Vyacheslav Kungurtsev
12 papers · 2019–2026 · 10 venues · across top CS/AI venues
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Achievements
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🌉 Interdisciplinary Bridge · Silver 🗺️ Taxonomy Completionist (31) 🌍 Conference Polyglot · Gold 🐣 Hot Topic Early Bird 🏃 Academic Marathon · Sprint
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The Questioner
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Unstoppable · Bronze
💎
Century Club · Bronze
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(10)
Optimization & Theory · Machine Learning
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(3)
Learning Types · Deep Learning
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federated learning
(3)
dataset distillation
(3)
diffusion model
(2)
stochastic gradient descent
(2)
image generation
(1)
curriculum learning
(1)
image classification
(1)
lifted inference
(1)
distributed learning
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neural network optimization
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minimax optimization
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risk minimization
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piecewise linear
(1)
singular value decomposition
(1)
maximum likelihood estimation
(1)
convergence analysis
(1)
free energy
(1)
distributed training
(1)
generative training
(1)
knowledge distillation
(1)
Papers
CONCORD: Concept-Informed Diffusion for Dataset Distillation
WACV 2026
Group Distributionally Robust Dataset Distillation with Risk Minimization
ICLR 2025
Efficient Dataset Distillation via Minimax Diffusion
CVPR 2024
Towards Diverse Device Heterogeneous Federated Learning via Task Arithmetic Knowledge Integration
NeurIPS 2024
Unlocking the Potential of Federated Learning: The Symphony of Dataset Distillation via Deep Generative Latents
ECCV 2024
Efficient Distribution Similarity Identification in Clustered Federated Learning via Principal Angles between Client Data Subspaces
AAAI 2023
When Do Curricula Work in Federated Learning?
ICCV 2023
Mean-field Analysis of Piecewise Linear Solutions for Wide ReLU Networks
JMLR 2022
Asynchronous Optimization Methods for Efficient Training of Deep Neural Networks with Guarantees
AAAI 2021
Elastic Consistency: A Practical Consistency Model for Distributed Stochastic Gradient Descent
AAAI 2021
Lifted Weight Learning of Markov Logic Networks (Revisited One More Time)
PGM 2020
Lifted Weight Learning of Markov Logic Networks Revisited
AISTATS 2019