in Deep Networks ICML 2019 Computational Limitations in Robust Classification and Win-Win Results COLT 2019