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Learning Theory

Learning theory

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Showing 551–600 of 852 papers

TitleStatusHype
Mirror Sample Based Distribution Alignment for Unsupervised Domain Adaption—0
Why Mixup Improves the Model Performance—0
Model Zoo: A Growing Brain That Learns Continually—0
Moderately-Balanced Representation Learning for Treatment Effects with Orthogonality Information—0
Monotonic Learning in the PAC Framework: A New Perspective—0
MS-DCANet: A Novel Segmentation Network For Multi-Modality COVID-19 Medical Images—0
Multi-label Learning for Large Text Corpora using Latent Variable Model with Provable Gurantees—0
Multimodal large language models for inclusive collaboration learning tasks—0
Nearest Neighbour Based Estimates of Gradients: Sharp Nonasymptotic Bounds and Applications—0
Near Optimal Memory-Regret Tradeoff for Online Learning—0
Neural Hilbert Ladders: Multi-Layer Neural Networks in Function Space—0
Envisioning Future Deep Learning Theories: Some Basic Concepts and Characteristics—0
New Statistical and Computational Results for Learning Junta Distributions—0
New Steps on the Exact Learning of CNF—0
Non-Bayesian Social Learning with Uncertain Models—0
Nonconvex penalties with analytical solutions for one-bit compressive sensing—0
Nonparametric Control Koopman Operators—0
When Is Inductive Inference Possible?—0
Notes on Deep Learning Theory—0
Novel Bernstein-like Concentration Inequalities for the Missing Mass—0
Novel Deviation Bounds for Mixture of Independent Bernoulli Variables with Application to the Missing Mass—0
Numerical and statistical analysis of NeuralODE with Runge-Kutta time integration—0
Of Dice and Games: A Theory of Generalized Boosting—0
Omnipredicting Single-Index Models with Multi-Index Models—0
On a Chatbot Navigating a User through a Concept-Based Knowledge Model—0
On aggregation for heavy-tailed classes—0
A Theoretical Survey on Foundation Models—0
On Communication Complexity of Classification Problems—0
On Continuity of Robust and Accurate Classifiers—0
On-Device Machine Learning: An Algorithms and Learning Theory Perspective—0
On Empirical Risk Minimization with Dependent and Heavy-Tailed Data—0
One-shot learning and behavioral eligibility traces in sequential decision making—0
On establishing learning separations between classical and quantum machine learning with classical data—0
On Generalization Error Bounds of Noisy Gradient Methods for Non-Convex Learning—0
On kernel-based statistical learning in the mean field limit—0
On Learnability under General Stochastic Processes—0
On Learnability with Computable Learners—0
On learning k-parities with and without noise—0
Disagreement-based Active Learning in Online Settings—0
Online Epsilon Net and Piercing Set for Geometric Concepts—0
Online Learning: Random Averages, Combinatorial Parameters, and Learnability—0
Online Learning: Stochastic, Constrained, and Smoothed Adversaries—0
Online Learning via Sequential Complexities—0
On Reject and Refine Options in Multicategory Classification—0
On statistical learning via the lens of compression—0
How Powerful are Shallow Neural Networks with Bandlimited Random Weights?—0
On the Asymptotic Learning Curves of Kernel Ridge Regression under Power-law Decay—0
On the Comparison between Multi-modal and Single-modal Contrastive Learning—0
On the Complexity of Computing Gödel Numbers—0
On the Complexity of Learning Description Logic Ontologies—0
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