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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
Lean Formalization of Generalization Error Bound by Rademacher ComplexityCode1
Prospective Learning: Learning for a Dynamic FutureCode1
VICE: Variational Interpretable Concept EmbeddingsCode1
A Characterization of Semi-Supervised Adversarially-Robust PAC Learnability—0
A Computational Separation between Private Learning and Online Learning—0
Active-learning-based non-intrusive Model Order Reduction—0
A Complete Characterization of Statistical Query Learning with Applications to Evolvability—0
A Distributional-Lifting Theorem for PAC Learning—0
Adversarial Laws of Large Numbers and Optimal Regret in Online Classification—0
Adversarially Robust Learning with Tolerance—0
Adversarial Online Learning with Changing Action Sets: Efficient Algorithms with Approximate Regret Bounds—0
Adversarial Robustness: What fools you makes you stronger—0
Agnostic Learning by Refuting—0
Agnostic Learning of a Single Neuron with Gradient Descent—0
Agnostic PAC Learning of k-juntas Using L2-Polynomial Regression—0
A Practical Theory of Generalization in Selectivity Learning—0
Agnostic Smoothed Online Learning—0
AI Reasoning Systems: PAC and Applied Methods—0
A learning problem that is independent of the set theory ZFC axioms—0
Algorithms and SQ Lower Bounds for PAC Learning One-Hidden-Layer ReLU Networks—0
Algorithms and SQ Lower Bounds for Robustly Learning Real-valued Multi-index Models—0
A Linear Theory of Multi-Winner Voting—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
A Polynomial Time Algorithm for Learning Halfspaces with Tsybakov Noise—0
Agnostic Multi-Group Active Learning—0
A Strongly Polynomial Algorithm for Approximate Forster Transforms and its Application to Halfspace Learning—0
A Theory of PAC Learnability of Partial Concept Classes—0
Attribute-Efficient PAC Learning of Low-Degree Polynomial Threshold Functions with Nasty Noise—0
Attribute-Efficient PAC Learning of Sparse Halfspaces with Constant Malicious Noise Rate—0
A Unified Framework for Approximating and Clustering Data—0
Bagging is an Optimal PAC Learner—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
Active Learning for Contextual Search with Binary Feedbacks—0
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