← Authors

Yuxin Chen

95 papers · 2013–2026 · 15 conferences · across top CS/AI conferences

Achievements

🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (14) πŸƒ Academic Marathon (12) 🌍 Conference Polyglot (15) 🌈 Renaissance Researcher (5) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (27) 🏠 Conference Loyalist (20) πŸ† Keyword Champion (4) πŸ‘‘ Triple Crown πŸ† Grand Slam πŸ”¬ Deep Specialist (15) 🀝 Dynamic Duo (18) πŸš€ Conference Pioneer ⚑ Prolific Year (7) πŸ”₯ Unstoppable (13) ❓ The Questioner (3) πŸ’Ž Century Club (94) πŸ—ƒοΈ Keyword Collector (73) πŸ“ˆ Trend Setter

Conferences

NIPS (20) ICML (18) AISTATS (12) ICLR (10) COLT (7) CVPR (5) ICCV (5) AAAI (4) IJCAI (4) UAI (4) CORL (2) ACL (1) ECCV (1) JMLR (1) NAACL (1)

Top co-authors

Yuejie Chi (18) Gen Li (14) Yuting Wei (11) Zhongang Qi (9) Yisong Yue (9) Ying Shan (9) Weiming Hu (8) Adish Singla (7) Ziqi Zhang (7) Bing Li (7)

Research topics

Learning Paradigms (1) Learning Paradigms (1) Education (1)

Keywords

sample complexity (14) active learning (9) machine teaching (7) variance reduction (6) regret bound (6) markov decision process (5) generative model (5) adaptive submodularity (4) teaching algorithm (4) submodular optimization (4) nonconvex optimization (4) offline reinforcement learning (4) bayesian optimization (3) reinforcement learning (3) contrastive learning (3) matrix completion (3) concept learning (3) online learning (3) policy optimization (3) gradient descent (3)

Papers

MMhops-R1: Multimodal Multi-hop Reasoning AAAI 2026
Designing Specialized Two-Dimensional Graph Spectral Filters for Spatial-Temporal Graph Modeling AAAI 2025
AnnaAgent: Dynamic Evolution Agent System with Multi-Session Memory for Realistic Seeker Simulation ACL 2025
Finding Interior Optimum of Black-box Constrained Objective with Bayesian Optimization UAI 2025
Taming Rectified Flow for Inversion and Editing ICML 2025
Low-dimensional adaptation of diffusion models: Convergence in total variation (extended abstract) COLT 2025
Mamba-3VL: Taming State Space Model for 3D Vision Language Learning ICCV 2025
DOGR: Towards Versatile Visual Document Grounding and Referring ICCV 2025
VisionMath: Vision-Form Mathematical Problem-Solving ICCV 2025
Bayesian Optimization with Inexact Acquisition: Is Random Grid Search Sufficient? UAI 2025
Mono2Stereo: A Benchmark and Empirical Study for Stereo Conversion CVPR 2025
Minimax Optimal Regret Bound for Reinforcement Learning with Trajectory Feedback ICML 2025
Online Reward-Weighted Fine-Tuning of Flow Matching with Wasserstein Regularization ICLR 2025
Constrained Multi-objective Bayesian Optimization through Optimistic Constraints Estimation AISTATS 2025
Robust Multi-fidelity Bayesian Optimization with Deep Kernel and Partition AISTATS 2025
Versatile Loco-Manipulation through Flexible Interlimb Coordination CORL 2025
Anytime Acceleration of Gradient Descent COLT 2025
Language Representations Can be What Recommenders Need: Findings and Potentials ICLR 2025
MEReQ: Max-Ent Residual-Q Inverse RL for Sample-Efficient Alignment from Intervention CORL 2025
Don’t Be Pessimistic Too Early: Look K Steps Ahead! AISTATS 2024
How to Make Cross Encoder a Good Teacher for Efficient Image-Text Retrieval? CVPR 2024
Settling the sample complexity of online reinforcement learning COLT 2024
Minimax-optimal reward-agnostic exploration in reinforcement learning COLT 2024
Optimal Multi-Distribution Learning COLT 2024
No-Regret Learning of Nash Equilibrium for Black-Box Games via Gaussian Processes UAI 2024
Learning to Rank for Active Learning via Multi-Task Bilevel Optimization UAI 2024
Wukong: Towards a Scaling Law for Large-Scale Recommendation ICML 2024
Accelerating Convergence of Score-Based Diffusion Models, Provably ICML 2024
Transformers Implement Functional Gradient Descent to Learn Non-Linear Functions In Context ICML 2024
GTSinger: A Global Multi-Technique Singing Corpus with Realistic Music Scores for All Singing Tasks NIPS 2024
On Softmax Direct Preference Optimization for Recommendation NIPS 2024
Contextual Active Model Selection NIPS 2024
Advancing Cross-domain Discriminability in Continual Learning of Vision-Language Models NIPS 2024
Federated Natural Policy Gradient and Actor Critic Methods for Multi-task Reinforcement Learning NIPS 2024
Beyond Reverse KL: Generalizing Direct Preference Optimization with Diverse Divergence Constraints ICLR 2024
Horizon-Free Regret for Linear Markov Decision Processes ICLR 2024
Towards Non-Asymptotic Convergence for Diffusion-Based Generative Models ICLR 2024
Blending Imitation and Reinforcement Learning for Robust Policy Improvement ICLR 2024
Enhancing Instance-Level Image Classification with Set-Level Labels ICLR 2024
EA-VTR: Event-Aware Video-Text Retrieval ECCV 2024
Model-based Policy Optimization under Approximate Bayesian Inference AISTATS 2024
Learning Human-Compatible Representations for Case-Based Decision Support ICLR 2023
Reward-agnostic Fine-tuning: Provable Statistical Benefits of Hybrid Reinforcement Learning NIPS 2023
The Curious Price of Distributional Robustness in Reinforcement Learning with a Generative Model NIPS 2023
ViLEM: Visual-Language Error Modeling for Image-Text Retrieval CVPR 2023
Order-Prompted Tag Sequence Generation for Video Tagging ICCV 2023
Scalable Batch-Mode Deep Bayesian Active Learning via Equivalence Class Annealing ICLR 2023
Active Policy Improvement from Multiple Black-box Oracles ICML 2023
Learning Regions of Interest for Bayesian Optimization with Adaptive Level-Set Estimation ICML 2023
Efficient Online Decision Tree Learning with Active Feature Acquisition IJCAI 2023
Explaining Why: How Instructions and User Interfaces Impact Annotator Rationales When Labeling Text Data NAACL 2022
Open-Vocabulary One-Stage Detection With Hierarchical Visual-Language Knowledge Distillation CVPR 2022
Minimax-Optimal Multi-Agent RL in Markov Games With a Generative Model NIPS 2022
Pessimistic Q-Learning for Offline Reinforcement Learning: Towards Optimal Sample Complexity ICML 2022
Channel-Wise Topology Refinement Graph Convolution for Skeleton-Based Action Recognition ICCV 2021
Teaching an Active Learner with Contrastive Examples NIPS 2021
The Teaching Dimension of Kernel Perceptron AISTATS 2021
Softmax Policy Gradient Methods Can Take Exponential Time to Converge COLT 2021
Adaptive Teaching of Temporal Logic Formulas to Preference-based Learners AAAI 2021
Sample-Efficient Reinforcement Learning Is Feasible for Linearly Realizable MDPs with Limited Revisiting NIPS 2021
Breaking the Sample Complexity Barrier to Regret-Optimal Model-Free Reinforcement Learning NIPS 2021
Tightening the Dependence on Horizon in the Sample Complexity of Q-Learning ICML 2021
Learning to Make Decisions via Submodular Regularization ICLR 2021
Teaching via Best-Case Counterexamples in the Learning-with-Equivalence-Queries Paradigm NIPS 2021
Understanding the Effect of Bias in Deep Anomaly Detection IJCAI 2021
Sample Complexity of Asynchronous Q-Learning: Sharper Analysis and Variance Reduction NIPS 2020
Communication-Efficient Distributed Optimization in Networks with Gradient Tracking and Variance Reduction JMLR 2020
Breaking the Sample Size Barrier in Model-Based Reinforcement Learning with a Generative Model NIPS 2020
Understanding the Power and Limitations of Teaching with Imperfect Knowledge IJCAI 2020
An Online Learning Framework for Energy-Efficient Navigation of Electric Vehicles IJCAI 2020
Communication-Efficient Distributed Optimization in Networks with Gradient Tracking and Variance Reduction AISTATS 2020
Uncertainty quantification for nonconvex tensor completion: Confidence intervals, heteroscedasticity and optimality ICML 2020
Nonconvex Matrix Factorization from Rank-One Measurements AISTATS 2019
Landmark Ordinal Embedding NIPS 2019
Batched Stochastic Bayesian Optimization via Combinatorial Constraints Design AISTATS 2019
A General Framework for Multi-fidelity Bayesian Optimization with Gaussian Processes AISTATS 2019
Nonconvex Low-Rank Tensor Completion from Noisy Data NIPS 2019
Type Sequence Preserving Heterogeneous Information Network Embedding AAAI 2019
Preference-Based Batch and Sequential Teaching: Towards a Unified View of Models NIPS 2019
Teaching Multiple Concepts to a Forgetful Learner NIPS 2019
Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval and Matrix Completion ICML 2018
Understanding the Role of Adaptivity in Machine Teaching: The Case of Version Space Learners NIPS 2018
Teaching Categories to Human Learners With Visual Explanations CVPR 2018
Near-Optimal Machine Teaching via Explanatory Teaching Sets AISTATS 2018
Near-optimal Bayesian Active Learning with Correlated and Noisy Tests AISTATS 2017
Community Recovery in Graphs with Locality ICML 2016
Spectral MLE: Top-K Rank Aggregation from Pairwise Comparisons ICML 2015
Sequential Information Maximization: When is Greedy Near-optimal? COLT 2015
Solving Random Quadratic Systems of Equations Is Nearly as Easy as Solving Linear Systems NIPS 2015
Near-Optimal Joint Object Matching via Convex Relaxation ICML 2014
Active Detection via Adaptive Submodularity ICML 2014
Near Optimal Bayesian Active Learning for Decision Making AISTATS 2014
Scalable Semidefinite Relaxation for Maximum A Posterior Estimation ICML 2014
Spectral Compressed Sensing via Structured Matrix Completion ICML 2013
Near-optimal Batch Mode Active Learning and Adaptive Submodular Optimization ICML 2013