← Authors

Zhiqiang Xu

35 papers · 2009–2025 · 13 conferences · across top CS/AI conferences

Achievements

🌍 Conference Polyglot (13) πŸƒ Academic Marathon (16) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (10) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (10) 🌈 Renaissance Researcher (9) πŸ‘‘ Triple Crown πŸ† Grand Slam πŸ”¬ Deep Specialist (10) 🧬 Topic Evolution πŸ† Keyword Champion (3) πŸ—ƒοΈ Keyword Collector (142) πŸ“ˆ Trend Setter πŸ”₯ Unstoppable (8) πŸ’Ž Century Club (35) ⚑ Prolific Year (5)

Conferences

NIPS (10) ICLR (4) ICML (4) AAAI (3) AISTATS (3) EMNLP (2) IJCAI (2) JMLR (2) ACML (1) ALT (1) ICCV (1) INTERSPEECH (1) UAI (1)

Top co-authors

Ping Li (8) Changyou Chen (4) Zeke Xie (4) Pengfei Wei (3) Shitong Shao (2) Zikai Zhou (2) Ruiyi Zhang (2) Xin Gao (2) Chunlai Zhou (2) Xiang Yin (2)

Research topics

Differential Privacy (1)

Keywords

riemannian optimization (5) convergence analysis (3) gradient descent (3) eigenvector computation (3) linear convergence (3) eigenvalue computation (3) canonical correlation analysis (3) stiefel manifold (2) power iteration (2) spectral gap (2) differential privacy (2) alternating least square (2) stochastic gradient (2) matrix computation (2) adversarial learning (2) principal component analysis (2) matrix decomposition (2) matrix factorization (2) diffusion model (2) matrix eigenvalue (2)

Papers

A Gaussian Filter-Based 3D Registration Method for Series Section Electron Microscopy AAAI 2025
Principled Data Selection for Alignment: The Hidden Risks of Difficult Examples ICML 2025
Zigzag Diffusion Sampling: Diffusion Models Can Self-Improve via Self-Reflection ICLR 2025
Measuring And Improving Engagement of Text-to-Image Generation Models ICLR 2025
Golden Noise for Diffusion Models: A Learning Framework ICCV 2025
Learning Constraints from Offline Demonstrations via Superior Distribution Correction Estimation ICML 2024
DALD: Improving Logits-based Detector without Logits from Black-box LLMs NIPS 2024
On the Comparison between Multi-modal and Single-modal Contrastive Learning NIPS 2024
Prior and Prediction Inverse Kernel Transformer for Single Image Defocus Deblurring AAAI 2024
Visual Question Decomposition on Multimodal Large Language Models EMNLP 2024
TextLap: Customizing Language Models for Text-to-Layout Planning EMNLP 2024
AUC-CL: A Batchsize-Robust Framework for Self-Supervised Contrastive Representation Learning ICLR 2024
Learning No-Regret Sparse Generalized Linear Models with Varying Observation(s) ICLR 2024
Hard-Thresholding Meets Evolution Strategies in Reinforcement Learning IJCAI 2024
Provably Neural Active Learning Succeeds via Prioritizing Perplexing Samples ICML 2024
On the Overlooked Pitfalls of Weight Decay and How to Mitigate Them: A Gradient-Norm Perspective NIPS 2023
Label-Retrieval-Augmented Diffusion Models for Learning from Noisy Labels NIPS 2023
On the Accelerated Noise-Tolerant Power Method AISTATS 2023
Unsupervised Video Domain Adaptation for Action Recognition: A Disentanglement Perspective NIPS 2023
S2CD: Self-heuristic Speaker Content Disentanglement for Any-to-Any Voice Conversion INTERSPEECH 2023
Multi-Modal Inverse Constrained Reinforcement Learning from a Mixture of Demonstrations NIPS 2023
Noisy Riemannian Gradient Descent for Eigenvalue Computation with Application to Inexact Stochastic Recursive Gradient Algorithm ACML 2022
Faster Noisy Power Method ALT 2022
Local Differential Privacy for Belief Functions AAAI 2022
On the Riemannian Search for Eigenvector Computation JMLR 2021
A Comprehensively Tight Analysis of Gradient Descent for PCA NIPS 2021
On the Faster Alternating Least-Squares for CCA AISTATS 2021
A Practical Riemannian Algorithm for Computing Dominant Generalized Eigenspace UAI 2020
Towards Better Generalization of Adaptive Gradient Methods NIPS 2020
Towards Practical Alternating Least-Squares for CCA NIPS 2019
Convergence Analysis of Gradient Descent for Eigenvector Computation IJCAI 2018
On Truly Block Eigensolvers via Riemannian Optimization AISTATS 2018
Gradient Descent Meets Shift-and-Invert Preconditioning for Eigenvector Computation NIPS 2018
Matrix Eigen-decomposition via Doubly Stochastic Riemannian Optimization ICML 2016
Marginal Likelihood Integrals for Mixtures of Independence Models JMLR 2009