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Learning Theory

Learning theory

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Showing 101–150 of 852 papers

TitleStatusHype
Convergence of Statistical Estimators via Mutual Information Bounds—0
Data-Dependent Generalization Bounds for Parameterized Quantum Models Under Noise—0
An Algorithm-Centered Approach To Model Streaming Data—0
Of Dice and Games: A Theory of Generalized Boosting—0
Effective Rank and the Staircase Phenomenon: New Insights into Neural Network Training Dynamics—0
Unified Inductive Logic: From Formal Learning to Statistical Inference to Supervised Learning—0
Geometry of fibers of the multiplication map of deep linear neural networks—0
Learned Random Label Predictions as a Neural Network Complexity Metric—0
Incomplete Multi-view Multi-label Classification via a Dual-level Contrastive Learning Framework—0
Learning Hierarchical Polynomials of Multiple Nonlinear Features with Three-Layer Networks—0
Statistical inference for quantum singular models—0
Understanding Machine Learning Paradigms through the Lens of Statistical Thermodynamics: A tutorial—0
On the Sample Complexity of One Hidden Layer Networks with Equivariance, Locality and Weight Sharing—0
Omnipredicting Single-Index Models with Multi-Index Models—0
On the Comparison between Multi-modal and Single-modal Contrastive Learning—0
Representative Social Choice: From Learning Theory to AI Alignment—0
Generation through the lens of learning theory—0
Agnostic Process Tomography—0
A Theoretical Survey on Foundation Models—0
Structure of Artificial Neural Networks -- Empirical Investigations—0
Adversarial Training Can Provably Improve Robustness: Theoretical Analysis of Feature Learning Process Under Structured Data—0
Upper Bounds for Learning in Reproducing Kernel Hilbert Spaces for Non IID Samples—0
Online Epsilon Net and Piercing Set for Geometric Concepts—0
Differentiation and Specialization of Attention Heads via the Refined Local Learning Coefficient—0
Efficient PAC Learning of Halfspaces with Constant Malicious Noise Rate—0
A multi-source data power load forecasting method using attention mechanism-based parallel cnn-gru—0
End-to-end guarantees for indirect data-driven control of bilinear systems with finite stochastic dataCode0
Bridging the Gap Between Approximation and Learning via Optimal Approximation by ReLU MLPs of Maximal Regularity—0
The Sample Complexity of Smooth Boosting and the Tightness of the Hardcore Theorem—0
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
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