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Learning Theory

Learning theory

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Showing 201–250 of 852 papers

TitleStatusHype
Deep Fisher Kernels - End to End Learning of the Fisher Kernel GMM Parameters—0
Deep Neural Nets as Hamiltonians—0
Deep Neural Networks for Choice Analysis: A Statistical Learning Theory Perspective—0
Deep Fictitious Play for Stochastic Differential Games—0
Deep Reinforcement Learning and the Deadly Triad—0
DePRL: Achieving Linear Convergence Speedup in Personalized Decentralized Learning with Shared Representations—0
Depth Separation with Multilayer Mean-Field Networks—0
Depth-Width Trade-offs for Neural Networks via Topological Entropy—0
Design-unbiased statistical learning in survey sampling—0
Detailed Balanced Chemical Reaction Networks as Generalized Boltzmann Machines—0
Device Sampling for Heterogeneous Federated Learning: Theory, Algorithms, and Implementation—0
Privacy of SGD under Gaussian or Heavy-Tailed Noise: Guarantees without Gradient Clipping—0
Differentiation and Specialization of Attention Heads via the Refined Local Learning Coefficient—0
Dimension-free Information Concentration via Exp-Concavity—0
A Sufficient Statistics Construction of Bayesian Nonparametric Exponential Family Conjugate Models—0
Disentangling Resilience from Robustness: Contextual Dualism, Interactionism, and Game-Theoretic Paradigms—0
Distributed Kernel Ridge Regression with Communications—0
Distributional property testing in a quantum world—0
Distribution-dependent concentration inequalities for tighter generalization bounds—0
Distribution-free Deviation Bounds and The Role of Domain Knowledge in Learning via Model Selection with Cross-validation Risk Estimation—0
Distribution free M-estimation—0
Do Deeper Convolutional Networks Perform Better?—0
Domain Generalization via Multidomain Discriminant Analysis—0
A Mathematical Theory of Learning—0
Adaptive time series forecasting with markovian variance switching—0
A Closer Look at the Learnability of Out-of-Distribution (OOD) Detection—0
1-bit Matrix Completion: PAC-Bayesian Analysis of a Variational Approximation—0
Kernel Ridge Riesz Representers: Generalization, Mis-specification, and the Counterfactual Effective Dimension—0
Dual VC Dimension Obstructs Sample Compression by Embeddings—0
Dynamical versus Bayesian Phase Transitions in a Toy Model of Superposition—0
Effective Rank and the Staircase Phenomenon: New Insights into Neural Network Training Dynamics—0
Effects of quantum resources on the statistical complexity of quantum circuits—0
Efficient and Accurate Estimation of Lipschitz Constants for Hybrid Quantum-Classical Decision Models—0
Efficient Learning for Linear Properties of Bounded-Gate Quantum Circuits—0
Efficient Learning of Linear Separators under Bounded Noise—0
Computational Complexity of Learning Neural Networks: Smoothness and Degeneracy—0
Efficient PAC Learning of Halfspaces with Constant Malicious Noise Rate—0
On the Existence of Simpler Machine Learning Models—0
DDPM Score Matching and Distribution Learning—0
Empirical Risk Minimization for Time Series: Nonparametric Performance Bounds for Prediction—0
Encoding-dependent generalization bounds for parametrized quantum circuits—0
A MapReduce based distributed SVM algorithm for binary classification—0
Data Selection for ERMs—0
Data-Driven Breakthroughs and Future Directions in AI Infrastructure: A Comprehensive Review—0
Enhancing Pattern Classification in Support Vector Machines through Matrix Formulation—0
Ensuring Learning Guarantees on Concept Drift Detection with Statistical Learning Theory—0
Error analysis of regularized least-square regression with Fredholm kernel—0
Error Exponent in Agnostic PAC Learning—0
ERUDITE: Human-in-the-Loop IoT for an Adaptive Personalized Learning System—0
A Statistical Learning Theory Framework for Supervised Pattern Discovery—0
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