Guanghui Lan
8 papers · 2017–2022 · 5 venues · across top CS/AI venues
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Achievements
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π Conference Polyglot Β· Silver π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Bronze πΊοΈ Taxonomy Completionist (20) π£ Hot Topic Early Bird
π
Conference Pioneer
Top co-authors
Research topics
Machine Learning
(8)
Optimization & Theory Β· Machine Learning
(6)
Mathematics & Optimization
(5)
Optimization
(5)
Core Methods
(3)
Deep Learning
(2)
Learning Types
(2)
Optimization & Theory Β· Deep Learning
(2)
Artificial Intelligence
(1)
Reinforcement Learning
(1)
Application Areas
(1)
Core AI
(1)
Methods
(1)
Keywords
non-convex optimization
(3)
cubic regularization
(2)
second-order stationary point
(2)
stochastic gradient descent
(2)
policy optimization
(1)
convex optimization
(1)
finite-sum optimization
(1)
second-order optimization
(1)
supervised learning
(1)
constrained optimization
(1)
constraint satisfaction
(1)
variance reduction
(1)
sparse optimization
(1)
alternating minimization
(1)
adaptive learning rate
(1)
natural policy gradient
(1)
complexity analysis
(1)
accelerated gradient
(1)
maximum likelihood estimation
(1)
embedding learning
(1)
Papers
Frequency-aware SGD for Efficient Embedding Learning with Provable Benefits
ICLR 2022
CRPO: A New Approach for Safe Reinforcement Learning with Convergence Guarantee
ICML 2021
A Feasible Level Proximal Point Method for Nonconvex Sparse Constrained Optimization
NeurIPS 2020
GLAD: Learning Sparse Graph Recovery
ICLR 2020
A unified variance-reduced accelerated gradient method for convex optimization
NeurIPS 2019
Cubic Regularization with Momentum for Nonconvex Optimization
UAI 2019
Stochastic Variance-Reduced Cubic Regularization for Nonconvex Optimization
AISTATS 2019
Conditional Accelerated Lazy Stochastic Gradient Descent
ICML 2017