PPaperPicks

Peter Richtárik

King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia

32 papers at tracked venues · 24 at CORE A* · active 2024–2025

DBLP profile ↗ORCID 0000-0003-4380-5848 ↗Google Scholar ↗Homepage ↗

Venues

NeurIPS ×12ICLR ×7ICML ×4UAI ×3AISTATS ×2AAAI ×1ECAI ×1ECML-PKDD ×1NAACL ×1

Frequent coauthors

Eduard Gorbunov
×7
Grigory Malinovsky
×6
Samuel Horváth
×5
Alexander Tyurin
×5
Arto Maranjyan
×4
Abdurakhmon Sadiev
×4
Yury Demidovich
×3
Ivan Ilin
×3
Dan Alistarh
×3
Kaja Gruntkowska
×3
Konstantin Burlachenko
×3
Sarit Khirirat
×2

Papers

  1. ATA: Adaptive Task Allocation for Efficient Resource Management in Distributed Machine Learning
    ICML 2025 ·
    Arto Maranjyan
    ,
    El Mehdi Saad
    , Peter Richtárik,
    Francesco Orabona
  2. Collaborative Value Function Estimation Under Model Mismatch: A Federated Temporal Difference Analysis
    ECML-PKDD 2025 ·
    Ali Beikmohammadi
    ,
    Sarit Khirirat
    , Peter Richtárik,
    Sindri Magnússon
  3. Correlated Quantization for Faster Nonconvex Distributed Optimization
    UAI 2025 ·
    Andrei Panferov
    ,
    Yury Demidovich
    ,
    Ahmad Rammal
    , Peter Richtárik
  4. ELF: Federated Langevin Algorithms with Primal, Dual and Bidirectional Compression
    UAI 2025 ·
    Avetik G. Karagulyan
    , Peter Richtárik
  5. Error Feedback under (L0, L1)-Smoothness: Normalization and Momentum
    NeurIPS 2025 ·
    Sarit Khirirat
    ,
    Abdurakhmon Sadiev
    ,
    Artem Riabinin
    ,
    Eduard Gorbunov
    , Peter Richtárik
  6. HIGGS: Pushing the Limits of Large Language Model Quantization via the Linearity Theorem
    NAACL 2025 ·
    Vladimir Malinovskii
    ,
    Andrei Panferov
    ,
    Ivan Ilin
    ,
    Han Guo
    , Peter Richtárik,
    Dan Alistarh
  7. LoCoDL: Communication-Efficient Distributed Learning with Local Training and Compression
    ICLR 2025 ·
    Laurent Condat
    ,
    Arto Maranjyan
    , Peter Richtárik
  8. Local Curvature Descent: Squeezing More Curvature out of Standard and Polyak Gradient Descent
    NeurIPS 2025 · Peter Richtárik,
    Simone Maria Giancola
    ,
    Dymitr Lubczyk
    ,
    Robin Yadav
  9. MAST: model-agnostic sparsified training
    ICLR 2025 ·
    Yury Demidovich
    ,
    Grigory Malinovsky
    ,
    Egor Shulgin
    , Peter Richtárik
  10. Methods for Convex (L0, L1)-Smooth Optimization: Clipping, Acceleration, and Adaptivity
    ICLR 2025 ·
    Eduard Gorbunov
    ,
    Nazarii Tupitsa
    ,
    Sayantan Choudhury
    ,
    Alen Aliev
    , Peter Richtárik,
    Samuel Horváth
    ,
    Martin Takác
  11. Methods with Local Steps and Random Reshuffling for Generally Smooth Non-Convex Federated Optimization
    ICLR 2025 ·
    Yury Demidovich
    ,
    Petr Ostroukhov
    ,
    Grigory Malinovsky
    ,
    Samuel Horváth
    ,
    Martin Takác
    , Peter Richtárik,
    Eduard Gorbunov
  12. MindFlayer SGD: Efficient Parallel SGD in the Presence of Heterogeneous and Random Worker Compute Times
    UAI 2025 ·
    Arto Maranjyan
    ,
    Omar Shaikh Omar
    , Peter Richtárik
  13. Quantize Once, Train Fast: Allreduce-Compatible Compression with Provable Guarantees
    ECAI 2025 ·
    Jihao Xin
    ,
    Marco Canini
    , Peter Richtárik,
    Samuel Horváth
  14. Ringmaster ASGD: The First Asynchronous SGD with Optimal Time Complexity
    ICML 2025 ·
    Arto Maranjyan
    ,
    Alexander Tyurin
    , Peter Richtárik
  15. Second-order Optimization under Heavy-Tailed Noise: Hessian Clipping and Sample Complexity Limits
    NeurIPS 2025 ·
    Abdurakhmon Sadiev
    , Peter Richtárik,
    Ilyas Fatkhullin
  16. Byzantine Robustness and Partial Participation Can Be Achieved at Once: Just Clip Gradient Differences
    NeurIPS 2024 ·
    Grigory Malinovsky
    , Peter Richtárik,
    Samuel Horváth
    ,
    Eduard Gorbunov
  17. Communication Compression for Byzantine Robust Learning: New Efficient Algorithms and Improved Rates
    AISTATS 2024 ·
    Ahmad Rammal
    ,
    Kaja Gruntkowska
    ,
    Nikita Fedin
    ,
    Eduard Gorbunov
    , Peter Richtárik
  18. Det-CGD: Compressed Gradient Descent with Matrix Stepsizes for Non-Convex Optimization
    ICLR 2024 ·
    Hanmin Li
    ,
    Avetik G. Karagulyan
    , Peter Richtárik
  19. Don't Compress Gradients in Random Reshuffling: Compress Gradient Differences
    NeurIPS 2024 ·
    Abdurakhmon Sadiev
    ,
    Grigory Malinovsky
    ,
    Eduard Gorbunov
    ,
    Igor Sokolov
    ,
    Ahmed Khaled
    ,
    Konstantin Burlachenko
    , Peter Richtárik
  20. Error Feedback Reloaded: From Quadratic to Arithmetic Mean of Smoothness Constants
    ICLR 2024 · Peter Richtárik,
    Elnur Gasanov
    ,
    Konstantin Burlachenko
  21. FedP3: Federated Personalized and Privacy-friendly Network Pruning under Model Heterogeneity
    ICLR 2024 ·
    Kai Yi
    ,
    Nidham Gazagnadou
    , Peter Richtárik,
    Lingjuan Lyu
  22. Freya PAGE: First Optimal Time Complexity for Large-Scale Nonconvex Finite-Sum Optimization with Heterogeneous Asynchronous Computations
    NeurIPS 2024 ·
    Alexander Tyurin
    ,
    Kaja Gruntkowska
    , Peter Richtárik
  23. High-Probability Convergence for Composite and Distributed Stochastic Minimization and Variational Inequalities with Heavy-Tailed Noise
    ICML 2024 ·
    Eduard Gorbunov
    ,
    Abdurakhmon Sadiev
    ,
    Marina Danilova
    ,
    Samuel Horváth
    ,
    Gauthier Gidel
    ,
    Pavel E. Dvurechensky
    ,
    Alexander V. Gasnikov
    , Peter Richtárik
  24. Improving the Worst-Case Bidirectional Communication Complexity for Nonconvex Distributed Optimization under Function Similarity
    NeurIPS 2024 ·
    Kaja Gruntkowska
    ,
    Alexander Tyurin
    , Peter Richtárik
  25. MicroAdam: Accurate Adaptive Optimization with Low Space Overhead and Provable Convergence
    NeurIPS 2024 ·
    Ionut-Vlad Modoranu
    ,
    Mher Safaryan
    ,
    Grigory Malinovsky
    ,
    Eldar Kurtic
    ,
    Thomas Robert
    , Peter Richtárik,
    Dan Alistarh
  26. Minibatch Stochastic Three Points Method for Unconstrained Smooth Minimization
    AAAI 2024 ·
    Soumia Boucherouite
    ,
    Grigory Malinovsky
    , Peter Richtárik,
    El Houcine Bergou
  27. On the Optimal Time Complexities in Decentralized Stochastic Asynchronous Optimization
    NeurIPS 2024 ·
    Alexander Tyurin
    , Peter Richtárik
  28. PV-Tuning: Beyond Straight-Through Estimation for Extreme LLM Compression
    NeurIPS 2024 ·
    Vladimir Malinovskii
    ,
    Denis Mazur
    ,
    Ivan Ilin
    ,
    Denis Kuznedelev
    ,
    Konstantin Burlachenko
    ,
    Kai Yi
    ,
    Dan Alistarh
    , Peter Richtárik
  29. Shadowheart SGD: Distributed Asynchronous SGD with Optimal Time Complexity Under Arbitrary Computation and Communication Heterogeneity
    NeurIPS 2024 ·
    Alexander Tyurin
    ,
    Marta Pozzi
    ,
    Ivan Ilin
    , Peter Richtárik
  30. The Power of Extrapolation in Federated Learning
    NeurIPS 2024 ·
    Hanmin Li
    ,
    Kirill Acharya
    , Peter Richtárik
  31. Towards a Better Theoretical Understanding of Independent Subnetwork Training
    ICML 2024 ·
    Egor Shulgin
    , Peter Richtárik
  32. Understanding Progressive Training Through the Framework of Randomized Coordinate Descent
    AISTATS 2024 ·
    Rafal Szlendak
    ,
    Elnur Gasanov
    , Peter Richtárik