Shay Vargaftik

7 papers · 2021–2025 · 3 venues · across top CS/AI venues

Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.

Achievements

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🌍 Conference Polyglot · Bronze 🔥 Unstoppable · Bronze

Venues

ICML (3) NeurIPS (2) NSDI (2)

Top co-authors

Michael Mitzenmacher (5) Yaniv Ben-Itzhak (4) Amit Portnoy (3) Ran Ben-Basat (3) Ran Ben Basat (3) Gal Mendelson (2) Kevin Xu (1) Ertza Warraich (1) Yaniv Ben Itzhak (1) Gil Einziger (1)

Research topics

Machine Learning (5) Application Areas (5) Optimization & Theory · Machine Learning (5) Artificial Intelligence (3) Learning Paradigms · Artificial Intelligence (3) Deep Learning (2) Learning Paradigms · Machine Learning (1) Optimization & Theory · Deep Learning (1) Techniques (1)

Keywords

federated learning (4) distributed mean estimation (3) communication efficiency (3) gradient compression (3) distributed training (2) model compression (2) optimization algorithm (1) communication compression (1) stochastic quantization (1) runtime complexity (1) adaptive quantization (1) tail latency (1) cloud computing (1) cross-device setting (1) packet loss (1) downlink compression (1) one-bit compression (1) in-network aggregation (1) homomorphic compression (1) gradient drop (1)

Papers

OptiReduce: Resilient and Tail-Optimal AllReduce for Distributed Deep Learning in the Cloud NSDI 2025 Accelerating Federated Learning with Quick Distributed Mean Estimation ICML 2024 Optimal and Approximate Adaptive Stochastic Quantization NeurIPS 2024 THC: Accelerating Distributed Deep Learning Using Tensor Homomorphic Compression NSDI 2024 DoCoFL: Downlink Compression for Cross-Device Federated Learning ICML 2023 EDEN: Communication-Efficient and Robust Distributed Mean Estimation for Federated Learning ICML 2022 DRIVE: One-bit Distributed Mean Estimation NeurIPS 2021