Mike Rabbat
8 papers · 2019–2024 · 4 venues · across top CS/AI venues
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Achievements
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🌍 Conference Polyglot · Bronze 🏃 Academic Marathon · Sprint 🌉 Interdisciplinary Bridge · Bronze 🗺️ Taxonomy Completionist (17) 🐣 Hot Topic Early Bird
🌈
Renaissance Researcher
(5)
Venues
Top co-authors
Research topics
Machine Learning
(8)
Optimization & Theory · Machine Learning
(6)
Artificial Intelligence
(4)
Learning Paradigms · Artificial Intelligence
(3)
Deep Learning
(2)
Mathematics & Optimization
(2)
Application Areas
(2)
Learning Paradigms · Machine Learning
(2)
Optimization
(2)
Optimization & Theory · Deep Learning
(2)
Natural Language Processing
(1)
Reinforcement Learning
(1)
Security & Privacy
(1)
Applications
(1)
Core AI
(1)
Keywords
federated learning
(3)
distributed optimization
(2)
differential privacy
(2)
gradient descent
(2)
convergence analysis
(2)
distributed learning
(2)
generalization error
(1)
stochastic approximation
(1)
partial observability
(1)
secure aggregation
(1)
communication efficiency
(1)
empirical risk
(1)
strongly convex optimization
(1)
hessian eigenvalue
(1)
implicit bia
(1)
next-token prediction
(1)
non-iid data
(1)
client-server architecture
(1)
reversal curse
(1)
nesterov acceleration
(1)
Papers
The Factorization Curse: Which Tokens You Predict Underlie the Reversal Curse and More
NeurIPS 2024
Federated Learning with Buffered Asynchronous Aggregation
AISTATS 2022
Federated Learning with Partial Model Personalization
ICML 2022
Privacy-aware compression for federated data analysis
UAI 2022
Learning with Gradient Descent and Weakly Convex Losses
AISTATS 2021
On the Convergence of Nesterov’s Accelerated Gradient Method in Stochastic Settings
ICML 2020
Stochastic Gradient Push for Distributed Deep Learning
ICML 2019
TarMAC: Targeted Multi-Agent Communication
ICML 2019