Luo Luo
35 papers · 2015–2026 · 7 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
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🗺️ Taxonomy Completionist (31) 🏃 Academic Marathon · Half 🌍 Conference Polyglot · Silver 🌉 Interdisciplinary Bridge · Silver 🐣 Hot Topic Early Bird
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Deep Specialist
(25)
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Dynamic Duo
(10)
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Topic Evolution
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Century Club · Bronze
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Research topics
Machine Learning
(30)
Mathematics & Optimization
(28)
Optimization
(27)
Optimization & Theory · Machine Learning
(27)
Mathematics
(6)
Application Areas
(3)
Computer Science
(2)
Deep Learning
(2)
Core Methods
(2)
Learning Types
(2)
Optimization & Theory · Deep Learning
(2)
Reinforcement Learning
(1)
Applications
(1)
Foundations
(1)
Systems
(1)
Keywords
stochastic optimization
(9)
minimax optimization
(7)
non-convex optimization
(7)
decentralized optimization
(6)
variance reduction
(5)
superlinear convergence
(4)
communication complexity
(3)
stochastic gradient
(3)
gradient-free method
(3)
convex optimization
(3)
quasi-newton method
(3)
distributed learning
(3)
stochastic algorithm
(3)
distributed optimization
(2)
online learning
(2)
convergence rate
(2)
matrix sketching
(2)
condition number
(2)
complexity bound
(2)
hessian approximation
(2)
Papers
Decentralized Non-convex Stochastic Optimization with Heterogeneous Variance
AAAI 2026
Faster Newton Methods for Convex and Nonconvex Optimization in Gradient Complexity
COLT 2026
Privacy Leaks by Adversaries: Adversarial Iterations for Membership Inference Attack
AAAI 2026
An Enhanced Levenberg--Marquardt Method via Gram Reduction
AAAI 2025
A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization
ICML 2025
Solving Convex-Concave Problems with O(ε^-4/7) Second-Order Oracle Complexity
COLT 2025
An Efficient Stochastic Algorithm for Decentralized Nonconvex-Strongly-Concave Minimax Optimization
AISTATS 2024
Decentralized Convex Finite-Sum Optimization with Better Dependence on Condition Numbers
ICML 2024
Decentralized Gradient-Free Methods for Stochastic Non-smooth Non-convex Optimization
AAAI 2024
Gradient-Free Methods for Nonconvex Nonsmooth Stochastic Compositional Optimization
NeurIPS 2024
Incremental Quasi-Newton Methods with Faster Superlinear Convergence Rates
AAAI 2024
Near-Optimal Algorithms for Making the Gradient Small in Stochastic Minimax Optimization
JMLR 2024
Near-Optimal Distributed Minimax Optimization under the Second-Order Similarity
NeurIPS 2024
On the Complexity of Finite-Sum Smooth Optimization under the Polyak–Łojasiewicz Condition
ICML 2024
Optimizing over Multiple Distributions under Generalized Quasar-Convexity Condition
NeurIPS 2024
Zeroth-Order Methods for Constrained Nonconvex Nonsmooth Stochastic Optimization
ICML 2024
Block Broyden's Methods for Solving Nonlinear Equations
NeurIPS 2023
Faster Gradient-Free Algorithms for Nonsmooth Nonconvex Stochastic Optimization
ICML 2023
Multi-Consensus Decentralized Accelerated Gradient Descent
JMLR 2023
Faster Stochastic Algorithms for Minimax Optimization under Polyak-{\L}ojasiewicz Condition
NeurIPS 2022
Finding Second-Order Stationary Points in Nonconvex-Strongly-Concave Minimax Optimization
NeurIPS 2022
Quasi-Newton Methods for Saddle Point Problems
NeurIPS 2022
Approximate Newton Methods
JMLR 2021
Revisiting Co-Occurring Directions: Sharper Analysis and Efficient Algorithm for Sparse Matrices
AAAI 2021
Decentralized Accelerated Proximal Gradient Descent
NeurIPS 2020
Efficient and Robust High-Dimensional Linear Contextual Bandits
IJCAI 2020
Efficient Projection-free Algorithms for Saddle Point Problems
NeurIPS 2020
Lower Complexity Bounds for Finite-Sum Convex-Concave Minimax Optimization Problems
ICML 2020
Nesterov's Acceleration for Approximate Newton
JMLR 2020
Stochastic Recursive Gradient Descent Ascent for Stochastic Nonconvex-Strongly-Concave Minimax Problems
NeurIPS 2020
Robust Frequent Directions with Application in Online Learning
JMLR 2019
Approximate Newton Methods and Their Local Convergence
ICML 2017
Frequent Direction Algorithms for Approximate Matrix Multiplication with Applications in CCA
IJCAI 2016
SPSD Matrix Approximation vis Column Selection: Theories, Algorithms, and Extensions
JMLR 2016
Support Matrix Machines
ICML 2015