← Keywords

learning theory

518 papers

Explore in graph

Co-occurring keywords

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

Hardness of Learning a Single Neuron with Adversarial Label Noise AISTATS 2022
On the Statistical Benefits of Curriculum Learning ICML 2022
On the Impossibility of Learning to Cooperate with Adaptive Partner Strategies in Repeated Games ICML 2022
Investigating Generalization by Controlling Normalized Margin ICML 2022
KL-UCB-Switch: Optimal Regret Bounds for Stochastic Bandits from Both a Distribution-Dependent and a Distribution-Free Viewpoints JMLR 2022
On the non-universality of deep learning: quantifying the cost of symmetry NIPS 2022
What is a Good Metric to Study Generalization of Minimax Learners? NIPS 2022
When Hardness of Approximation Meets Hardness of Learning JMLR 2022
SQ Lower Bounds for Learning Single Neurons with Massart Noise NIPS 2022
Linear Label Ranking with Bounded Noise NIPS 2022
Hardness of Noise-Free Learning for Two-Hidden-Layer Neural Networks NIPS 2022
Overparameterization from Computational Constraints NIPS 2022
A spectral-based analysis of the separation between two-layer neural networks and linear methods JMLR 2022
Theoretical analysis of deep neural networks for temporally dependent observations NIPS 2022
Local Identifiability of Deep ReLU Neural Networks: the Theory NIPS 2022
On Robust Multiclass Learnability NIPS 2022
Exponentially Improving the Complexity of Simulating the Weisfeiler-Lehman Test with Graph Neural Networks NIPS 2022
Towards Understanding the Mixture-of-Experts Layer in Deep Learning NIPS 2022
A general approximation lower bound in $L^p$ norm, with applications to feed-forward neural networks NIPS 2022
Hidden Progress in Deep Learning: SGD Learns Parities Near the Computational Limit NIPS 2022
Stability and Generalization for Markov Chain Stochastic Gradient Methods NIPS 2022
Rethinking Influence Functions of Neural Networks in the Over-Parameterized Regime AAAI 2022
Regularized Modal Regression on Markov-Dependent Observations: A Theoretical Assessment AAAI 2022
The Perils of Learning Before Optimizing AAAI 2022
On the Generalization Power of the Overfitted Three-Layer Neural Tangent Kernel Model NIPS 2022