Adversarially Robust Submodular Maximization under Knapsack Constraints. - Dmitrii Avdiukhin; Slobodan Mitrovic; Grigory Yaroslavtsev; Samson Zhou (KDD, 2019)

Multi-Dimensional Balanced Graph Partitioning via Projected Gradient Descent. - Dmitrii Avdiukhin; Sergey Pupyrev; Grigory Yaroslavtsev (Proc. VLDB Endow., 2019)

"Bring Your Own Greedy"+Max: Near-Optimal 1/2-Approximations for Submodular Knapsack. - Grigory Yaroslavtsev; Samson Zhou; Dmitrii Avdiukhin (AISTATS, 2020)

Objective-Based Hierarchical Clustering of Deep Embedding Vectors. - Stanislav Naumov; Grigory Yaroslavtsev; Dmitrii Avdiukhin (AAAI, 2021)

Federated Learning under Arbitrary Communication Patterns. - Dmitrii Avdiukhin; Shiva Prasad Kasiviswanathan (ICML, 2021)

Escaping Saddle Points with Compressed SGD. - Dmitrii Avdiukhin; Grigory Yaroslavtsev (NeurIPS, 2021)

Tree Learning: Optimal Sample Complexity and Algorithms. - Dmitrii Avdiukhin; Grigory Yaroslavtsev; Danny Vainstein; Orr Fischer; Sauman Das; Faraz Mirza (AAAI, 2023)

HOUDINI: Escaping from Moderately Constrained Saddles. - Dmitrii Avdiukhin; Grigory Yaroslavtsev (IJCAI, 2023)

Tree Learning: Optimal Algorithms and Sample Complexity. - Dmitrii Avdiukhin; Grigory Yaroslavtsev; Danny Vainstein; Orr Fischer; Sauman Das; Faraz Mirza (CoRR, 2023)

Approximation Scheme for Weighted Metric Clustering via Sherali-Adams. - Dmitrii Avdiukhin; Vaggos Chatziafratis; Konstantin Makarychev; Grigory Yaroslavtsev (AAAI, 2024)

Optimal Sample Complexity of Contrastive Learning. - Noga Alon; Dmitrii Avdiukhin; Dor Elboim; Orr Fischer; Grigory Yaroslavtsev (ICLR, 2024)

Embedding Dimension of Contrastive Learning and k-Nearest Neighbors. - Dmitrii Avdiukhin; Vaggos Chatziafratis; Orr Fischer; Grigory Yaroslavtsev (NeurIPS, 2024)

Noise is All You Need: Private Second-Order Convergence of Noisy SGD. - Dmitrii Avdiukhin; Michael Dinitz; Chenglin Fan; Grigory Yaroslavtsev (CoRR, 2024)

Federated Learning Clients Clustering with Adaptation to Data Drifts. - Minghao Li 003; Dmitrii Avdiukhin; Rana Shahout; Nikita Ivkin; Vladimir Braverman; Minlan Yu (CoRR, 2024)