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Learning Theory

Learning theory

Papers

Showing 601–650 of 852 papers

TitleStatusHype
An Active Learning Framework for Constructing High-fidelity Mobility Maps—0
Better Depth-Width Trade-offs for Neural Networks through the lens of Dynamical Systems—0
Contextual Search in the Presence of Adversarial Corruptions—0
A Generalized Neural Tangent Kernel Analysis for Two-layer Neural Networks—0
Learning CHARME models with neural networksCode0
On Learnability with Computable Learners—0
Statistical Limits of Supervised Quantum Learning—0
Recursion, evolution and conscious self—0
Adaptive Stopping Rule for Kernel-based Gradient Descent Algorithms—0
Restarted Bayesian Online Change-point Detector achieves Optimal Detection DelayCode0
PAC Confidence Sets for Deep Neural Networks via Calibrated PredictionCode1
TentacleNet: A Pseudo-Ensemble Template for Accurate Binary Convolutional Neural NetworksCode0
Optimization for deep learning: theory and algorithms—0
Σ-net: Systematic Evaluation of Iterative Deep Neural Networks for Fast Parallel MR Image ReconstructionCode0
Realization of spatial sparseness by deep ReLU nets with massive data—0
Rademacher complexity and spin glasses: A link between the replica and statistical theories of learning—0
Generalization Error Bounds Via Rényi-, f-Divergences and Maximal Leakage—0
Information-Theoretic Local Minima Characterization and RegularizationCode0
Coarse-Refinement Dilemma: On Generalization Bounds for Data Clustering—0
On the Complexity of Labeled Datasets—0
One-shot learning and behavioral eligibility traces in sequential decision making—0
Machine Intelligence at the Edge with Learning Centric Power Allocation—0
Learning Internal Representations (PhD Thesis)—0
On-Device Machine Learning: An Algorithms and Learning Theory Perspective—0
A Formal Proof of PAC Learnability for Decision Stumps—0
Risk bounds for reservoir computing—0
Fast classification rates without standard margin assumptions—0
Robust Model Predictive Shielding for Safe Reinforcement Learning with Stochastic Dynamics—0
Compressive Learning for Semi-Parametric Models—0
Building Efficient CNNs Using Depthwise Convolutional Eigen-Filters (DeCEF)—0
Sharper bounds for uniformly stable algorithms—0
Partial differential equation regularization for supervised machine learning—0
Siamese Networks: The Tale of Two Manifolds—0
Truth or Backpropaganda? An Empirical Investigation of Deep Learning TheoryCode0
Knowledge Graph Embedding: A Probabilistic Perspective and Generalization Bounds—0
The Frechet Distance of training and test distribution predicts the generalization gap—0
ShardNet: One Filter Set to Rule Them All—0
Compression based bound for non-compressed network: unified generalization error analysis of large compressible deep neural network—0
Deep Neural Networks for Choice Analysis: A Statistical Learning Theory Perspective—0
On the Hardness of Robust Classification—0
Non-Bayesian Social Learning with Uncertain Models—0
Subjectivity Learning Theory towards Artificial General Intelligence—0
McDiarmid-Type Inequalities for Graph-Dependent Variables and Stability Bounds—0
Free resolutions of function classes via order complexes—0
Deep Learning Theory Review: An Optimal Control and Dynamical Systems PerspectiveCode0
Lecture Notes: Selected topics on robust statistical learning theory—0
A Domain-Knowledge-Aided Deep Reinforcement Learning Approach for Flight Control Design—0
On the Existence of Simpler Machine Learning Models—0
Domain Generalization via Multidomain Discriminant Analysis—0
Minimal Sample Subspace Learning: Theory and Algorithms—0
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