SOTAVerified

Learning Theory

Learning theory

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 251–300 of 852 papers

TitleStatusHype
Data-Driven Breakthroughs and Future Directions in AI Infrastructure: A Comprehensive Review—0
A Statistical Learning Theory Framework for Supervised Pattern Discovery—0
Evaluated CMI Bounds for Meta Learning: Tightness and Expressiveness—0
Evidence on the Regularisation Properties of Maximum-Entropy Reinforcement Learning—0
A Machine Learning Theory Perspective on Strategic Litigation—0
Adaptive Stopping Rule for Kernel-based Gradient Descent Algorithms—0
Data-Dependent Generalization Bounds for Parameterized Quantum Models Under Noise—0
Curriculum Learning by Transfer Learning: Theory and Experiments with Deep Networks—0
A Statistical Learning Based System for Fake Website Detection—0
Credit Assignment: Challenges and Opportunities in Developing Human-like AI Agents—0
Credal Learning Theory—0
Associative Memory in Iterated Overparameterized Sigmoid Autoencoders—0
A Linear Theory of Multi-Winner Voting—0
Contextual Search in the Presence of Adversarial Corruptions—0
Corpus-Based Computation of Reverse Associations—0
Optimal Approximations Made Easy—0
Coordination of Damping Controllers: A Novel Data-Informed Approach for Adaptability—0
Convergence Rates for Learning Linear Operators from Noisy Data—0
A Simple and General Debiased Machine Learning Theorem with Finite Sample Guarantees—0
Algorithmic statistics, prediction and machine learning—0
Adaptive Parameter Selection for Kernel Ridge Regression—0
A Characterization of Multiclass Learnability—0
Convergence of Statistical Estimators via Mutual Information Bounds—0
Convergence of Gradient EM on Multi-component Mixture of Gaussians—0
Convergence Analysis of Gradient EM for Multi-component Gaussian Mixture—0
Contrastive Learning as Kernel Approximation—0
A Revision of Neural Tangent Kernel-based Approaches for Neural Networks—0
Algorithmic Stability and Uniform Generalization—0
Contrasting random and learned features in deep Bayesian linear regression—0
Barren Plateaus in Variational Quantum Computing—0
Continuous Homeostatic Reinforcement Learning for Self-Regulated Autonomous Agents—0
Continuity of Generalized Entropy and Statistical Learning—0
A Reinforcement Learning Theory for Homeostatic Regulation—0
Algorithmic learning of probability distributions from random data in the limit—0
Constructive Large Language Models Alignment with Diverse Feedback—0
Constrained Learning with Non-Convex Losses—0
Consistency Analysis for Binary Classification Revisited—0
A Learning Theory in Linear Systems under Compositional Models—0
Conformal Shield: A Novel Adversarial Attack Detection Framework for Automatic Modulation Classification—0
Conformal Predictions for Probabilistically Robust Scalable Machine Learning Classification—0
Approximation in L^p(μ) with deep ReLU neural networks—0
Computing the Shattering Coefficient of Supervised Learning Algorithms—0
A Domain-Knowledge-Aided Deep Reinforcement Learning Approach for Flight Control Design—0
Approximability and Generalisation—0
A learning theory for quantum photonic processors and beyond—0
Adaptive Frequency Band Selection for Accurate and Fast Positioning utilizing SOPs—0
A Characterization of List Learnability—0
A Bayesian Approach to (Online) Transfer Learning: Theory and Algorithms—0
Computable learning of natural hypothesis classes—0
Computabilities of Validity and Satisfiability in Probability Logics over Finite and Countable Models—0
Show:102550
← PrevPage 6 of 18Next →

No leaderboard results yet.