Mitzenmacher, Michael

22 publications

ICLR 2025 Don’T Stop Me Now: Embedding Based Scheduling for LLMs Rana Shahout, Eran Malach, Chunwei Liu, Weifan Jiang, Minlan Yu, Michael Mitzenmacher

NeurIPS 2025 Fast Inference for Augmented Large Language Models Rana Shahout, Cong Liang, Shiji Xin, Qianru Lao, Yong Cui, Minlan Yu, Michael Mitzenmacher

ICML 2024 Accelerating Federated Learning with Quick Distributed Mean Estimation Ran Ben-Basat, Shay Vargaftik, Amit Portnoy, Gil Einziger, Yaniv Ben-Itzhak, Michael Mitzenmacher

ICMLW 2024 Janus: An Efficient and Expressive Subquadratic Architecture for Modeling Biological Sequences Krithik Ramesh, Sameed Muneeb Siddiqui, Michael Mitzenmacher, Pardis Sabeti

NeurIPS 2024 Optimal and Approximate Adaptive Stochastic Quantization Ran Ben Basat, Yaniv Ben-Itzhak, Michael Mitzenmacher, Shay Vargaftik

NeurIPS 2024 SkipPredict: When to Invest in Predictions for Scheduling Rana Shahout, Michael Mitzenmacher

TMLR 2024 Tabula: Efficiently Computing Nonlinear Activation Functions for Secure Neural Network Inference Max Lam, Michael Mitzenmacher, Vijay Janapa Reddi, Gu-Yeon Wei, David Brooks

ECML-PKDD 2022 Algorithmic Tools for Understanding the Motif Structure of Networks Tianyi Chen, Brian Matejek, Michael Mitzenmacher, Charalampos E. Tsourakakis

ICML 2022 EDEN: Communication-Efficient and Robust Distributed Mean Estimation for Federated Learning Shay Vargaftik, Ran Ben Basat, Amit Portnoy, Gal Mendelson, Yaniv Ben Itzhak, Michael Mitzenmacher

NeurIPS 2021 DRIVE: One-Bit Distributed Mean Estimation Shay Vargaftik, Ran Ben-Basat, Amit Portnoy, Gal Mendelson, Yaniv Ben-Itzhak, Michael Mitzenmacher

ICML 2021 Gradient Disaggregation: Breaking Privacy in Federated Learning by Reconstructing the User Participant Matrix Maximilian Lam, Gu-Yeon Wei, David Brooks, Vijay Janapa Reddi, Michael Mitzenmacher

ICLR 2021 Partitioned Learned Bloom Filters Kapil Vaidya, Eric Knorr, Michael Mitzenmacher, Tim Kraska

ICML 2021 Putting the “Learning" into Learning-Augmented Algorithms for Frequency Estimation Elbert Du, Franklyn Wang, Michael Mitzenmacher

AISTATS 2020 Prophets, Secretaries, and Maximizing the Probability of Choosing the Best Hossein Esfandiari, MohammadTaghi Hajiaghayi, Brendan Lucier, Michael Mitzenmacher

AAAI 2019 Online Pandora's Boxes and Bandits Hossein Esfandiari, Mohammad Taghi Hajiaghayi, Brendan Lucier, Michael Mitzenmacher

NeurIPS 2018 A Bayesian Nonparametric View on Count-Min Sketch Diana Cai, Michael Mitzenmacher, Ryan P. Adams

NeurIPS 2018 A Model for Learned Bloom Filters and Optimizing by Sandwiching Michael Mitzenmacher

ICML 2018 Weightless: Lossy Weight Encoding for Deep Neural Network Compression Brandon Reagan, Udit Gupta, Bob Adolf, Michael Mitzenmacher, Alexander Rush, Gu-Yeon Wei, David Brooks

JMLR 2016 Measuring Dependence Powerfully and Equitably Yakir A. Reshef, David N. Reshef, Hilary K. Finucane, Pardis C. Sabeti, Michael Mitzenmacher

NeurIPS 2016 Quantized Random Projections and Non-Linear Estimation of Cosine Similarity Ping Li, Michael Mitzenmacher, Martin Slawski

ICML 2014 Coding for Random Projections Ping Li, Michael Mitzenmacher, Anshumali Shrivastava

AAAI 2002 Human-Guided Tabu Search Gunnar W. Klau, Neal Lesh, Joe Marks, Michael Mitzenmacher