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Learning Theory

Learning theory

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Showing 651–700 of 852 papers

TitleStatusHype
Causal RegularizationCode0
Symphony of high-dimensional brain—0
Learning from weakly dependent data under Dobrushin's condition—0
Quadratic Suffices for Over-parametrization via Matrix Chernoff Bound—0
Graph-based Discriminators: Sample Complexity and Expressiveness—0
On the Generalization Gap in Reparameterizable Reinforcement Learning—0
Understanding the Behaviour of the Empirical Cross-Entropy Beyond the Training Distribution—0
Empirical Risk Minimization in the Interpolating Regime with Application to Neural Network Learning—0
Disagreement-based Active Learning in Online Settings—0
The Landscape of the Planted Clique Problem: Dense subgraphs and the Overlap Gap Property—0
Approximation in L^p(μ) with deep ReLU neural networks—0
Deep Fictitious Play for Stochastic Differential Games—0
Recovering the Lowest Layer of Deep Networks with High Threshold Activations—0
A Brain-inspired Algorithm for Training Highly Sparse Neural NetworksCode0
A nonasymptotic law of iterated logarithm for general M-estimators—0
Is Deeper Better only when Shallow is Good?Code0
Improving Generalization of Deep Networks for Inverse Reconstruction of Image SequencesCode0
Fast Approximation of Frequent k-mers and Applications to Metagenomics—0
Integrated analysis of the urban water-electricity demand nexus in the Midwestern United States—0
Analyzing Data Selection Techniques with Tools from the Theory of Information Losses—0
Generalisation in fully-connected neural networks for time series forecasting—0
Scaling Limits of Wide Neural Networks with Weight Sharing: Gaussian Process Behavior, Gradient Independence, and Neural Tangent Kernel Derivation—0
Learning Theory and Support Vector Machines - a primer—0
Fast Hyperparameter Tuning using Bayesian Optimization with Directional Derivatives—0
On Generalization Error Bounds of Noisy Gradient Methods for Non-Convex Learning—0
Distributional property testing in a quantum world—0
Learning Schatten--von Neumann Operators—0
Robust Learning from Untrusted SourcesCode0
Anomaly detecting and ranking of the cloud computing platform by multi-view learning—0
Optimality Implies Kernel Sum Classifiers are Statistically Efficient—0
Tighter Problem-Dependent Regret Bounds in Reinforcement Learning without Domain Knowledge using Value Function Bounds—0
Max-Diversity Distributed Learning: Theory and Algorithms—0
Deep Reinforcement Learning and the Deadly Triad—0
Machine Learning of coarse-grained Molecular Dynamics Force Fields—0
Practical methods for graph two-sample testingCode0
The SWAG Algorithm; a Mathematical Approach that Outperforms Traditional Deep Learning. Theory and ImplementationCode0
An Algorithmic Perspective on Imitation Learning—0
Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers—0
A Bayesian Perspective of Statistical Machine Learning for Big DataCode0
An Optimal Transport View on Generalization—0
Piecewise Strong Convexity of Neural Networks—0
Improving Generalization of Sequence Encoder-Decoder Networks for Inverse Imaging of Cardiac Transmembrane Potential—0
Generalization Properties of hyper-RKHS and its Applications—0
When is there a Representer Theorem? Reflexive Banach spaces—0
Unsupervised parameter selection for denoising with the elastic net—0
Exponential inequalities for nonstationary Markov Chains—0
Spectral Pruning: Compressing Deep Neural Networks via Spectral Analysis and its Generalization Error—0
The Mismatch Principle: The Generalized Lasso Under Large Model Uncertainties—0
Importance of the Mathematical Foundations of Machine Learning Methods for Scientific and Engineering Applications—0
A Temporal Difference Reinforcement Learning Theory of Emotion: unifying emotion, cognition and adaptive behavior—0
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