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Learning Theory

Learning theory

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Showing 451–500 of 852 papers

TitleStatusHype
Intrinisic Gradient Compression for Federated Learning—0
Intrinsic Gradient Compression for Scalable and Efficient Federated Learning—0
Introduction to Quantum Reinforcement Learning: Theory and PennyLane-based Implementation—0
Is Algorithmic Stability Testable? A Unified Framework under Computational Constraints—0
Is Out-of-Distribution Detection Learnable?—0
Is Transductive Learning Equivalent to PAC Learning?—0
Just Mix Once: Worst-group Generalization by Group Interpolation—0
Kernel-Based Distributed Q-Learning: A Scalable Reinforcement Learning Approach for Dynamic Treatment Regimes—0
Kernel Methods for Linear Discrete-Time Equations—0
Knowledge Distillation: Bad Models Can Be Good Role Models—0
Knowledge Graph Embedding: A Probabilistic Perspective and Generalization Bounds—0
Labeled sample compression schemes for complexes of oriented matroids—0
Large Language Models at Work in China's Labor Market—0
Leaky Nets: Recovering Embedded Neural Network Models and Inputs through Simple Power and Timing Side-Channels -- Attacks and Defenses—0
Transductive Learning Is Compact—0
Learned Random Label Predictions as a Neural Network Complexity Metric—0
Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers—0
Learning-Based Compressive MRI—0
Learning circuits with few negations—0
Learning curves for deep structured Gaussian feature models—0
Learning Description Logic Ontologies. Five Approaches. Where Do They Stand?—0
Learning deterministic hydrodynamic equations from stochastic active particle dynamics—0
Learning Distributions by Generative Adversarial Networks: Approximation and Generalization—0
Learning DNF Expressions from Fourier Spectrum—0
Learning DNF through Generalized Fourier Representations—0
Learning from many trajectories—0
Learning from weakly dependent data under Dobrushin's condition—0
Learning Guarantee of Reward Modeling Using Deep Neural Networks—0
Learning Hierarchical Polynomials of Multiple Nonlinear Features with Three-Layer Networks—0
Markets with Heterogeneous Agents: Dynamics and Survival of Bayesian vs. No-Regret Learners—0
Learning in Observable POMDPs, without Computationally Intractable Oracles—0
Learning Internal Representations (PhD Thesis)—0
Learning Losses for Strategic Classification—0
Learning Mixtures of Gaussians in High Dimensions—0
Learning Neural Networks with Two Nonlinear Layers in Polynomial Time—0
Learning opacity in Stratal Maximum Entropy Grammar—0
Learning Possibilistic Logic Theories from Default Rules—0
Learning Prediction Intervals for Regression: Generalization and Calibration—0
Learning Probability Measures with respect to Optimal Transport Metrics—0
Learning rates of l^q coefficient regularization learning with Gaussian kernel—0
Learning Regularities from Data using Spiking Functions: A Theory—0
New Guarantees for Learning Revenue Maximizing Menus of Lotteries and Two-Part Tariffs—0
Learning Schatten--von Neumann Operators—0
Learning stability of partially observed switched linear systems—0
Learning sum of diverse features: computational hardness and efficient gradient-based training for ridge combinations—0
Learning Temporal Invariance in Android Malware Detectors—0
Learning the Integral Quadratic Constraints on Plant-Model Mismatch—0
Learning-Theoretic Foundations of Algorithm Configuration for Combinatorial Partitioning Problems—0
Learning Theory and Algorithms for Forecasting Non-stationary Time Series—0
Learning Theory and Algorithms for Revenue Optimization in Second-Price Auctions with Reserve—0
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