Regularization of the Policy Updates for Stabilizing Mean Field Games, Talal Algumaei, Ruben Solozabal, Reda Alami, Hakim Hacid, Merouane Debbah, Martin Takáč
Martin Takac

A Damped Newton Method Achieves Global O(1/K²) and Local Quadratic Convergence Rate, Slavomír Hanzely, Dmitry Kamzolov, Dmitry Pasechnyuk, Alexander Gasnikov, Peter Richtárik, Martin Takáč
Martin Takac

Regularization of the Policy Updates for Stabilizing Mean Field Games, Talal Algumaei, Ruben Solozabal, Reda Alami, Hakim Hacid, Merouane Debbah, Martin Takáč
Mérouane Debbah

Regularization of the Policy Updates for Stabilizing Mean Field Games, Talal Algumaei, Ruben Solozabal, Reda Alami, Hakim Hacid, Merouane Debbah, Martin Takáč
Machine Learning Faculty Publications

A Damped Newton Method Achieves Global O(1/K²) and Local Quadratic Convergence Rate, Slavomír Hanzely, Dmitry Kamzolov, Dmitry Pasechnyuk, Alexander Gasnikov, Peter Richtárik, Martin Takáč
Machine Learning Faculty Publications

The Power Of First-Order Smooth Optimization for Black-Box Non-Smooth Problems, Alexander V. Gasnikov., Anton Novitskii, Vasilii Novitskii, Farshed Abdukhakimov, Dmitry Kamzolov, Aleksandr Beznosikov, Martin Takáč, Pavel Dvurechensky, Bin Gu
Bin Gu

Quasi-Newton Methods for Machine Learning: Forget the Past, Just Sample, Albert S. Berahas, Majid Jahani, Peter Richtárik, Martin Takáč
Martin Takac

The Power Of First-Order Smooth Optimization for Black-Box Non-Smooth Problems, Alexander V. Gasnikov., Anton Novitskii, Vasilii Novitskii, Farshed Abdukhakimov, Dmitry Kamzolov, Aleksandr Beznosikov, Martin Takáč, Pavel Dvurechensky, Bin Gu
Martin Takac

Doubly Adaptive Scaled Algorithm for Machine Learning Using Second-Order Information, Majid Jahani, Sergey Rusakov, Zheng Shi, Peter Richtárik, Michael W. Mahoney, Martin Takáč
Martin Takac

Random-Reshuffled SARAH Does Not Need a Full Gradient Computations, Aleksandr Beznosikov, Martin Takáč
Martin Takac

Decentralized Personalized Federated Min-Max Problems, Ekaterina Borodich, Aleksandr Beznosikov, Abdurakhmon Sadiev, Vadim Sushko, Nikolay Savelyev, Martin Takáč, Alexander V. Gasnikov
Machine Learning Faculty Publications

The Power Of First-Order Smooth Optimization for Black-Box Non-Smooth Problems, Alexander V. Gasnikov., Anton Novitskii, Vasilii Novitskii, Farshed Abdukhakimov, Dmitry Kamzolov, Aleksandr Beznosikov, Martin Takáč, Pavel Dvurechensky, Bin Gu
Machine Learning Faculty Publications

Random-Reshuffled SARAH Does Not Need a Full Gradient Computations, Aleksandr Beznosikov, Martin Takáč
Machine Learning Faculty Publications

Improving Text-To-Image Synthesis Using Contrastive Learning, Hui Ye, Xiulong Yang, Martin Takáč, Raj Sunderraman, Shihao Ji
Machine Learning Faculty Publications

Quasi-Newton Methods for Machine Learning: Forget the Past, Just Sample, Albert S. Berahas, Majid Jahani, Peter Richtárik, Martin Takáč
Machine Learning Faculty Publications

Doubly Adaptive Scaled Algorithm for Machine Learning Using Second-Order Information, Majid Jahani, Sergey Rusakov, Zheng Shi, Peter Richtárik, Michael W. Mahoney, Martin Takáč
Machine Learning Faculty Publications