Dmitry Kovalev
26 papers · 2018–2025 · 6 conferences · across top CS/AI conferences
Achievements
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π Academic Marathon (7) π Conference Polyglot (6) π Interdisciplinary Bridge π§ Keyword Pioneer π Cross-Pollinator (3)
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Conference Polyglot
(6)
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(18)
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Topic Evolution
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Keyword Champion
(3)
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Trend Setter
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Keyword Collector
(98)
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Prolific Year
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Century Club
(26)
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The Questioner
Conferences
NIPS (13)
ICML (6)
AISTATS (3)
ICLR (2)
ALT (1)
UAI (1)
Top co-authors
Keywords
convex optimization
(10)
decentralized optimization
(7)
communication complexity
(6)
distributed learning
(6)
optimal algorithm
(5)
distributed optimization
(5)
variance reduction
(5)
saddle-point problems
(3)
stochastic optimization
(3)
linear convergence
(3)
oracle complexity
(3)
time-varying network
(3)
federated learning
(3)
communication compression
(2)
primal-dual algorithm
(2)
variational inequality
(2)
network optimization
(2)
gradient descent
(2)
coordinate descent
(2)
strong convexity
(2)
Papers
An Optimal Algorithm for Strongly Convex Min-Min Optimization
UAI 2025
Decentralized Optimization with Coupled Constraints
ICLR 2025
On Linear Convergence in Smooth Convex-Concave Bilinearly-Coupled Saddle-Point Optimization: Lower Bounds and Optimal Algorithms
ICML 2025
Lower Bounds and Optimal Algorithms for Non-Smooth Convex Decentralized Optimization over Time-Varying Networks
NIPS 2024
Is Consensus Acceleration Possible in Decentralized Optimization over Slowly Time-Varying Networks?
ICML 2023
Optimal Algorithms for Decentralized Stochastic Variational Inequalities
NIPS 2022
Optimal Gradient Sliding and its Application to Optimal Distributed Optimization Under Similarity
NIPS 2022
The First Optimal Acceleration of High-Order Methods in Smooth Convex Optimization
NIPS 2022
An Optimal Algorithm for Strongly Convex Minimization under Affine Constraints
AISTATS 2022
IntSGD: Adaptive Floatless Compression of Stochastic Gradients
ICLR 2022
The First Optimal Algorithm for Smooth and Strongly-Convex-Strongly-Concave Minimax Optimization
NIPS 2022
Accelerated Primal-Dual Gradient Method for Smooth and Convex-Concave Saddle-Point Problems with Bilinear Coupling
NIPS 2022
Communication Acceleration of Local Gradient Methods via an Accelerated Primal-Dual Algorithm with an Inexact Prox
NIPS 2022
ADOM: Accelerated Decentralized Optimization Method for Time-Varying Networks
ICML 2021
A Linearly Convergent Algorithm for Decentralized Optimization: Sending Less Bits for Free!
AISTATS 2021
Lower Bounds and Optimal Algorithms for Smooth and Strongly Convex Decentralized Optimization Over Time-Varying Networks
NIPS 2021
Revisiting Stochastic Extragradient
AISTATS 2020
Optimal and Practical Algorithms for Smooth and Strongly Convex Decentralized Optimization
NIPS 2020
Linearly Converging Error Compensated SGD
NIPS 2020
Donβt Jump Through Hoops and Remove Those Loops: SVRG and Katyusha are Better Without the Outer Loop
ALT 2020
Variance Reduced Coordinate Descent with Acceleration: New Method With a Surprising Application to Finite-Sum Problems
ICML 2020
Acceleration for Compressed Gradient Descent in Distributed and Federated Optimization
ICML 2020
From Local SGD to Local Fixed-Point Methods for Federated Learning
ICML 2020
RSN: Randomized Subspace Newton
NIPS 2019
Stochastic Proximal Langevin Algorithm: Potential Splitting and Nonasymptotic Rates
NIPS 2019
Stochastic Spectral and Conjugate Descent Methods
NIPS 2018