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learning theory

518 papers

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generalization bound (649) sample complexity (1158) statistical learning (350) neural network (6616) online learning (1770) gradient descent (1143) stochastic gradient descent (1088) empirical risk minimization (348) convergence rate (606) pac learning (280)

Papers

Small random initialization is akin to spectral learning: Optimization and generalization guarantees for overparameterized low-rank matrix reconstruction NIPS 2021
On the Cryptographic Hardness of Learning Single Periodic Neurons NIPS 2021
Towards Convergence Rate Analysis of Random Forests for Classification NIPS 2020
A Limitation of the PAC-Bayes Framework NIPS 2020
On the Theory of Transfer Learning: The Importance of Task Diversity NIPS 2020
Spectra of the Conjugate Kernel and Neural Tangent Kernel for linear-width neural networks NIPS 2020
Hardness of Learning Neural Networks with Natural Weights NIPS 2020
Generalization Error Bounds of Gradient Descent for Learning Over-Parameterized Deep ReLU Networks AAAI 2020
Conference on Learning Theory 2020: Preface COLT 2020
On the limits of cross-domain generalization in automated X-ray prediction MIDL 2020
Statistical Learning with a Nuisance Component (Extended Abstract) IJCAI 2020
Lower Bounds for Learning Distributions under Communication Constraints via Fisher Information JMLR 2020
Incorporating Failure Events in Agents’ Decision Making to Improve User Satisfaction IJCAI 2020
What shapes feature representations? Exploring datasets, architectures, and training NIPS 2020
Sample-Efficient Reinforcement Learning of Undercomplete POMDPs NIPS 2020
Fast Rates for General Unbounded Loss Functions: From ERM to Generalized Bayes JMLR 2020
Theory of Curriculum Learning, with Convex Loss Functions JMLR 2020
Sharper Bounds for Uniformly Stable Algorithms COLT 2020
Open Problem: Tight Convergence of SGD in Constant Dimension COLT 2020
Universal Equivariant Multilayer Perceptrons ICML 2020
Strength from Weakness: Fast Learning Using Weak Supervision ICML 2020
Improved PAC-Bayesian Bounds for Linear Regression AAAI 2020
More Data Can Expand The Generalization Gap Between Adversarially Robust and Standard Models ICML 2020
Simultaneous Inference for Massive Data: Distributed Bootstrap ICML 2020
PAC-Bayes Learning Bounds for Sample-Dependent Priors NIPS 2020