Michael Mitzenmacher
18 papers · 2014–2025 · 7 conferences · across top CS/AI conferences
Achievements
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π Conference Polyglot (7) π Interdisciplinary Bridge π§ Keyword Pioneer π£ Hot Topic Early Bird π Academic Marathon (11)
π
Renaissance Researcher
(7)
πΊοΈ
Taxonomy Completionist
(35)
π
Conference Polyglot
(7)
π
Triple Crown
π
Grand Slam
π₯
Unstoppable
(5)
π
Century Club
(18)
π
Conference Pioneer
ποΈ
Keyword Collector
(79)
Conferences
ICML (6)
NIPS (6)
ICLR (2)
AAAI (1)
AISTATS (1)
JMLR (1)
NSDI (1)
Top co-authors
Research topics
Keywords
federated learning
(3)
gradient compression
(3)
online algorithm
(2)
count-min sketch
(2)
model compression
(2)
random projection
(2)
distributed mean estimation
(2)
sequential decision
(2)
communication efficiency
(2)
bayesian nonparametrics
(1)
posterior distribution
(1)
online decision making
(1)
mutual information
(1)
vector quantization
(1)
dirichlet process
(1)
bayesian inference
(1)
robust estimation
(1)
variational inference
(1)
neural network compression
(1)
independence testing
(1)
Papers
DONβT 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 βLearning" 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 Pandoraβs 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