Diggavi, Suhas

15 publications

AISTATS 2025 ADEPT: Hierarchical Bayes Approach to Personalized Federated Unsupervised Learning Kaan Ozkara, Bruce Huang, Ruida Zhou, Suhas Diggavi

NeurIPSW 2024 Transformers Learn to Compress Variable-Order Markov Chains In-Context Ruida Zhou, Chao Tian, Suhas Diggavi

ICLR 2023 A Statistical Framework for Personalized Federated Learning and Estimation: Theory, Algorithms, and Privacy Kaan Ozkara, Antonious M. Girgis, Deepesh Data, Suhas Diggavi

ICMLW 2023 Distributed Mean Estimation for Multi-Message Shuffled Privacy Antonious M. Girgis, Suhas Diggavi

NeurIPS 2023 FOCAL: Contrastive Learning for Multimodal Time-Series Sensing Signals in Factorized Orthogonal Latent Space Shengzhong Liu, Tomoyoshi Kimura, Dongxin Liu, Ruijie Wang, Jinyang Li, Suhas Diggavi, Mani Srivastava, Tarek Abdelzaher

NeurIPS 2022 On Leave-One-Out Conditional Mutual Information for Generalization Mohamad Rida Rammal, Alessandro Achille, Aditya Golatkar, Suhas Diggavi, Stefano Soatto

AISTATS 2021 Group Testing for Connected Communities Pavlos Nikolopoulos, Sundara Rajan Srinivasavaradhan, Tao Guo, Christina Fragouli, Suhas Diggavi

AISTATS 2021 Shuffled Model of Differential Privacy in Federated Learning Antonious Girgis, Deepesh Data, Suhas Diggavi, Peter Kairouz, Ananda Theertha Suresh

ICML 2021 Byzantine-Resilient High-Dimensional SGD with Local Iterations on Heterogeneous Data Deepesh Data, Suhas Diggavi

NeurIPS 2021 QuPeD: Quantized Personalization via Distillation with Applications to Federated Learning Kaan Ozkara, Navjot Singh, Deepesh Data, Suhas Diggavi

NeurIPS 2021 Renyi Differential Privacy of the Subsampled Shuffle Model in Distributed Learning Antonious Girgis, Deepesh Data, Suhas Diggavi

NeurIPS 2019 Qsparse-Local-SGD: Distributed SGD with Quantization, Sparsification and Local Computations Debraj Basu, Deepesh Data, Can Karakus, Suhas Diggavi

JMLR 2019 Redundancy Techniques for Straggler Mitigation in Distributed Optimization and Learning Can Karakus, Yifan Sun, Suhas Diggavi, Wotao Yin

NeurIPS 2017 Straggler Mitigation in Distributed Optimization Through Data Encoding Can Karakus, Yifan Sun, Suhas Diggavi, Wotao Yin

NeurIPS 2011 Randomized Algorithms for Comparison-Based Search Dominique Tschopp, Suhas Diggavi, Payam Delgosha, Soheil Mohajer