Reinforcement Learning Approach to Stochastic Vehicle Routing Problem With Correlated Demands, Zangir Iklassov, Ikboljon Sobirov, Ruben Solozabal, Martin Takac
Martin Takac

On the Study of Curriculum Learning for Inferring Dispatching Policies on the Job Shop Scheduling, Zangir Iklassov, Dmitrii Medvedev, Ruben Solozabal Ochoa de Retana, Martin Takac
Martin Takac

On the Study of Curriculum Learning for Inferring Dispatching Policies on the Job Shop Scheduling, Zangir Iklassov, Dmitrii Medvedev, Ruben Solozabal Ochoa de Retana, Martin Takac
Machine Learning Faculty Publications

Reinforcement Learning Approach to Stochastic Vehicle Routing Problem With Correlated Demands, Zangir Iklassov, Ikboljon Sobirov, Ruben Solozabal, Martin Takac
Machine Learning Faculty Publications

Decentralized personalized federated learning: Lower bounds and optimal algorithm for all personalization modes, Abdurakhmon Sadiev, Ekaterina Borodich, Aleksandr Beznosikov, Darina Dvinskikh, Saveliy Chezhegov, Rachael Tappenden, Martin Takac, Alexander Gasnikov
Martin Takac

Towards Practical Large Scale Non-Linear Semi-Supervised Learning with Balancing Constraints, Zhengqing Gao, Huimin Wu, Martin Takac, Bin Gu
Martin Takac

Towards Practical Large Scale Non-Linear Semi-Supervised Learning with Balancing Constraints, Zhengqing Gao, Huimin Wu, Martin Takac, Bin Gu
Bin Gu

Towards Practical Large Scale Non-Linear Semi-Supervised Learning with Balancing Constraints, Zhengqing Gao, Huimin Wu, Martin Takac, Bin Gu
Machine Learning Faculty Publications

Suppressing Poisoning Attacks on Federated Learning for Medical Imaging, Naif Alkhunaizi, Dmitry Kamzolov, Martin Takac, Karthik Nandakumar
Martin Takac

SP2: A Second Order Stochastic Polyak Method, Shuang Li, William J. Swartworth, Martin Takac, Deanna Needell, Robert M. Gower
Martin Takac

Decentralized personalized federated learning: Lower bounds and optimal algorithm for all personalization modes, Abdurakhmon Sadiev, Ekaterina Borodich, Aleksandr Beznosikov, Darina Dvinskikh, Saveliy Chezhegov, Rachael Tappenden, Martin Takac, Alexander Gasnikov
Machine Learning Faculty Publications

Suppressing Poisoning Attacks on Federated Learning for Medical Imaging, Naif Alkhunaizi, Dmitry Kamzolov, Martin Takac, Karthik Nandakumar
Karthik Nandakumar

Suppressing Poisoning Attacks on Federated Learning for Medical Imaging, Naif Alkhunaizi, Dmitry Kamzolov, Martin Takac, Karthik Nandakumar
Machine Learning Faculty Publications

Exploiting higher-order derivatives in convex optimization methods, Dmitry Kamzolov, Alexander Gasnikov, Pavel Dvurechensky, Artem Agafonov, Martin Takac
Martin Takac

Exploiting higher-order derivatives in convex optimization methods, Dmitry Kamzolov, Alexander Gasnikov, Pavel Dvurechensky, Artem Agafonov, Martin Takac
Machine Learning Faculty Publications

Learning to Control under Time-Varying Environment, Yuzhen Han, Ruben Solozabal, Jing Dong, Xingyu Zhou, Martin Takac, Bin Gu
Bin Gu

Learning to Control under Time-Varying Environment, Yuzhen Han, Ruben Solozabal, Jing Dong, Xingyu Zhou, Martin Takac, Bin Gu
Martin Takac

On Scaled Methods for Saddle Point Problems, Aleksandr Beznosikov, Aibek Alanov, Dmitry Kovalev, Martin Takac, Alexander Gasnikov
Martin Takac

Algorithm for Constrained Markov Decision Process with Linear Convergence, Egor Gladin, Maksim Lavrik-Karmazin, Karina Zainullina, Varvara Rudenko, Alexander Gasnikov, Martin Takac
Martin Takac

Learning to generalize Dispatching rules on the Job Shop Scheduling, Zangir Iklassov, Dmitrii Medvedev, Ruben Solozabal, Martin Takac
Martin Takac

Stochastic Gradient Methods with Preconditioned Updates, Abdurakhmon Sadiev, Aleksandr Beznosikov, Abdulla Jasem Almansoori, Dmitry Kamzolov, Rachael Tappenden, Martin Takac
Martin Takac

FLECS: A Federated Learning Second-Order Framework via Compression and Sketching, Artem Agafonov, Dmitry Kamzolov, Rachael Tappenden, Alexander Gasnikov, Martin Takac
Martin Takac

Inexact Tensor Methods and Their Application to Stochastic Convex Optimization, Artem Agafonov, Dmitry Kamzolov, Pavel Dvurechensky, Alexander Gasnikov, Martin Takac
Martin Takac

AI-SARAH: Adaptive and Implicit Stochastic Recursive Gradient Methods, Zheng Shi, Abdurakhmon Sadiev, Nicolas Loizou, Peter Richtárik, Martin Takac
Martin Takac

Distributed Learning With Sparsified Gradient Differences, Yicheng Chen, Rick S. Blum, Martin Takac, Brian M. Sadler
Martin Takac

SP2: A Second Order Stochastic Polyak Method, Shuang Li, William J. Swartworth, Martin Takac, Deanna Needell, Robert M. Gower
Machine Learning Faculty Publications

Stochastic Gradient Methods with Preconditioned Updates, Abdurakhmon Sadiev, Aleksandr Beznosikov, Abdulla Jasem Almansoori, Dmitry Kamzolov, Rachael Tappenden, Martin Takac
Machine Learning Faculty Publications

Algorithm for Constrained Markov Decision Process with Linear Convergence, Egor Gladin, Maksim Lavrik-Karmazin, Karina Zainullina, Varvara Rudenko, Alexander Gasnikov, Martin Takac
Machine Learning Faculty Publications

FLECS: A Federated Learning Second-Order Framework via Compression and Sketching, Artem Agafonov, Dmitry Kamzolov, Rachael Tappenden, Alexander Gasnikov, Martin Takac
Machine Learning Faculty Publications

Learning to Control under Time-Varying Environment, Yuzhen Han, Ruben Solozabal, Jing Dong, Xingyu Zhou, Martin Takac, Bin Gu
Machine Learning Faculty Publications

Learning to generalize Dispatching rules on the Job Shop Scheduling, Zangir Iklassov, Dmitrii Medvedev, Ruben Solozabal, Martin Takac
Machine Learning Faculty Publications

On Scaled Methods for Saddle Point Problems, Aleksandr Beznosikov, Aibek Alanov, Dmitry Kovalev, Martin Takac, Alexander Gasnikov
Machine Learning Faculty Publications

Robustness Analysis of Classification Using Recurrent Neural Networks with Perturbed Sequential Input, Guangyi Liu, Arash Amini, Martin Takac, Nader Motee
Martin Takac

Distributed Learning With Sparsified Gradient Differences, Yicheng Chen, Rick S. Blum, Martin Takac, Brian M. Sadler
Machine Learning Faculty Publications

Robustness Analysis of Classification Using Recurrent Neural Networks with Perturbed Sequential Input, Guangyi Liu, Arash Amini, Martin Takac, Nader Motee
Machine Learning Faculty Publications

AI-SARAH: Adaptive and Implicit Stochastic Recursive Gradient Methods, Zheng Shi, Abdurakhmon Sadiev, Nicolas Loizou, Peter Richtárik, Martin Takac
Machine Learning Faculty Publications

Inexact Tensor Methods and Their Application to Stochastic Convex Optimization, Artem Agafonov, Dmitry Kamzolov, Pavel Dvurechensky, Alexander Gasnikov, Martin Takac
Machine Learning Faculty Publications