Zhi-Quan Luo
24 papers · 2013–2025 · 8 conferences · across top CS/AI conferences
Achievements
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🌍 Conference Polyglot (8) 🏃 Academic Marathon (12) 🧭 Keyword Pioneer 🌉 Interdisciplinary Bridge 🐝 Cross-Pollinator (13)
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Conference Polyglot
(8)
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Academic Marathon
(12)
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(6)
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(2)
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(24)
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Conferences
NIPS (10)
ICML (5)
ICLR (4)
AISTATS (1)
CVPR (1)
ICCV (1)
JMLR (1)
UAI (1)
Top co-authors
Keywords
stochastic gradient descent
(3)
block coordinate descent
(2)
generalization bound
(2)
adam optimizer
(2)
neural network
(2)
regret bound
(2)
iteration complexity
(2)
parallel algorithm
(2)
imitation learning
(2)
convex optimization
(2)
neuromorphic computing
(2)
adversarial learning
(2)
surrogate gradient
(2)
spiking neural network
(2)
gradient descent
(2)
convergence analysis
(1)
global convergence
(1)
adversarial robustness
(1)
sequential decision making
(1)
stochastic gradient
(1)
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
ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models
ICML 2024
Q-Star Meets Scalable Posterior Sampling: Bridging Theory and Practice via HyperAgent
ICML 2024
Bridging Distributional and Risk-sensitive Reinforcement Learning with Provable Regret Bounds
JMLR 2024
Why Transformers Need Adam: A Hessian Perspective
NIPS 2024
Uniformly Stable Algorithms for Adversarial Training and Beyond
ICML 2024
Provably Efficient Adversarial Imitation Learning with Unknown Transitions
UAI 2023
Imitation Learning from Imperfection: Theoretical Justifications and Algorithms
NIPS 2023
PAC-Bayesian Spectrally-Normalized Bounds for Adversarially Robust Generalization
NIPS 2023
Towards Memory- and Time-Efficient Backpropagation for Training Spiking Neural Networks
ICCV 2023
A Distribution Optimization Framework for Confidence Bounds of Risk Measures
ICML 2023
Fast Generic Interaction Detection for Model Interpretability and Compression
ICLR 2022
HyperDQN: A Randomized Exploration Method for Deep Reinforcement Learning
ICLR 2022
Adam Can Converge Without Any Modification On Update Rules
NIPS 2022
Stability Analysis and Generalization Bounds of Adversarial Training
NIPS 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
NIPS 2021
A Single-Loop Smoothed Gradient Descent-Ascent Algorithm for Nonconvex-Concave Min-Max Problems
NIPS 2020
Direct Acceleration of SAGA using Sampled Negative Momentum
AISTATS 2019
Parallel Successive Convex Approximation for Nonsmooth Nonconvex Optimization
NIPS 2014
Parallel Direction Method of Multipliers
NIPS 2014
On the Linear Convergence of the Proximal Gradient Method for Trace Norm Regularization
NIPS 2013