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Learning Theory

Learning theory

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Showing 151–175 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
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