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vc dimension

108 papers

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Also known as

VC-DIMENSION VCDIM

Co-occurring keywords

sample complexity (1169) pac learning (283) generalization bound (652) learning theory (519) concept class (38) differential privacy (1016) sample compression (32) empirical risk minimization (352) hypothesis class (28) support vector machine (978)

Papers

Proper Learning, Helly Number, and an Optimal SVM Bound COLT 2020
PAC learning with stable and private predictions COLT 2020
Open Problem: Information Complexity of VC Learning COLT 2020
Reasoning About Generalization via Conditional Mutual Information COLT 2020
Quantum Boosting ICML 2020
Towards a Combinatorial Characterization of Bounded-Memory Learning NIPS 2020
Smoothed Analysis of Online and Differentially Private Learning NIPS 2020
Model Selection via the VC Dimension JMLR 2019
An Approach to One-Bit Compressed Sensing Based on Probably Approximately Correct Learning Theory JMLR 2019
Characterizing the Sample Complexity of Pure Private Learners JMLR 2019
Limits of Private Learning with Access to Public Data NIPS 2019
Graph-based Discriminators: Sample Complexity and Expressiveness NIPS 2019
VC Classes are Adversarially Robustly Learnable, but Only Improperly COLT 2019
Preference-Based Batch and Sequential Teaching: Towards a Unified View of Models NIPS 2019
Precision-Recall versus Accuracy and the Role of Large Data Sets AAAI 2019
Small ReLU networks are powerful memorizers: a tight analysis of memorization capacity NIPS 2019
A Sharp Lower Bound for Agnostic Learning with Sample Compression Schemes ALT 2019
Learning from Weakly Dependent Data under Dobrushin’s Condition COLT 2019
Optimal Quantum Sample Complexity of Learning Algorithms JMLR 2018
Chaining Mutual Information and Tightening Generalization Bounds NIPS 2018
PAC-learning in the presence of adversaries NIPS 2018
A Direct Sum Result for the Information Complexity of Learning COLT 2018
Model-Agnostic Private Learning NIPS 2018
Information Theoretic Guarantees for Empirical Risk Minimization with Applications to Model Selection and Large-Scale Optimization ICML 2018
Tight Bounds for Collaborative PAC Learning via Multiplicative Weights NIPS 2018