Communication trade-offs for Local-SGD with large step size. - Aymeric Dieuleveut; Kumar Kshitij Patel (NeurIPS, 2019)

Communication trade-offs for synchronized distributed SGD with large step size. - Kumar Kshitij Patel; Aymeric Dieuleveut (CoRR, 2019)

Corruption-tolerant bandit learning. - Sayash Kapoor; Kumar Kshitij Patel; Purushottam Kar (Mach. Learn., 2019)

Don't Use Large Mini-batches, Use Local SGD. - Tao Lin 004; Sebastian U. Stich; Kumar Kshitij Patel; Martin Jaggi (ICLR, 2020)

Is Local SGD Better than Minibatch SGD? - Blake E. Woodworth; Kumar Kshitij Patel; Sebastian U. Stich; Zhen Dai; Brian Bullins; H. Brendan McMahan; Ohad Shamir; Nathan Srebro (ICML, 2020)

Minibatch vs Local SGD for Heterogeneous Distributed Learning. - Blake E. Woodworth; Kumar Kshitij Patel; Nati Srebro (NeurIPS, 2020)

A Stochastic Newton Algorithm for Distributed Convex Optimization. - Brian Bullins; Kumar Kshitij Patel; Ohad Shamir; Nathan Srebro; Blake E. Woodworth (NeurIPS, 2021)

Towards Optimal Communication Complexity in Distributed Non-Convex Optimization. - Kumar Kshitij Patel; Lingxiao Wang; Blake E. Woodworth; Brian Bullins; Nati Srebro (NeurIPS, 2022)

Federated Online and Bandit Convex Optimization. - Kumar Kshitij Patel; Lingxiao Wang; Aadirupa Saha; Nathan Srebro (ICML, 2023)

On the Effect of Defections in Federated Learning and How to Prevent Them. - Minbiao Han; Kumar Kshitij Patel; Han Shao; Lingxiao Wang (CoRR, 2023)

Federated Online and Bandit Convex Optimization. - Kumar Kshitij Patel; Lingxiao Wang; Aadirupa Saha; Nati Sebro (CoRR, 2023)

The Limits and Potentials of Local SGD for Distributed Heterogeneous Learning with Intermittent Communication. - Kumar Kshitij Patel; Margalit Glasgow; Ali Zindari; Lingxiao Wang; Sebastian U. Stich; Ziheng Cheng; Nirmit Joshi; Nathan Srebro (COLT, 2024)

Online Combinatorial Optimization with Group Fairness Constraints. - Negin Golrezaei; Rad Niazadeh; Kumar Kshitij Patel; Fransisca Susan (IJCAI, 2024)

The Limitations of Model Retraining in the Face of Performativity. - Anmol Kabra; Kumar Kshitij Patel (CoRR, 2024)

Approaching Deep Learning through the Spectral Dynamics of Weights. - David Yunis; Kumar Kshitij Patel; Samuel Wheeler; Pedro Savarese; Gal Vardi; Karen Livescu; Michael Maire; Matthew R. Walter (CoRR, 2024)

Personalized Federated Training of Diffusion Models with Privacy Guarantees. - Kumar Kshitij Patel; Weitong Zhang; Lingxiao Wang (CoRR, 2025)

What Makes Local Updates Effective: The Role of Data Heterogeneity and Smoothness. - Kumar Kshitij Patel (CoRR, 2025)