Publications associées à Hessian Schatten-Norm Regularization for Linear Inverse Problems

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Convergence of adaptive algorithms for constrained weakly convex optimization

Volkan Cevher, Ahmet Alacaoglu, Yurii Malitskyi

We analyze the adaptive first order algorithm AMSGrad, for solving a constrained stochastic optimization problem with a weakly convex objective. We prove the

\tilde O(t^{-1/2})

rate of convergence for the squared norm of the gradient of Moreau envelope, ...

2021

Hessian Schatten-Norm Regularization for Linear Inverse Problems

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Augmented Lagrangian Methods for Provable and Scalable Machine Learning

Learning of Continuous and Piecewise-Linear Functions With Hessian Total-Variation Regularization

Optimization Over Banach Spaces: A Unified View on Supervised Learning and Inverse Problems

Predicting in Uncertain Environments: Methods for Robust Machine Learning

Convex optimization in sums of Banach spaces

KPC: Learning-Based Model Predictive Control with Deterministic Guarantees

Convergence of adaptive algorithms for constrained weakly convex optimization

A Unifying Representer Theorem for Inverse Problems and Machine Learning

Bootstrapping massive quantum field theories

Maximum-likelihood estimation of kinetic parameters via the extent-based incremental approach

Augmented Lagrangian Methods for Provable and Scalable Machine Learning

Learning of Continuous and Piecewise-Linear Functions With Hessian Total-Variation Regularization

Optimization Over Banach Spaces: A Unified View on Supervised Learning and Inverse Problems

Predicting in Uncertain Environments: Methods for Robust Machine Learning

Convex optimization in sums of Banach spaces

Maximum-likelihood estimation of kinetic parameters via the extent-based incremental approach

KPC: Learning-Based Model Predictive Control with Deterministic Guarantees

Bootstrapping massive quantum field theories

A Unifying Representer Theorem for Inverse Problems and Machine Learning

Convergence of adaptive algorithms for constrained weakly convex optimization