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Learning Theory

Learning theory

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Showing 151–200 of 852 papers

TitleStatusHype
Bayesian Free Energy of Deep ReLU Neural Network in Overparametrized Cases—0
A Nearly Optimal and Agnostic Algorithm for Properly Learning a Mixture of k Gaussians, for any Constant k—0
Adversarial Training Can Provably Improve Robustness: Theoretical Analysis of Feature Learning Process Under Structured Data—0
Generalization within in silico screening—0
Bandit Theory and Thompson Sampling-Guided Directed Evolution for Sequence Optimization—0
An Asymptotic Equation Linking WAIC and WBIC in Singular Models—0
Bagging is an Optimal PAC Learner—0
Improving Generalization of Complex Models under Unbounded Loss Using PAC-Bayes Bounds—0
An Approach to One-Bit Compressed Sensing Based on Probably Approximately Correct Learning Theory—0
Adversarial Robustness of Deep Learning: Theory, Algorithms, and Applications—0
Autonomous Learning of Generative Models with Chemical Reaction Network Ensembles—0
Automatically Score Tissue Images Like a Pathologist by Transfer Learning—0
A unified framework of non-local parametric methods for image denoising—0
Analyzing Upper Bounds on Mean Absolute Errors for Deep Neural Network Based Vector-to-Vector Regression—0
Adversarial Robustness is at Odds with Lazy Training—0
A Combinatorial Characterization of Supervised Online Learnability—0
A Bennett Inequality for the Missing Mass—0
A Unified Approach to Universal Prediction: Generalized Upper and Lower Bounds—0
Attribute-Efficient PAC Learning of Sparse Halfspaces with Constant Malicious Noise Rate—0
An Algorithmic Perspective on Imitation Learning—0
Attention Is Not the Only Choice: Counterfactual Reasoning for Path-Based Explainable Recommendation—0
An Algorithm-Centered Approach To Model Streaming Data—0
A Denoising Loss Bound for Neural Network based Universal Discrete Denoisers—0
A Tight Lower Bound for Uniformly Stable Algorithms—0
A Tight Excess Risk Bound via a Unified PAC-Bayesian-Rademacher-Shtarkov-MDL Complexity—0
An Adaptive Clipping Approach for Proximal Policy Optimization—0
A Theory of Learning Unified Model via Knowledge Integration from Label Space Varying Domains—0
A Theory of Formal Synthesis via Inductive Learning—0
An Active Learning Framework for Constructing High-fidelity Mobility Maps—0
A deep learning theory for neural networks grounded in physics—0
A cognitively driven weighted-entropy model for embedding semantic categories in hyperbolic geometry—0
A Temporal Difference Reinforcement Learning Theory of Emotion: unifying emotion, cognition and adaptive behavior—0
A Systems Theory of Transfer Learning—0
A multi-source data power load forecasting method using attention mechanism-based parallel cnn-gru—0
A Survey on Statistical Theory of Deep Learning: Approximation, Training Dynamics, and Generative Models—0
A Survey on Optimal Transport for Machine Learning: Theory and Applications—0
A Moment-Matching Approach to Testable Learning and a New Characterization of Rademacher Complexity—0
A deep deformable residual learning network for SAR images segmentation—0
A Survey of Quantum Learning Theory—0
Deep learning generalizes because the parameter-function map is biased towards simple functions—0
A Model of Selective Advantage for the Efficient Inference of Cancer Clonal Evolution—0
Deep Learning and Continuous Representations for Natural Language Processing—0
DeepHider: A Covert NLP Watermarking Framework Based on Multi-task Learning—0
Tight Bounds on the Hardness of Learning Simple Nonparametric Mixtures—0
Deep Fisher Kernels - End to End Learning of the Fisher Kernel GMM Parameters—0
Deep Fictitious Play for Stochastic Differential Games—0
A Sufficient Statistics Construction of Bayesian Nonparametric Exponential Family Conjugate Models—0
Deep Learning Optimization Theory - Trajectory Analysis of Gradient Descent—0
A Mathematical Theory of Learning—0
Adaptive time series forecasting with markovian variance switching—0
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