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PAC learning

Probably Approximately Correct (PAC) learning analyzes machine learning mathematically using probability bounds.

Papers

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Showing 1–50 of 289 papers

TitleStatusHype
Prospective Learning: Learning for a Dynamic FutureCode1
Lean Formalization of Generalization Error Bound by Rademacher ComplexityCode1
VICE: Variational Interpretable Concept EmbeddingsCode1
Planted Dense Subgraphs in Dense Random Graphs Can Be Recovered using Graph-based Machine LearningCode0
Towards a theory of model distillationCode0
SLIP: Learning to Predict in Unknown Dynamical Systems with Long-Term MemoryCode0
Privacy Induces Robustness: Information-Computation Gaps and Sparse Mean EstimationCode0
Understanding Boolean Function Learnability on Deep Neural Networks: PAC Learning Meets Neurosymbolic ModelsCode0
SAT-Based PAC Learning of Description Logic ConceptsCode0
Introduction to Machine Learning: Class Notes 67577Code0
Regression EquilibriumCode0
Optimistic Rates for Learning from Label ProportionsCode0
Quantum Boosting using Domain-Partitioning HypothesesCode0
Agnostic Learning of a Single Neuron with Gradient Descent—0
Agnostic Learning by Refuting—0
Active-learning-based non-intrusive Model Order Reduction—0
Adversarial Robustness: What fools you makes you stronger—0
Adversarial Online Learning with Changing Action Sets: Efficient Algorithms with Approximate Regret Bounds—0
A Computational Separation between Private Learning and Online Learning—0
A Characterization of Semi-Supervised Adversarially-Robust PAC Learnability—0
A Linear Theory of Multi-Winner Voting—0
Algorithms and SQ Lower Bounds for Robustly Learning Real-valued Multi-index Models—0
An Active Learning Framework for Constructing High-fidelity Mobility Maps—0
Analyzing Robustness of Angluin's L* Algorithm in Presence of Noise—0
An Approach to One-Bit Compressed Sensing Based on Probably Approximately Correct Learning Theory—0
A Near-optimal Algorithm for Learning Margin Halfspaces with Massart Noise—0
An Optimal Elimination Algorithm for Learning a Best Arm—0
A packing lemma for VCN_k-dimension and learning high-dimensional data—0
A PAC Learning Algorithm for LTL and Omega-regular Objectives in MDPs—0
A Parameterized Theory of PAC Learning—0
Adversarially Robust Learning with Tolerance—0
Algorithms and SQ Lower Bounds for PAC Learning One-Hidden-Layer ReLU Networks—0
A learning problem that is independent of the set theory ZFC axioms—0
Adversarial Laws of Large Numbers and Optimal Regret in Online Classification—0
A Complete Characterization of Statistical Query Learning with Applications to Evolvability—0
Bagging is an Optimal PAC Learner—0
A Unified Framework for Approximating and Clustering Data—0
AI Reasoning Systems: PAC and Applied Methods—0
Bandit Multiclass List Classification—0
Best-item Learning in Random Utility Models with Subset Choices—0
Bézier Flow: a Surface-wise Gradient Descent Method for Multi-objective Optimization—0
Broadly Applicable Targeted Data Sample Omission Attacks—0
Can SGD Learn Recurrent Neural Networks with Provable Generalization?—0
Characterizing the Sample Complexity of Private Learners—0
Clifford Circuits can be Properly PAC Learned if and only if RP=NP—0
Closure Properties for Private Classification and Online Prediction—0
Collaborative Learning with Different Labeling Functions—0
Collaborative PAC Learning—0
Communication-Aware Collaborative Learning—0
Attribute-Efficient PAC Learning of Sparse Halfspaces with Constant Malicious Noise Rate—0
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