Donald Goldfarb
11 papers · 2010–2023 · 5 venues · across top CS/AI venues
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Achievements
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🐣 Hot Topic Early Bird 🌍 Conference Polyglot · Silver 🏃 Academic Marathon · Half 🌉 Interdisciplinary Bridge · Bronze 🗺️ Taxonomy Completionist (24)
🧭
Keyword Pioneer
🔬
Deep Specialist
(11)
💎
Century Club · Bronze
🗃️
Keyword Collector
(58)
Top co-authors
Research topics
Machine Learning
(11)
Optimization & Theory · Machine Learning
(11)
Mathematics & Optimization
(5)
Optimization
(5)
Deep Learning
(3)
Core Methods
(3)
Optimization & Theory · Deep Learning
(2)
Artificial Intelligence
(1)
Architectures
(1)
Bayesian & Probabilistic
(1)
Core AI
(1)
Mathematics
(1)
Techniques
(1)
Keywords
stochastic optimization
(3)
quasi-newton method
(3)
fisher matrix
(2)
second-order optimization
(2)
second-order method
(2)
convex optimization
(2)
linear convergence
(2)
sparse learning
(1)
natural gradient
(1)
stochastic gradient
(1)
group lasso
(1)
convex relaxation
(1)
variance reduction
(1)
sparse inverse covariance
(1)
sparse estimation
(1)
neural network training
(1)
signal recovery
(1)
distributed training
(1)
inverse covariance
(1)
sample complexity
(1)
Papers
A Mini-Block Fisher Method for Deep Neural Networks
AISTATS 2023
Increasing Iterate Averaging for Solving Saddle-Point Problems
AAAI 2021
Tensor Normal Training for Deep Learning Models
NeurIPS 2021
Practical Quasi-Newton Methods for Training Deep Neural Networks
NeurIPS 2020
Leader Stochastic Gradient Descent for Distributed Training of Deep Learning Models
NeurIPS 2019
Linear Convergence of Stochastic Frank Wolfe Variants
AISTATS 2017
Stochastic Adaptive Quasi-Newton Methods for Minimizing Expected Values
ICML 2017
Stochastic Block BFGS: Squeezing More Curvature out of Data
ICML 2016
Square Deal: Lower Bounds and Improved Relaxations for Tensor Recovery
ICML 2014
Structured Sparsity via Alternating Direction Methods
JMLR 2012
Sparse Inverse Covariance Selection via Alternating Linearization Methods
NeurIPS 2010