Παρακολούθηση
Avetik Karagulyan
Avetik Karagulyan
CNRS, L2S
Η διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα kaust.edu.sa - Αρχική σελίδα
Τίτλος
Παρατίθεται από
Παρατίθεται από
Έτος
User-friendly guarantees for the Langevin Monte Carlo with inaccurate gradient
AS Dalalyan, AG Karagulyan
Stochastic Processes and their Applications, 2017
3522017
Bounding the error of discretized Langevin algorithms for non-strongly log-concave targets
AS Dalalyan, A Karagulyan, L Riou-Durand
Journal of Machine Learning Research 23 (235), 1-38, 2022
552022
Convergence of Stein variational gradient descent under a weaker smoothness condition
L Sun, A Karagulyan, P Richtarik
International Conference on Artificial Intelligence and Statistics, 3693-3717, 2023
212023
Penalized Langevin dynamics with vanishing penalty for smooth and log-concave targets
A Karagulyan, AS Dalalyan
Advances in Neural Information Processing Systems, 2020, 2020
132020
Existence of positive solutions for an approximation of stationary mean-field games
N Almayouf, E Bachini, A Chapouto, R Ferreira, D Gomes, D Jordão, ...
Involve, a Journal of Mathematics 10 (3), 473-493, 2016
102016
Det-cgd: Compressed gradient descent with matrix stepsizes for non-convex optimization
H Li, A Karagulyan, P Richtárik
International Conference on Learning Representations 2024, 2024
52024
ELF: Federated langevin algorithms with primal, dual and bidirectional compression
A Karagulyan, P Richtárik
arXiv preprint arXiv:2303.04622, 2023
52023
SPAM: Stochastic Proximal Point Method with Momentum Variance Reduction for Non-convex Cross-Device Federated Learning
A Karagulyan, E Shulgin, A Sadiev, P Richtárik
arXiv preprint arXiv:2405.20127, 2024
42024
Langevin Monte Carlo for strongly log-concave distributions: Randomized midpoint revisited
L Yu, A Karagulyan, A Dalalyan
International Conference on Learning Representations 2024, 2023
32023
Sampling with the Langevin Monte-Carlo
A Karagulyan
Institut Polytechnique de Paris, 2021
22021
Applying statistical learning theory to deep learning
C Gerbelot, A Karagulyan, S Karp, K Ravichandran, M Stern, N Srebro
Journal of Statistical Mechanics: Theory and Experiment 2024 (10), 104003, 2024
12024
Variance reduced distributed non-convex optimization using matrix stepsizes
H Li, A Karagulyan, P Richtárik
arXiv, 2024
12024
Non-asymptotic guarantees for sampling by stochastic gradient descent
AG Karagulyan
Journal of Contemporary Mathematical Analysis (Armenian Academy of Sciences …, 2019
12019
MARINA Meets Matrix Stepsizes: Variance Reduced Distributed Non-convex Optimization
H Li, A Karagulyan, P Richtárik
arXiv preprint arXiv:2310.04614, 2023
2023
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