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Learning Theory

Learning theory

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Showing 401–450 of 852 papers

TitleStatusHype
Information-Theoretic Analysis of Minimax Excess Risk—0
Artificial Intelligence and Spontaneous Collusion—0
Minimax Regret Optimization for Robust Machine Learning under Distribution Shift—0
Trust in AI: Interpretability is not necessary or sufficient, while black-box interaction is necessary and sufficient—0
Deep Learning in Random Neural Fields: Numerical Experiments via Neural Tangent KernelCode0
Smoothed Online Learning is as Easy as Statistical Learning—0
The no-free-lunch theorems of supervised learning—0
Interplay between depth of neural networks and locality of target functions—0
Limitation of Characterizing Implicit Regularization by Data-independent Functions—0
Universal Online Learning with Unbounded Losses: Memory Is All You Need—0
Learning deterministic hydrodynamic equations from stochastic active particle dynamics—0
Understanding Few-Shot Multi-Task Representation Learning Theory—0
Deep Learning Optimization Theory - Trajectory Analysis of Gradient Descent—0
Universal Online Learning: an Optimistically Universal Learning Rule—0
On generalization bounds for deep networks based on loss surface implicit regularizationCode0
Formal models of memory based on temporally-varying representations—0
Envisioning Future Deep Learning Theories: Some Basic Concepts and Characteristics—0
A cognitively driven weighted-entropy model for embedding semantic categories in hyperbolic geometry—0
Regularized Modal Regression on Markov-dependent Observations: A Theoretical Assessment—0
Learning Theory Can (Sometimes) Explain Generalisation in Graph Neural Networks—0
Intrinisic Gradient Compression for Federated Learning—0
Black-box tests for algorithmic stability—0
Mesarovician Abstract Learning Systems—0
Improved Fine-Tuning by Better Leveraging Pre-Training Data—0
Uniform Brackets, Containers, and Combinatorial Macbeath Regions—0
SpeedyIBL: A Comprehensive, Precise, and Fast Implementation of Instance-Based Learning TheoryCode0
Realizable Learning is All You Need—0
Provably efficient, succinct, and precise explanations—0
Labeled sample compression schemes for complexes of oriented matroids—0
Latent Equilibrium: A unified learning theory for arbitrarily fast computation with arbitrarily slow neuronsCode0
User-friendly introduction to PAC-Bayes bounds—0
On Optimal Interpolation In Linear RegressionCode0
Provable Hierarchy-Based Meta-Reinforcement Learning—0
Explaining generalization in deep learning: progress and fundamental limits—0
Synthesizing Machine Learning Programs with PAC Guarantees via Statistical Sketching—0
I Do Not Understand What I Cannot Define: Automatic Question Generation With Pedagogically-Driven Content Selection—0
PAC Synthesis of Machine Learning Programs—0
Variational Inference via Resolution of Singularities—0
Model Zoo: A Growing Brain That Learns Continually—0
Huber Additive Models for Non-stationary Time Series Analysis—0
Learning to Abstain in the Presence of Uninformative Data—0
Towards a theory of out-of-distribution learning—0
The NTK Adversary: An Approach to Adversarial Attacks without any Model Access—0
Reliable Estimation of KL Divergence using a Discriminator in Reproducing Kernel Hilbert Space—0
Sequence Approximation using Feedforward Spiking Neural Network for Spatiotemporal Learning: Theory and Optimization Methods—0
Improved Generalization Risk Bounds for Meta-Learning with PAC-Bayes-kl Analysis—0
Task Relatedness-Based Generalization Bounds for Meta Learning—0
Cancer Progression as a Learning Process—0
Robust Generalization of Quadratic Neural Networks via Function Identification—0
Minimax Rates for High-Dimensional Random Tessellation Forests—0
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