SOTAVerified

PAC learning

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

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 151–200 of 289 papers

TitleStatusHype
Quantum Boosting using Domain-Partitioning HypothesesCode0
Active Learning for Contextual Search with Binary Feedbacks—0
Towards a theory of out-of-distribution learning—0
Learning the hypotheses space from data through a U-curve algorithm—0
Learning General Halfspaces with General Massart Noise under the Gaussian Distribution—0
Is Nash Equilibrium Approximator Learnable?—0
Statistically Near-Optimal Hypothesis Selection—0
On the Power of Differentiable Learning versus PAC and SQ Learning—0
Multiclass versus Binary Differentially Private PAC Learning—0
A Theory of PAC Learnability of Partial Concept Classes—0
Forster Decomposition and Learning Halfspaces with Noise—0
Semi-verified PAC Learning from the Crowd—0
Supervising the Transfer of Reasoning Patterns in VQA—0
Multi-group Agnostic PAC Learnability—0
Incentive-aware PAC learning—0
Learning and Certification under Instance-targeted Poisoning—0
Broadly Applicable Targeted Data Sample Omission Attacks—0
Symbolic Abstractions From Data: A PAC Learning Approach—0
PAC-learning gains of Turing machines over circuits and neural networks—0
Robust learning under clean-label attack—0
Private learning implies quantum stability—0
Sample-Optimal PAC Learning of Halfspaces with Malicious Noise—0
On Agnostic PAC Learning using L_2-polynomial Regression and Fourier-based Algorithms—0
Fairness-Aware PAC Learning from Corrupted Data—0
Adversarial Robustness: What fools you makes you stronger—0
On the Hardness of PAC-learning Stabilizer States with Noise—0
Adversarial Laws of Large Numbers and Optimal Regret in Online Classification—0
From Local Pseudorandom Generators to Hardness of Learning—0
The Price is (Probably) Right: Learning Market Equilibria from Samples—0
Communication-Aware Collaborative Learning—0
Near-Optimal Statistical Query Hardness of Learning Halfspaces with Massart Noise—0
Small Covers for Near-Zero Sets of Polynomials and Learning Latent Variable Models—0
Sample-efficient proper PAC learning with approximate differential privacy—0
VC Dimension and Distribution-Free Sample-Based Testing—0
PAC-Learning for Strategic Classification—0
Towards a Combinatorial Characterization of Bounded-Memory Learning—0
Efficient PAC Learning from the Crowd with Pairwise Comparisons—0
Reducing Adversarially Robust Learning to Non-Robust PAC Learning—0
Learning, compression, and leakage: Minimising classification error via meta-universal compression principles—0
SLIP: Learning to Predict in Unknown Dynamical Systems with Long-Term MemoryCode0
A Polynomial Time Algorithm for Learning Halfspaces with Tsybakov Noise—0
Understanding Boolean Function Learnability on Deep Neural Networks: PAC Learning Meets Neurosymbolic ModelsCode0
Learning from Mixtures of Private and Public Populations—0
A Computational Separation between Private Learning and Online Learning—0
Algorithms and SQ Lower Bounds for PAC Learning One-Hidden-Layer ReLU Networks—0
An Optimal Elimination Algorithm for Learning a Best Arm—0
Learning Halfspaces with Tsybakov Noise—0
List Learning with Attribute Noise—0
Faster PAC Learning and Smaller Coresets via Smoothed Analysis—0
Probably Approximately Correct Constrained Learning—0
Show:102550
← PrevPage 4 of 6Next →

No leaderboard results yet.