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Learning Theory

Learning theory

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Showing 451–500 of 852 papers

TitleStatusHype
Under-bagging Nearest Neighbors for Imbalanced Classification—0
Convergence Rates for Learning Linear Operators from Noisy Data—0
Adversarial Robustness of Deep Learning: Theory, Algorithms, and Applications—0
Primal and Dual Combinatorial Dimensions—0
Introduction to Quantum Reinforcement Learning: Theory and PennyLane-based Implementation—0
Empirical Risk Minimization for Time Series: Nonparametric Performance Bounds for Prediction—0
Unified Regularity Measures for Sample-wise Learning and Generalization—0
Path classification by stochastic linear recurrent neural networks—0
Characterizing the Generalization Error of Gibbs Algorithm with Symmetrized KL information—0
Accelerating Federated Edge Learning via Optimized Probabilistic Device Scheduling—0
Towards Explaining Adversarial Examples Phenomenon in Artificial Neural Networks—0
An induction proof of the backpropagation algorithm in matrix notation—0
Improved Learning Rates for Stochastic Optimization: Two Theoretical Viewpoints—0
Continuous vs. Discrete Optimization of Deep Neural NetworksCode0
A Framework for Machine Learning of Model Error in Dynamical SystemsCode0
On the Variance of the Fisher Information for Deep Learning—0
Learning an Explicit Hyperparameter Prediction Function Conditioned on TasksCode0
The Last-Iterate Convergence Rate of Optimistic Mirror Descent in Stochastic Variational Inequalities—0
A Systems Theory of Transfer Learning—0
Learning Bounds for Open-Set LearningCode1
f-Domain-Adversarial Learning: Theory and AlgorithmsCode1
The Principles of Deep Learning Theory—0
On Anytime Learning at MacroscaleCode0
Solving PDEs on Unknown Manifolds with Machine LearningCode0
GBHT: Gradient Boosting Histogram Transform for Density Estimation—0
Fractal Structure and Generalization Properties of Stochastic Optimization Algorithms—0
Encoding-dependent generalization bounds for parametrized quantum circuits—0
Redundant representations help generalization in wide neural networksCode0
Reverse Engineering the Neural Tangent KernelCode0
Model Zoo: A Growing "Brain" That Learns ContinuallyCode1
Towards an Understanding of Benign Overfitting in Neural Networks—0
Robust Model Selection and Nearly-Proper Learning for GMMs—0
Learning Curves for SGD on Structured FeaturesCode0
A Survey on Optimal Transport for Machine Learning: Theory and Applications—0
Optimization Variance: Exploring Generalization Properties of DNNsCode0
Post-mortem on a deep learning contest: a Simpson's paradox and the complementary roles of scale metrics versus shape metrics—0
A Simple and General Debiased Machine Learning Theorem with Finite Sample Guarantees—0
Tesseract: Tensorised Actors for Multi-Agent Reinforcement Learning—0
Learning Union of Integer Hypercubes with Queries (Technical Report)—0
Yes We Care! -- Certification for Machine Learning Methods through the Care Label Framework—0
The Modern Mathematics of Deep Learning—0
Quantum Machine Learning For Classical Data—0
Regret-Optimal LQR Control—0
Robust Kernel-based Distribution Regression—0
Minimax Kernel Machine Learning for a Class of Doubly Robust Functionals with Application to Proximal Causal InferenceCode0
Learning Description Logic Ontologies. Five Approaches. Where Do They Stand?—0
Why is AI hard and Physics simple?—0
Understanding the role of importance weighting for deep learning—0
Leaky Nets: Recovering Embedded Neural Network Models and Inputs through Simple Power and Timing Side-Channels -- Attacks and Defenses—0
On the Complexity of Learning Description Logic Ontologies—0
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