Zhi-Quan Luo
24 papers · 2013–2025 · 8 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (48) π Academic Marathon Β· Half π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
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Keyword Champion
(2)
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Topic Evolution
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Deep Specialist
(10)
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Century Club Β· Bronze
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Unstoppable Β· Bronze
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Renaissance Researcher
(6)
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Prolific Year Β· Productive
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(122)
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Research topics
Machine Learning
(21)
Optimization & Theory Β· Machine Learning
(20)
Artificial Intelligence
(8)
Deep Learning
(8)
Core AI
(8)
Learning Types
(7)
Mathematics & Optimization
(6)
Optimization
(6)
Architectures
(5)
Reinforcement Learning
(4)
Methods
(4)
Natural Language Processing
(2)
Application Areas
(2)
Learning Paradigms
(2)
Optimization & Theory Β· Deep Learning
(2)
Keywords
stochastic gradient descent
(3)
robust overfitting
(2)
reinforcement learning
(2)
generalization bound
(2)
iteration complexity
(2)
adam optimizer
(2)
adversarial training
(2)
variance reduction
(2)
learning rate
(2)
adversarial learning
(2)
spiking neural network
(2)
parallel algorithm
(2)
imitation learning
(2)
convex optimization
(2)
block coordinate descent
(2)
neuromorphic computing
(2)
posterior sampling
(2)
gradient descent
(2)
regret bound
(2)
surrogate gradient
(2)
Papers
Adam-mini: Use Fewer Learning Rates To Gain More
ICLR 2025
Preserving Diversity in Supervised Fine-Tuning of Large Language Models
ICLR 2025
ROS: A GNN-based Relax-Optimize-and-Sample Framework for Max-k-Cut Problems
ICML 2025
Bridging Distributional and Risk-sensitive Reinforcement Learning with Provable Regret Bounds
JMLR 2024
Q-Star Meets Scalable Posterior Sampling: Bridging Theory and Practice via HyperAgent
ICML 2024
ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models
ICML 2024
Uniformly Stable Algorithms for Adversarial Training and Beyond
ICML 2024
Why Transformers Need Adam: A Hessian Perspective
NeurIPS 2024
A Distribution Optimization Framework for Confidence Bounds of Risk Measures
ICML 2023
Imitation Learning from Imperfection: Theoretical Justifications and Algorithms
NeurIPS 2023
PAC-Bayesian Spectrally-Normalized Bounds for Adversarially Robust Generalization
NeurIPS 2023
Provably Efficient Adversarial Imitation Learning with Unknown Transitions
UAI 2023
Towards Memory- and Time-Efficient Backpropagation for Training Spiking Neural Networks
ICCV 2023
Adam Can Converge Without Any Modification On Update Rules
NeurIPS 2022
Fast Generic Interaction Detection for Model Interpretability and Compression
ICLR 2022
HyperDQN: A Randomized Exploration Method for Deep Reinforcement Learning
ICLR 2022
Stability Analysis and Generalization Bounds of Adversarial Training
NeurIPS 2022
Training High-Performance Low-Latency Spiking Neural Networks by Differentiation on Spike Representation
CVPR 2022
When Expressivity Meets Trainability: Fewer than n Neurons Can Work
NeurIPS 2021
A Single-Loop Smoothed Gradient Descent-Ascent Algorithm for Nonconvex-Concave Min-Max Problems
NeurIPS 2020
Direct Acceleration of SAGA using Sampled Negative Momentum
AISTATS 2019
Parallel Direction Method of Multipliers
NeurIPS 2014
Parallel Successive Convex Approximation for Nonsmooth Nonconvex Optimization
NeurIPS 2014
On the Linear Convergence of the Proximal Gradient Method for Trace Norm Regularization
NeurIPS 2013