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Learning Theory

Learning theory

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Showing 151–200 of 852 papers

TitleStatusHype
Improving Noise Robustness through Abstractions and its Impact on Machine Learning—0
Probability Distribution Learning and Its Application in Deep Learning—0
CMAR-Net: Accurate Cross-Modal 3D SAR Reconstruction of Vehicle Targets with Sparse-Aspect Multi-Baseline Data—0
On the Limitations of Fractal Dimension as a Measure of GeneralizationCode0
Coded Computing for Resilient Distributed Computing: A Learning-Theoretic Framework—0
Review and Prospect of Algebraic Research in Equivalent Framework between Statistical Mechanics and Machine Learning Theory—0
Weak Robust Compatibility Between Learning Algorithms and Counterfactual Explanation Generation Algorithms—0
Scaling Laws for the Value of Individual Data Points in Machine LearningCode0
Occam Gradient DescentCode0
Beyond Discrepancy: A Closer Look at the Theory of Distribution Shift—0
MODL: Multilearner Online Deep LearningCode0
Unveiling the Cycloid Trajectory of EM Iterations in Mixed Linear RegressionCode0
Dual VC Dimension Obstructs Sample Compression by Embeddings—0
Is Algorithmic Stability Testable? A Unified Framework under Computational Constraints—0
A Contextual Online Learning Theory of Brokerage—0
Learning Regularities from Data using Spiking Functions: A Theory—0
Preparing for Black Swans: The Antifragility Imperative for Machine Learning—0
Using Degeneracy in the Loss Landscape for Mechanistic Interpretability—0
Nonparametric Control Koopman Operators—0
Robust Semi-supervised Learning by Wisely Leveraging Open-set Data—0
Is Transductive Learning Equivalent to PAC Learning?—0
Data-Error Scaling in Machine Learning on Natural Discrete Combinatorial Mutation-prone Sets: Case Studies on Peptides and Small MoleculesCode0
Towards a Formal Creativity Theory: Preliminary results in Novelty and Transformativeness—0
Position: Understanding LLMs Requires More Than Statistical GeneralizationCode0
Error Exponent in Agnostic PAC Learning—0
Barren Plateaus in Variational Quantum Computing—0
Research on geometric figure classification algorithm based on Deep Learning—0
Data-Driven Performance Guarantees for Classical and Learned OptimizersCode0
Generalization Error Bounds for Learning under Censored Feedback—0
A neural network account to Kant's philosophical aesthetics—0
On the Learnability of Out-of-distribution Detection—0
Bayesian Inference for Consistent Predictions in Overparameterized Nonlinear RegressionCode0
Statistical Mechanics and Artificial Neural Networks: Principles, Models, and Applications—0
Causal-StoNet: Causal Inference for High-Dimensional Complex DataCode0
Generalization Error Analysis for Sparse Mixture-of-Experts: A Preliminary Study—0
CODA: A COst-efficient Test-time Domain Adaptation Mechanism for HAR—0
Robust NAS under adversarial training: benchmark, theory, and beyond—0
Conformal Predictions for Probabilistically Robust Scalable Machine Learning Classification—0
Majority-of-Three: The Simplest Optimal Learner?—0
On the Diminishing Returns of Width for Continual LearningCode0
Disentangling Resilience from Robustness: Contextual Dualism, Interactionism, and Game-Theoretic Paradigms—0
Privacy of SGD under Gaussian or Heavy-Tailed Noise: Guarantees without Gradient Clipping—0
Lotka-Volterra Model with Mutations and Generative Adversarial Networks—0
Conformal Shield: A Novel Adversarial Attack Detection Framework for Automatic Modulation Classification—0
Shapley Value Based Multi-Agent Reinforcement Learning: Theory, Method and Its Application to Energy Network—0
Adaptive time series forecasting with markovian variance switching—0
Generalising realisability in statistical learning theory under epistemic uncertainty—0
A unified framework of non-local parametric methods for image denoising—0
The Dimension of Self-Directed Learning—0
Rigor with Machine Learning from Field Theory to the Poincaré Conjecture—0
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