More from the Same Authors

• 2021 : Better Linear Rates for SGD with Data Shuffling »
  Grigory Malinovsky · Alibek Sailanbayev · Peter Richtarik
• 2021 : Better Linear Rates for SGD with Data Shuffling »
  Grigory Malinovsky · Alibek Sailanbayev · Peter Richtarik
• 2021 : Shifted Compression Framework: Generalizations and Improvements »
  Egor Shulgin · Peter Richtarik
• 2021 : EF21 with Bells & Whistles: Practical Algorithmic Extensions of Modern Error Feedback »
  Peter Richtarik · Igor Sokolov · Ilyas Fatkhullin · Eduard Gorbunov · Zhize Li
• 2021 : On Server-Side Stepsizes in Federated Optimization: Theory Explaining the Heuristics »
  Grigory Malinovsky · Konstantin Mishchenko · Peter Richtarik
• 2021 : FedMix: A Simple and Communication-Efficient Alternative to Local Methods in Federated Learning »
  Elnur Gasanov · Ahmed Khaled Ragab Bayoumi · Samuel Horváth · Peter Richtarik
• 2021 : FedMix: A Simple and Communication-Efficient Alternative to Local Methods in Federated Learning »
  Elnur Gasanov · Ahmed Khaled Ragab Bayoumi · Samuel Horváth · Peter Richtarik
• 2022 Poster: Theoretically Better and Numerically Faster Distributed Optimization with Smoothness-Aware Quantization Techniques »
  Bokun Wang · Mher Safaryan · Peter Richtarik
• 2022 : RandProx: Primal-Dual Optimization Algorithms with Randomized Proximal Updates »
  Laurent Condat · Peter Richtarik
• 2022 : Distributed Newton-Type Methods with Communication Compression and Bernoulli Aggregation »
  Rustem Islamov · Xun Qian · Slavomír Hanzely · Mher Safaryan · Peter Richtarik
• 2022 : Certified Robustness in Federated Learning »
  Motasem Alfarra · Juan Perez · Egor Shulgin · Peter Richtarik · Bernard Ghanem
• 2022 Spotlight: Accelerated Primal-Dual Gradient Method for Smooth and Convex-Concave Saddle-Point Problems with Bilinear Coupling »
  Dmitry Kovalev · Alexander Gasnikov · Peter Richtarik
• 2022 Spotlight: Communication Acceleration of Local Gradient Methods via an Accelerated Primal-Dual Algorithm with an Inexact Prox »
  Abdurakhmon Sadiev · Dmitry Kovalev · Peter Richtarik
• 2022 Spotlight: Distributed Methods with Compressed Communication for Solving Variational Inequalities, with Theoretical Guarantees »
  Aleksandr Beznosikov · Peter Richtarik · Michael Diskin · Max Ryabinin · Alexander Gasnikov
• 2022 Spotlight: Optimal Algorithms for Decentralized Stochastic Variational Inequalities »
  Dmitry Kovalev · Aleksandr Beznosikov · Abdurakhmon Sadiev · Michael Persiianov · Peter Richtarik · Alexander Gasnikov
• 2022 Spotlight: Lightning Talks 4A-1 »
  Jiawei Huang · Su Jia · Abdurakhmon Sadiev · Ruomin Huang · Yuanyu Wan · Denizalp Goktas · Jiechao Guan · Andrew Li · Wei-Wei Tu · Li Zhao · Amy Greenwald · Jiawei Huang · Dmitry Kovalev · Yong Liu · Wenjie Liu · Peter Richtarik · Lijun Zhang · Zhiwu Lu · R Ravi · Tao Qin · Wei Chen · Hu Ding · Nan Jiang · Tie-Yan Liu
• 2022 Workshop: Federated Learning: Recent Advances and New Challenges »
  Shiqiang Wang · Nathalie Baracaldo · Olivia Choudhury · Gauri Joshi · Peter Richtarik · Praneeth Vepakomma · Han Yu
• 2022 Poster: Variance Reduced ProxSkip: Algorithm, Theory and Application to Federated Learning »
  Grigory Malinovsky · Kai Yi · Peter Richtarik
• 2022 Poster: Communication Acceleration of Local Gradient Methods via an Accelerated Primal-Dual Algorithm with an Inexact Prox »
  Abdurakhmon Sadiev · Dmitry Kovalev · Peter Richtarik
• 2022 Poster: A Damped Newton Method Achieves Global $\mathcal O \left(\frac{1}{k^2}\right)$ and Local Quadratic Convergence Rate »
  Slavomír Hanzely · Dmitry Kamzolov · Dmitry Pasechnyuk · Alexander Gasnikov · Peter Richtarik · Martin Takac
• 2022 Poster: BEER: Fast $O(1/T)$ Rate for Decentralized Nonconvex Optimization with Communication Compression »
  Haoyu Zhao · Boyue Li · Zhize Li · Peter Richtarik · Yuejie Chi
• 2022 Poster: EF-BV: A Unified Theory of Error Feedback and Variance Reduction Mechanisms for Biased and Unbiased Compression in Distributed Optimization »
  Laurent Condat · Kai Yi · Peter Richtarik
• 2022 Poster: Optimal Algorithms for Decentralized Stochastic Variational Inequalities »
  Dmitry Kovalev · Aleksandr Beznosikov · Abdurakhmon Sadiev · Michael Persiianov · Peter Richtarik · Alexander Gasnikov
• 2022 Poster: Accelerated Primal-Dual Gradient Method for Smooth and Convex-Concave Saddle-Point Problems with Bilinear Coupling »
  Dmitry Kovalev · Alexander Gasnikov · Peter Richtarik
• 2022 Poster: Distributed Methods with Compressed Communication for Solving Variational Inequalities, with Theoretical Guarantees »
  Aleksandr Beznosikov · Peter Richtarik · Michael Diskin · Max Ryabinin · Alexander Gasnikov
• 2021 : Keynote Talk: Permutation Compressors for Provably Faster Distributed Nonconvex Optimization (Peter Richtarik) »
  Peter Richtarik
• 2021 Poster: Smoothness Matrices Beat Smoothness Constants: Better Communication Compression Techniques for Distributed Optimization »
  Mher Safaryan · Filip Hanzely · Peter Richtarik
• 2021 Poster: EF21: A New, Simpler, Theoretically Better, and Practically Faster Error Feedback »
  Peter Richtarik · Igor Sokolov · Ilyas Fatkhullin
• 2021 Poster: Error Compensated Distributed SGD Can Be Accelerated »
  Xun Qian · Peter Richtarik · Tong Zhang
• 2021 Poster: CANITA: Faster Rates for Distributed Convex Optimization with Communication Compression »
  Zhize Li · Peter Richtarik
• 2021 Poster: Lower Bounds and Optimal Algorithms for Smooth and Strongly Convex Decentralized Optimization Over Time-Varying Networks »
  Dmitry Kovalev · Elnur Gasanov · Alexander Gasnikov · Peter Richtarik
• 2021 Oral: EF21: A New, Simpler, Theoretically Better, and Practically Faster Error Feedback »
  Peter Richtarik · Igor Sokolov · Ilyas Fatkhullin
• 2020 : Poster Session 1 (gather.town) »
  Laurent Condat · Tiffany Vlaar · Ohad Shamir · Mohammadi Zaki · Zhize Li · Guan-Horng Liu · Samuel Horváth · Mher Safaryan · Yoni Choukroun · Kumar Shridhar · Nabil Kahale · Jikai Jin · Pratik Kumar Jawanpuria · Gaurav Kumar Yadav · Kazuki Koyama · Junyoung Kim · Xiao Li · Saugata Purkayastha · Adil Salim · Dighanchal Banerjee · Peter Richtarik · Lakshman Mahto · Tian Ye · Bamdev Mishra · Huikang Liu · Jiajie Zhu
• 2020 Poster: Primal Dual Interpretation of the Proximal Stochastic Gradient Langevin Algorithm »
  Adil Salim · Peter Richtarik
• 2020 Poster: Linearly Converging Error Compensated SGD »
  Eduard Gorbunov · Dmitry Kovalev · Dmitry Makarenko · Peter Richtarik
• 2020 Poster: Random Reshuffling: Simple Analysis with Vast Improvements »
  Konstantin Mishchenko · Ahmed Khaled Ragab Bayoumi · Peter Richtarik
• 2020 Spotlight: Linearly Converging Error Compensated SGD »
  Eduard Gorbunov · Dmitry Kovalev · Dmitry Makarenko · Peter Richtarik
• 2020 Session: Orals & Spotlights Track 21: Optimization »
  Peter Richtarik · Marco Cuturi
• 2020 Poster: Lower Bounds and Optimal Algorithms for Personalized Federated Learning »
  Filip Hanzely · Slavomír Hanzely · Samuel Horváth · Peter Richtarik
• 2020 Poster: Optimal and Practical Algorithms for Smooth and Strongly Convex Decentralized Optimization »
  Dmitry Kovalev · Adil Salim · Peter Richtarik
• 2019 Poster: RSN: Randomized Subspace Newton »
  Robert Gower · Dmitry Kovalev · Felix Lieder · Peter Richtarik
• 2019 Poster: Stochastic Proximal Langevin Algorithm: Potential Splitting and Nonasymptotic Rates »
  Adil Salim · Dmitry Kovalev · Peter Richtarik
• 2019 Spotlight: Stochastic Proximal Langevin Algorithm: Potential Splitting and Nonasymptotic Rates »
  Adil Salim · Dmitry Kovalev · Peter Richtarik
• 2018 Poster: Stochastic Spectral and Conjugate Descent Methods »
  Dmitry Kovalev · Peter Richtarik · Eduard Gorbunov · Elnur Gasanov
• 2018 Poster: Accelerated Stochastic Matrix Inversion: General Theory and Speeding up BFGS Rules for Faster Second-Order Optimization »
  Robert Gower · Filip Hanzely · Peter Richtarik · Sebastian Stich
• 2018 Poster: SEGA: Variance Reduction via Gradient Sketching »
  Filip Hanzely · Konstantin Mishchenko · Peter Richtarik
• 2015 Poster: Quartz: Randomized Dual Coordinate Ascent with Arbitrary Sampling »
  Zheng Qu · Peter Richtarik · Tong Zhang