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Zhiqiang Xu

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

Achievements

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+13 more ↓ 🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (10) 🧭 Keyword Pioneer 🌍 Conference Polyglot (13)
🐣 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)

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