Justin Romberg
14 papers · 2015–2024 · 6 conferences · across top CS/AI conferences
Achievements
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🏃 Academic Marathon (9) 🧭 Keyword Pioneer 🌉 Interdisciplinary Bridge 🌍 Conference Polyglot (6) 🐣 Hot Topic Early Bird
🏃
Academic Marathon
(9)
🧭
Keyword Pioneer
🐣
Hot Topic Early Bird
🗃️
Keyword Collector
(72)
💎
Century Club
(14)
🔥
Unstoppable
(6)
🚀
Conference Pioneer
Conferences
NIPS (8)
AISTATS (2)
ICML (1)
JMLR (1)
L4DC (1)
UAI (1)
Top co-authors
Keywords
sample complexity
(4)
low-rank matrix
(2)
entropy regularization
(2)
convex relaxation
(2)
sparse recovery
(2)
convex optimization
(2)
policy optimization
(1)
policy evaluation
(1)
multi-agent reinforcement learning
(1)
compressive sensing
(1)
statistical learning theory
(1)
function approximation
(1)
ridge regression
(1)
minimax optimization
(1)
temporal difference learning
(1)
robust reinforcement learning
(1)
distributed optimization
(1)
semidefinite programming
(1)
network pruning
(1)
distributed learning
(1)
Papers
Precise asymptotics of reweighted least-squares algorithms for linear diagonal networks
NIPS 2024
PETAL: Physics Emulation Through Averaged Linearizations for Solving Inverse Problems
NIPS 2023
Connected Superlevel Set in (Deep) Reinforcement Learning and its Application to Minimax Theorems
NIPS 2023
Regularized Gradient Descent Ascent for Two-Player Zero-Sum Markov Games
NIPS 2022
A decentralized policy gradient approach to multi-task reinforcement learning
UAI 2021
Sample complexity and effective dimension for regression on manifolds
NIPS 2020
Sample complexity bounds for localized sketching
AISTATS 2020
Convex Programming for Estimation in Nonlinear Recurrent Models
JMLR 2020
Finite-Time Performance of Distributed Two-Time-Scale Stochastic Approximation
L4DC 2020
Finite-Time Analysis of Distributed TD(0) with Linear Function Approximation on Multi-Agent Reinforcement Learning
ICML 2019
Decentralized sketching of low rank matrices
NIPS 2019
Net-Trim: Convex Pruning of Deep Neural Networks with Performance Guarantee
NIPS 2017
Phase Retrieval Meets Statistical Learning Theory: A Flexible Convex Relaxation
AISTATS 2017
Efficient Compressive Phase Retrieval with Constrained Sensing Vectors
NIPS 2015