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Monte-Carlo utility estimates for Bayesian reinforcement learning

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Understanding generalization and robustness in modern deep learning

Revisiting Character-level Adversarial Attacks for Language Models

Deep Learning Generalization with Limited and Noisy Labels

Computationally Efficient Reinforcement Learning: Targeted Exploration leveraging Simple Rules

Byzantine Fault-Tolerance in Federated Local SGD Under 2f-Redundancy

Masked Training of Neural Networks with Partial Gradients

Stochastic Second-Order Methods Improve Best-Known Sample Complexity of SGD for Gradient-Dominated Function

Phase diagram of Stochastic Gradient Descent in high-dimensional two-layer neural networks

Gradient-Based Learning of Discrete Structured Measurement Operators for Signal Recovery

Faster One-Sample Stochastic Conditional Gradient Method for Composite Convex Minimization

Understanding generalization and robustness in modern deep learning

Deep Learning Generalization with Limited and Noisy Labels

Stochastic Second-Order Methods Improve Best-Known Sample Complexity of SGD for Gradient-Dominated Function

Faster One-Sample Stochastic Conditional Gradient Method for Composite Convex Minimization

Gradient-Based Learning of Discrete Structured Measurement Operators for Signal Recovery

Masked Training of Neural Networks with Partial Gradients

Revisiting Character-level Adversarial Attacks for Language Models

Computationally Efficient Reinforcement Learning: Targeted Exploration leveraging Simple Rules

Byzantine Fault-Tolerance in Federated Local SGD Under 2f-Redundancy

Phase diagram of Stochastic Gradient Descent in high-dimensional two-layer neural networks