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Learning Theory

Learning theory

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Showing 101–150 of 852 papers

TitleStatusHype
NGD converges to less degenerate solutions than SGDCode0
Fairness, Accuracy, and Unreliable Data—0
Lecture Notes on Linear Neural Networks: A Tale of Optimization and Generalization in Deep Learning—0
Transformers are Minimax Optimal Nonparametric In-Context Learners—0
Efficient Learning for Linear Properties of Bounded-Gate Quantum Circuits—0
Deep Learning with CNNs: A Compact Holistic Tutorial with Focus on Supervised Regression (Preprint)Code0
Graph Classification via Reference Distribution Learning: Theory and Practice—0
Revisiting Agnostic PAC Learning—0
Mathematical theory of deep learning—0
Which distribution were you sampled from? Towards a more tangible conception of data—0
Computable learning of natural hypothesis classes—0
Inferring Ingrained Remote Information in AC Power Flows Using Neuromorphic Modality Regime—0
Quantum Maximum Entropy Inference and Hamiltonian Learning—0
Learning Confidence Bounds for Classification with Imbalanced DataCode0
Topological Generalization Bounds for Discrete-Time Stochastic Optimization Algorithms—0
10 Years of Fair Representations: Challenges and Opportunities—0
Foundations and Frontiers of Graph Learning Theory—0
Present and Future of AI in Renewable Energy Domain : A Comprehensive Survey—0
A General Control-Theoretic Approach for Reinforcement Learning: Theory and Algorithms—0
Learning sum of diverse features: computational hardness and efficient gradient-based training for ridge combinations—0
How Out-of-Distribution Detection Learning Theory Enhances Transformer: Learnability and Reliability—0
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
Occam Gradient DescentCode0
Scaling Laws for the Value of Individual Data Points in Machine LearningCode0
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
Barren Plateaus in Variational Quantum Computing—0
Error Exponent in Agnostic PAC Learning—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
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