Michael Mitzenmacher

18 papers · 2014–2025 · 7 conferences · across top CS/AI conferences

Achievements

🏃 Academic Marathon (11) 🐝 Cross-Pollinator (11) 🌉 Interdisciplinary Bridge 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌈 Renaissance Researcher (7) 🗺️ Taxonomy Completionist (35) 🌍 Conference Polyglot (7) 👑 Triple Crown 🏆 Grand Slam 🔥 Unstoppable (5) 💎 Century Club (18) 🚀 Conference Pioneer 🗃️ Keyword Collector (79)

Conferences

ICML (6) NIPS (6) ICLR (2) AAAI (1) AISTATS (1) JMLR (1) NSDI (1)

Top co-authors

Shay Vargaftik (5) Amit Portnoy (3) Yaniv Ben-Itzhak (3) Ran Ben Basat (3) Ran Ben-Basat (3) Hossein Esfandiari (2) Gu-Yeon Wei (2) Minlan Yu (2) Brendan Lucier (2) Ping Li (2)

Research topics

Keywords

federated learning (3) gradient compression (3) online algorithm (2) count-min sketch (2) model compression (2) communication efficiency (2) distributed mean estimation (2) random projection (2) sequential decision (2) probabilistic modeling (1) mutual information (1) posterior distribution (1) vector quantization (1) nonparametric statistics (1) dirichlet process (1) online decision making (1) maximum likelihood estimation (1) bayesian inference (1) neural network compression (1) robust estimation (1)

Papers

DON’T STOP ME NOW: EMBEDDING BASED SCHEDULING FOR LLMS ICLR 2025

THC: Accelerating Distributed Deep Learning Using Tensor Homomorphic Compression NSDI 2024

Optimal and Approximate Adaptive Stochastic Quantization NIPS 2024

SkipPredict: When to Invest in Predictions for Scheduling NIPS 2024

Accelerating Federated Learning with Quick Distributed Mean Estimation ICML 2024

EDEN: Communication-Efficient and Robust Distributed Mean Estimation for Federated Learning ICML 2022

DRIVE: One-bit Distributed Mean Estimation NIPS 2021

Partitioned Learned Bloom Filters ICLR 2021

Putting the “Learning" into Learning-Augmented Algorithms for Frequency Estimation ICML 2021

Gradient Disaggregation: Breaking Privacy in Federated Learning by Reconstructing the User Participant Matrix ICML 2021

Prophets, Secretaries, and Maximizing the Probability of Choosing the Best AISTATS 2020

Online Pandora’s Boxes and Bandits AAAI 2019

A Model for Learned Bloom Filters and Optimizing by Sandwiching NIPS 2018

Weightless: Lossy weight encoding for deep neural network compression ICML 2018

A Bayesian Nonparametric View on Count-Min Sketch NIPS 2018

Quantized Random Projections and Non-Linear Estimation of Cosine Similarity NIPS 2016

Measuring Dependence Powerfully and Equitably JMLR 2016

Coding for Random Projections ICML 2014