Adrian Vladu
9 papers · 2017–2023 · 4 venues · across top CS/AI venues
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Achievements
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🐣 Hot Topic Early Bird 🌍 Conference Polyglot · Bronze 🏃 Academic Marathon · Sprint 🌉 Interdisciplinary Bridge · Bronze 🗺️ Taxonomy Completionist (15)
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Grand Slam
🚀
Conference Pioneer
Venues
Top co-authors
Research topics
Keywords
convex optimization
(4)
model compression
(2)
stochastic gradient
(1)
robust optimization
(1)
adversarial robustness
(1)
variational inequality
(1)
constrained optimization
(1)
discrete optimization
(1)
sparse approximation
(1)
distributed training
(1)
maximum flow
(1)
parametric optimization
(1)
adversarial attack
(1)
support vector machine
(1)
convergence guarantee
(1)
bandit optimization
(1)
deep neural network
(1)
accelerated method
(1)
adaptive gradient method
(1)
weight pruning
(1)
Papers
CrAM: A Compression-Aware Minimizer
ICLR 2023
Quantized Distributed Training of Large Models with Convergence Guarantees
ICML 2023
AC/DC: Alternating Compressed/DeCompressed Training of Deep Neural Networks
NeurIPS 2021
Adaptive Gradient Methods for Constrained Convex Optimization and Variational Inequalities
AAAI 2021
Decomposable Submodular Function Minimization via Maximum Flow
ICML 2021
Projection-Free Bandit Optimization with Privacy Guarantees
AAAI 2021
Improved Convergence for ℓ_1 and ℓ_∞ Regression via Iteratively Reweighted Least Squares
ICML 2019
Towards Deep Learning Models Resistant to Adversarial Attacks
ICLR 2018
Tight Bounds for Approximate Carathéodory and Beyond
ICML 2017