Learning Proximal Operators with Gaussian Processes

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Learning Proximal Operators with Gaussian Processes

Chat with Graph Search

Understanding generalization and robustness in modern deep learning

On the Generalization of Stochastic Gradient Descent with Momentum

Optimization Algorithms for Decentralized, Distributed and Collaborative Machine Learning

3D diffractive optics for linear interconnects and nonlinear processing

Hypergraph-Based Fast Distributed AC Power Flow Optimization

Incremental Learning in Diagonal Linear Networks

The evolution of behavioral cues and signaling in displaced communication

Deep Learning Generalization with Limited and Noisy Labels

The statistical complexity of early-stopped mirror descent

Bayes-optimal Learning of Deep Random Networks of Extensive-width

(S)GD over Diagonal Linear Networks: Implicit Regularisation, Large Stepsizes and Edge of Stability

Saddle-to-Saddle Dynamics in Diagonal Linear Networks

Regularization Techniques for Low-Resource Machine Translation

Genomics and conservation: Guidance from training to analyses and applications

Data-Driven Control and Optimization under Noisy and Uncertain Conditions

Machine Learning Methods for Robust Uncertainty Quantification and Controller Approximation

Fundamental Limits in Statistical Learning Problems: Block Models and Neural Networks

A digital bridge between brain and spinal cord restores walking after paralysis

Distributionally Robust Linear Quadratic Control

A new variable shape parameter strategy for RBF approximation using neural networks