Liu, Han

157 publications

CPAL 2025 Adaptive Batch Size Schedules for Distributed Training of Language Models with Data and Model Parallelism Tim Tsz-Kit Lau, Weijian Li, Chenwei Xu, Han Liu, Mladen Kolar

NeurIPS 2025 Attention Mechanism, Max-Affine Partition, and Universal Approximation Hude Liu, Jerry Yao-Chieh Hu, Zhao Song, Han Liu

ICLR 2025 Chain-of-Action: Faithful and Multimodal Question Answering Through Large Language Models Zhenyu Pan, Haozheng Luo, Manling Li, Han Liu

ICLR 2025 Computational Limits of Low-Rank Adaptation (LoRA) Fine-Tuning for Transformer Models Jerry Yao-Chieh Hu, Maojiang Su, En-jui Kuo, Zhao Song, Han Liu

ICLRW 2025 Computational Limits of Low-Rank Adaptation (LoRA) Fine-Tuning for Transformer Models Jerry Yao-Chieh Hu, Maojiang Su, En-Jui Kuo, Zhao Song, Han Liu

ECML-PKDD 2025 Cross-Domain Conditional Diffusion Models for Time Series Imputation Kexin Zhang, Baoyu Jing, K. Selçuk Candan, Dawei Zhou, Qingsong Wen, Han Liu, Kaize Ding

AAAI 2025 Dual-View Interaction-Aware Lane Change Prediction for Autonomous Driving Yuhuan Lu, Zhen Zhang, Rufan Bai, Han Liu, Wei Wang

IJCAI 2025 ECG2TOK: ECG Pre-Training with Self-Distillation Semantic Tokenizers Xiaoyan Yuan, Wei Wang, Han Liu, Jian Chen, Xiping Hu

AAAI 2025 EGSRAL: An Enhanced 3D Gaussian Splatting Based Renderer with Automated Labeling for Large-Scale Driving Scene Yixiong Huo, Guangfeng Jiang, Hongyang Wei, Ji Liu, Song Zhang, Han Liu, Xingliang Huang, Mingjie Lu, Jinzhang Peng, Dong Li, Lu Tian, Emad Barsoum

ICML 2025 Fast and Low-Cost Genomic Foundation Models via Outlier Removal Haozheng Luo, Chenghao Qiu, Maojiang Su, Zhihan Zhou, Zoe Mehta, Guo Ye, Jerry Yao-Chieh Hu, Han Liu

ICLR 2025 Fundamental Limits of Prompt Tuning Transformers: Universality, Capacity and Efficiency Jerry Yao-Chieh Hu, Wei-Po Wang, Ammar Gilani, Chenyang Li, Zhao Song, Han Liu

ICLRW 2025 Fundamental Limits of Prompt Tuning Transformers: Universality, Capacity and Efficiency Jerry Yao-Chieh Hu, Wei-Po Wang, Ammar Gilani, Chenyang Li, Zhao Song, Han Liu

NeurIPS 2025 HQA-VLAttack: Towards High Quality Adversarial Attack on Vision-Language Pre-Trained Models Han Liu, Jiaqi Li, Zhi Xu, Xiaotong Zhang, Xiaoming Xu, Fenglong Ma, Yuanman Li, Hong Yu

NeurIPS 2025 High-Order Flow Matching: Unified Framework and Sharp Statistical Rates Maojiang Su, Jerry Yao-Chieh Hu, Yi-Chen Lee, Ning Zhu, Jui-Hui Chung, Shang Wu, Zhao Song, Minshuo Chen, Han Liu

CVPR 2025 Improving Accuracy and Calibration via Differentiated Deep Mutual Learning Han Liu, Peng Cui, Bingning Wang, Weipeng Chen, Yupeng Zhang, Jun Zhu, Xiaolin Hu

ICML 2025 In-Context Deep Learning via Transformer Models Weimin Wu, Maojiang Su, Jerry Yao-Chieh Hu, Zhao Song, Han Liu

ICML 2025 In-Context Learning as Conditioned Associative Memory Retrieval Weimin Wu, Teng-Yun Hsiao, Jerry Yao-Chieh Hu, Wenxin Zhang, Han Liu

NeurIPS 2025 Investigating Hallucinations of Time Series Foundation Models Through Signal Subspace Analysis Yufeng Zou, Zijian Wang, Diego Klabjan, Han Liu

NeurIPS 2025 MetaFind: Scene-Aware 3D Asset Retrieval for Coherent Metaverse Scene Generation Zhenyu Pan, Yucheng Lu, Han Liu

AAAI 2025 Multi-Label Few-Shot Image Classification via Pairwise Feature Augmentation and Flexible Prompt Learning Han Liu, Yuanyuan Wang, Xiaotong Zhang, Feng Zhang, Wei Wang, Fenglong Ma, Hong Yu

ICML 2025 Nonparametric Modern Hopfield Models Jerry Yao-Chieh Hu, Bo-Yu Chen, Dennis Wu, Feng Ruan, Han Liu

ICLR 2025 On Statistical Rates of Conditional Diffusion Transformers: Approximation, Estimation and Minimax Optimality Jerry Yao-Chieh Hu, Weimin Wu, Yi-Chen Lee, Yu-Chao Huang, Minshuo Chen, Han Liu

NeurIPS 2025 Pareto-Optimal Energy Alignment for Designing Nature-like Antibodies Yibo Wen, Chenwei Xu, Jerry Yao-Chieh Hu, Kaize Ding, Han Liu

ICLRW 2025 Statistical Foundations of Conditional Diffusion Transformers Jerry Yao-Chieh Hu, Weimin Wu, Yi-Chen Lee, Yu-Chao Huang, Minshuo Chen, Han Liu

AISTATS 2025 Statistical Guarantees for Lifelong Reinforcement Learning Using PAC-Bayes Theory Zhi Zhang, Chris Chow, Yasi Zhang, Yanchao Sun, Haochen Zhang, Eric Hanchen Jiang, Han Liu, Furong Huang, Yuchen Cui, Oscar Hernan Madrid Padilla

AAAI 2025 Uncertainty-Aware Contrastive Learning with Hard Negative Sampling for Code Search Tasks Han Liu, Jiaqing Zhan, Qin Zhang

NeurIPS 2025 VPO: Reasoning Preferences Optimization Based on $\mathcal{V}$-Usable Information Zecheng Wang, Chunshan Li, Yupeng Zhang, Han Liu, Bingning Wang, Dianhui Chu, Dianbo Sui

AAAI 2024 A Goal Interaction Graph Planning Framework for Conversational Recommendation Xiaotong Zhang, Xuefang Jia, Han Liu, Xinyue Liu, Xianchao Zhang

ICLR 2024 Beyond Reverse KL: Generalizing Direct Preference Optimization with Diverse Divergence Constraints Chaoqi Wang, Yibo Jiang, Chenghao Yang, Han Liu, Yuxin Chen

ICML 2024 BiSHop: Bi-Directional Cellular Learning for Tabular Data with Generalized Sparse Modern Hopfield Model Chenwei Xu, Yu-Chao Huang, Jerry Yao-Chieh Hu, Weijian Li, Ammar Gilani, Hsi-Sheng Goan, Han Liu

ICLR 2024 DNABERT-2: Efficient Foundation Model and Benchmark for Multi-Species Genomes Zhihan Zhou, Yanrong Ji, Weijian Li, Pratik Dutta, Ramana V Davuluri, Han Liu

AAAI 2024 Depression Detection via Capsule Networks with Contrastive Learning Han Liu, Changya Li, Xiaotong Zhang, Feng Zhang, Wei Wang, Fenglong Ma, Hongyang Chen, Hong Yu, Xianchao Zhang

TMLR 2024 Efficient Action Robust Reinforcement Learning with Probabilistic Policy Execution Uncertainty Guanlin Liu, Zhihan Zhou, Han Liu, Lifeng Lai

ICMLW 2024 Fast Adaptation and Robust Quantization of Multi-Modal Foundation Models from Associative Memory: A Case Study in SpeechLM Shang Wu, Yen-Ju Lu, Haozheng Luo, Jerry Yao-Chieh Hu, Jiayi Wang, Najim Dehak, Jesus Villalba, Han Liu

NeurIPS 2024 Global Convergence in Training Large-Scale Transformers Cheng Gao, Yuan Cao, Zihao Li, Yihan He, Mengdi Wang, Han Liu, Jason M. Klusowski, Jianqing Fan

AAAI 2024 Liberating Seen Classes: Boosting Few-Shot and Zero-Shot Text Classification via Anchor Generation and Classification Reframing Han Liu, Siyang Zhao, Xiaotong Zhang, Feng Zhang, Wei Wang, Fenglong Ma, Hongyang Chen, Hong Yu, Xianchao Zhang

AISTATS 2024 Multivariate Time Series Forecasting by Graph Attention Networks with Theoretical Guarantees Zhi Zhang, Weijian Li, Han Liu

ICML 2024 On Computational Limits of Modern Hopfield Models: A Fine-Grained Complexity Analysis Jerry Yao-Chieh Hu, Thomas Lin, Zhao Song, Han Liu

NeurIPS 2024 On Statistical Rates and Provably Efficient Criteria of Latent Diffusion Transformers (DiTs) Jerry Yao-Chieh Hu, Weimin Wu, Zhuoru Li, Sophia Pi, Zhao Song, Han Liu

NeurIPS 2024 One-Layer Transformer Provably Learns One-Nearest Neighbor in Context Zihao Li, Yuan Cao, Cheng Gao, Yihan He, Han Liu, Jason M. Klusowski, Jianqing Fan, Mengdi Wang

ICMLW 2024 OutEffHop: A Principled Outlier-Efficient Attention Layer from Dense Associative Memory Models Haozheng Luo, Jerry Yao-Chieh Hu, Pei-Hsuan Chang, Hong-Yu Chen, Weijian Li, Wei-Po Wang, Han Liu

ICML 2024 Outlier-Efficient Hopfield Layers for Large Transformer-Based Models Jerry Yao-Chieh Hu, Pei-Hsuan Chang, Haozheng Luo, Hong-Yu Chen, Weijian Li, Wei-Po Wang, Han Liu

NeurIPS 2024 Provably Optimal Memory Capacity for Modern Hopfield Models: Transformer-Compatible Dense Associative Memories as Spherical Codes Jerry Yao-Chieh Hu, Dennis Wu, Han Liu

ICLR 2024 STanHop: Sparse Tandem Hopfield Model for Memory-Enhanced Time Series Prediction Dennis Wu, Jerry Yao-Chieh Hu, Weijian Li, Bo-Yu Chen, Han Liu

ICML 2024 Uniform Memory Retrieval with Larger Capacity for Modern Hopfield Models Dennis Wu, Jerry Yao-Chieh Hu, Teng-Yun Hsiao, Han Liu

AAAI 2024 VQAttack: Transferable Adversarial Attacks on Visual Question Answering via Pre-Trained Models Ziyi Yin, Muchao Ye, Tianrong Zhang, Jiaqi Wang, Han Liu, Jinghui Chen, Ting Wang, Fenglong Ma

NeurIPSW 2023 Beyond Reverse KL: Generalizing Direct Preference Optimization with Diverse Divergence Constraints Chaoqi Wang, Yibo Jiang, Chenghao Yang, Han Liu, Yuxin Chen

NeurIPSW 2023 Beyond Reverse KL: Generalizing Direct Preference Optimization with Diverse Divergence Constraints Chaoqi Wang, Yibo Jiang, Chenghao Yang, Han Liu, Yuxin Chen

IJCAI 2023 Boosting Decision-Based Black-Box Adversarial Attack with Gradient Priors Han Liu, Xingshuo Huang, Xiaotong Zhang, Qimai Li, Fenglong Ma, Wei Wang, Hongyang Chen, Hong Yu, Xianchao Zhang

AAAI 2023 Boosting Few-Shot Text Classification via Distribution Estimation Han Liu, Feng Zhang, Xiaotong Zhang, Siyang Zhao, Fenglong Ma, Xiao-Ming Wu, Hongyang Chen, Hong Yu, Xianchao Zhang

MIDL 2023 Domain Generalization for Retinal Vessel Segmentation with Vector Field Transformer Dewei Hu, Hao Li, Han Liu, Ipek Oguz

ICML 2023 Feature Programming for Multivariate Time Series Prediction Alex Daniel Reneau, Jerry Yao-Chieh Hu, Ammar Gilani, Han Liu

NeurIPS 2023 HQA-Attack: Toward High Quality Black-Box Hard-Label Adversarial Attack on Text Han Liu, Zhi Xu, Xiaotong Zhang, Feng Zhang, Fenglong Ma, Hongyang Chen, Hong Yu, Xianchao Zhang

AAAI 2023 Ising-Traffic: Using Ising Machine Learning to Predict Traffic Congestion Under Uncertainty Zhenyu Pan, Anshujit Sharma, Jerry Yao-Chieh Hu, Zhuo Liu, Ang Li, Han Liu, Michael C. Huang, Tong Geng

ICLR 2023 Learning Human-Compatible Representations for Case-Based Decision Support Han Liu, Yizhou Tian, Chacha Chen, Shi Feng, Yuxin Chen, Chenhao Tan

NeurIPS 2023 On Sparse Modern Hopfield Model Jerry Yao-Chieh Hu, Donglin Yang, Dennis Wu, Chenwei Xu, Bo-Yu Chen, Han Liu

CVPR 2023 RIATIG: Reliable and Imperceptible Adversarial Text-to-Image Generation with Natural Prompts Han Liu, Yuhao Wu, Shixuan Zhai, Bo Yuan, Ning Zhang

ICLR 2023 Real-Time Image Demoir$\acute{e}$ing on Mobile Devices Yuxin Zhang, Mingbao Lin, Xunchao Li, Han Liu, Guozhi Wang, Fei Chao, Ren Shuai, Yafei Wen, Xiaoxin Chen, Rongrong Ji

AAAI 2023 SSPAttack: A Simple and Sweet Paradigm for Black-Box Hard-Label Textual Adversarial Attack Han Liu, Zhi Xu, Xiaotong Zhang, Xiaoming Xu, Feng Zhang, Fenglong Ma, Hongyang Chen, Hong Yu, Xianchao Zhang

CVPR 2023 SlowLiDAR: Increasing the Latency of LiDAR-Based Detection Using Adversarial Examples Han Liu, Yuhao Wu, Zhiyuan Yu, Yevgeniy Vorobeychik, Ning Zhang

NeurIPSW 2023 TopoPool: An Adaptive Graph Pooling Layer for Extracting Molecular and Protein Substructures Mattson Thieme, Majdi Hassan, Chetan Rupakheti, Kedar Balaji Thiagarajan, Abhishek Pandey, Han Liu

NeurIPS 2023 VLATTACK: Multimodal Adversarial Attacks on Vision-Language Tasks via Pre-Trained Models Ziyi Yin, Muchao Ye, Tianrong Zhang, Tianyu Du, Jinguo Zhu, Han Liu, Jinghui Chen, Ting Wang, Fenglong Ma

ICML 2022 Bregman Proximal Langevin Monte Carlo via Bregman-Moreau Envelopes Tim Tsz-Kit Lau, Han Liu

AAAI 2022 Cross-Dataset Collaborative Learning for Semantic Segmentation in Autonomous Driving Li Wang, Dong Li, Han Liu, Jinzhang Peng, Lu Tian, Yi Shan

NeurIPSW 2022 Interdisciplinary Discovery of Nanomaterials Based on Convolutional Neural Networks Tong Xie, Yuwei Wan, Weijian Li, Qingyuan Linghu, Shaozhou Wang, Yalun Cai, Han Liu, Chunyu Kit, Clara Grazian, Bram Hoex

ICLR 2022 Reinforcement Learning Under a Multi-Agent Predictive State Representation Model: Method and Theory Zhi Zhang, Zhuoran Yang, Han Liu, Pratap Tokekar, Furong Huang

AAAI 2021 Converse, Focus and Guess - Towards Multi-Document Driven Dialogue Han Liu, Caixia Yuan, Xiaojie Wang, Yushu Yang, Huixing Jiang, Zhongyuan Wang

CVPR 2021 Posterior Promoted GAN with Distribution Discriminator for Unsupervised Image Synthesis Xianchao Zhang, Ziyang Cheng, Xiaotong Zhang, Han Liu

CoRL 2021 RoboFlow: A Data-Centric Workflow Management System for Developing AI-Enhanced Robots Qinjie Lin, Guo Ye, Jiayi Wang, Han Liu

JMLR 2020 Agnostic Estimation for Phase Retrieval Matey Neykov, Zhaoran Wang, Han Liu

ICLR 2020 GLAD: Learning Sparse Graph Recovery Harsh Shrivastava, Xinshi Chen, Binghong Chen, Guanghui Lan, Srinvas Aluru, Han Liu, Le Song

ICLR 2020 Learning to Plan in High Dimensions via Neural Exploration-Exploitation Trees Binghong Chen, Bo Dai, Qinjie Lin, Guo Ye, Han Liu, Le Song

IJCAI 2019 Attributed Graph Clustering via Adaptive Graph Convolution Xiaotong Zhang, Han Liu, Qimai Li, Xiao-Ming Wu

NeurIPS 2019 Fast Low-Rank Metric Learning for Large-Scale and High-Dimensional Data Han Liu, Zhizhong Han, Yu-Shen Liu, Ming Gu

ICML 2019 Grid-Wise Control for Multi-Agent Reinforcement Learning in Video Game AI Lei Han, Peng Sun, Yali Du, Jiechao Xiong, Qing Wang, Xinghai Sun, Han Liu, Tong Zhang

JMLR 2019 Layer-Wise Learning Strategy for Nonparametric Tensor Product Smoothing Spline Regression and Graphical Models Kean Ming Tan, Junwei Lu, Tong Zhang, Han Liu

ICLR 2019 Marginal Policy Gradients: A Unified Family of Estimators for Bounded Action Spaces with Applications Carson Eisenach, Haichuan Yang, Ji Liu, Han Liu

UAI 2019 On Fast Convergence of Proximal Algorithms for SQRT-Lasso Optimization: Don’t Worry About Its Nonsmooth Loss Function Xinguo Li, Haoming Jiang, Jarvis Haupt, Raman Arora, Han Liu, Mingyi Hong, Tuo Zhao

MLOSS 2019 Picasso: A Sparse Learning Library for High Dimensional Data Analysis in R and Python Jason Ge, Xingguo Li, Haoming Jiang, Han Liu, Tong Zhang, Mengdi Wang, Tuo Zhao

IJCAI 2018 Discrete Factorization Machines for Fast Feature-Based Recommendation Han Liu, Xiangnan He, Fuli Feng, Liqiang Nie, Rui Liu, Hanwang Zhang

NeurIPS 2018 Exponentially Weighted Imitation Learning for Batched Historical Data Qing Wang, Jiechao Xiong, Lei Han, Peng Sun, Han Liu, Tong Zhang

ICML 2018 Feedback-Based Tree Search for Reinforcement Learning Daniel Jiang, Emmanuel Ekwedike, Han Liu

ICML 2018 Fully Decentralized Multi-Agent Reinforcement Learning with Networked Agents Kaiqing Zhang, Zhuoran Yang, Han Liu, Tong Zhang, Tamer Basar

ICML 2018 Graphical Nonconvex Optimization via an Adaptive Convex Relaxation Qiang Sun, Kean Ming Tan, Han Liu, Tong Zhang

AISTATS 2018 Minimax-Optimal Privacy-Preserving Sparse PCA in Distributed Systems Jason Ge, Zhaoran Wang, Mengdi Wang, Han Liu

IJCAI 2018 Multi-Task Clustering with Model Relation Learning Xiaotong Zhang, Xianchao Zhang, Han Liu, Jiebo Luo

JMLR 2018 On Semiparametric Exponential Family Graphical Models Zhuoran Yang, Yang Ning, Han Liu

NeurIPS 2018 Sketching Method for Large Scale Combinatorial Inference Wei Sun, Junwei Lu, Han Liu

ICML 2018 The Edge Density Barrier: Computational-Statistical Tradeoffs in Combinatorial Inference Hao Lu, Yuan Cao, Zhuoran Yang, Junwei Lu, Han Liu, Zhaoran Wang

NeurIPS 2017 Diffusion Approximations for Online Principal Component Estimation and Global Convergence Chris Junchi Li, Mengdi Wang, Han Liu, Tong Zhang

NeurIPS 2017 Estimating High-Dimensional Non-Gaussian Multiple Index Models via Stein’s Lemma Zhuoran Yang, Krishnakumar Balasubramanian, Zhaoran Wang, Han Liu

ICML 2017 High-Dimensional Non-Gaussian Single Index Models via Thresholded Score Function Estimation Zhuoran Yang, Krishnakumar Balasubramanian, Han Liu

NeurIPS 2017 Parametric Simplex Method for Sparse Learning Haotian Pang, Han Liu, Robert J Vanderbei, Tuo Zhao

AISTATS 2016 A Lasso-Based Sparse Knowledge Gradient Policy for Sequential Optimal Learning Yan Li, Han Liu, Warren B. Powell

NeurIPS 2016 Agnostic Estimation for Misspecified Phase Retrieval Models Matey Neykov, Zhaoran Wang, Han Liu

AISTATS 2016 An Improved Convergence Analysis of Cyclic Block Coordinate Descent-Type Methods for Strongly Convex Minimization Xingguo Li, Tuo Zhao, Raman Arora, Han Liu, Mingyi Hong

NeurIPS 2016 Blind Attacks on Machine Learners Alex Beatson, Zhaoran Wang, Han Liu

AISTATS 2016 Low-Rank and Sparse Structure Pursuit via Alternating Minimization Quanquan Gu, Zhaoran Wang, Han Liu

NeurIPS 2016 More Supervision, Less Computation: Statistical-Computational Tradeoffs in Weakly Supervised Learning Xinyang Yi, Zhaoran Wang, Zhuoran Yang, Constantine Caramanis, Han Liu

ICML 2016 On the Statistical Limits of Convex Relaxations Zhaoran Wang, Quanquan Gu, Han Liu

NeurIPS 2016 Online ICA: Understanding Global Dynamics of Nonconvex Optimization via Diffusion Processes Chris Junchi Li, Zhaoran Wang, Han Liu

IJCAI 2016 Self-Adapted Multi-Task Clustering Xianchao Zhang, Xiaotong Zhang, Han Liu

ICML 2016 Sparse Nonlinear Regression: Parameter Estimation Under Nonconvexity Zhuoran Yang, Zhaoran Wang, Han Liu, Yonina Eldar, Tong Zhang

ICML 2016 Stochastic Variance Reduced Optimization for Nonconvex Sparse Learning Xingguo Li, Tuo Zhao, Raman Arora, Han Liu, Jarvis Haupt

JMLR 2015 A Direct Estimation of High Dimensional Stationary Vector Autoregressions Fang Han, Huanran Lu, Han Liu

NeurIPS 2015 A Nonconvex Optimization Framework for Low Rank Matrix Estimation Tuo Zhao, Zhaoran Wang, Han Liu

JMLR 2015 Calibrated Multivariate Regression with Application to Neural Semantic Basis Discovery Han Liu, Lie Wang, Tuo Zhao

NeurIPS 2015 High Dimensional EM Algorithm: Statistical Optimization and Asymptotic Normality Zhaoran Wang, Quanquan Gu, Yang Ning, Han Liu

NeurIPS 2015 Local Smoothness in Variance Reduced Optimization Daniel Vainsencher, Han Liu, Tong Zhang

IJCAI 2015 Multi-Task Multi-View Clustering for Non-Negative Data Xianchao Zhang, Xiaotong Zhang, Han Liu

NeurIPS 2015 Non-Convex Statistical Optimization for Sparse Tensor Graphical Model Wei Sun, Zhaoran Wang, Han Liu, Guang Cheng

NeurIPS 2015 Optimal Linear Estimation Under Unknown Nonlinear Transform Xinyang Yi, Zhaoran Wang, Constantine Caramanis, Han Liu

ICML 2015 Robust Estimation of Transition Matrices in High Dimensional Heavy-Tailed Vector Autoregressive Processes Huitong Qiu, Sheng Xu, Fang Han, Han Liu, Brian Caffo

NeurIPS 2015 Robust Portfolio Optimization Huitong Qiu, Fang Han, Han Liu, Brian Caffo

MLOSS 2015 The Flare Package for High Dimensional Linear Regression and Precision Matrix Estimation in R Xingguo Li, Tuo Zhao, Xiaoming Yuan, Han Liu

NeurIPS 2014 Accelerated Mini-Batch Randomized Block Coordinate Descent Method Tuo Zhao, Mo Yu, Yiming Wang, Raman Arora, Han Liu

AISTATS 2014 Context Aware Group Nearest Shrunken Centroids in Large-Scale Genomic Studies Juemin Yang, Fang Han, Rafael A. Irizarry, Han Liu

JMLR 2014 Graph Estimation from Multi-Attribute Data Mladen Kolar, Han Liu, Eric P. Xing

NeurIPS 2014 Mode Estimation for High Dimensional Discrete Tree Graphical Models Chao Chen, Han Liu, Dimitris Metaxas, Tianqi Zhao

NeurIPS 2014 Multivariate Regression with Calibration Han Liu, Lie Wang, Tuo Zhao

AAAI 2014 Novel Density-Based Clustering Algorithms for Uncertain Data Xianchao Zhang, Han Liu, Xiaotong Zhang, Xinyue Liu

NeurIPS 2014 Sparse PCA with Oracle Property Quanquan Gu, Zhaoran Wang, Han Liu

MLOSS 2014 The FASTCLIME Package for Linear Programming and Large-Scale Precision Matrix Estimation in R Haotian Pang, Han Liu, Robert Vanderbei

NeurIPS 2014 Tighten After Relax: Minimax-Optimal Sparse PCA in Polynomial Time Zhaoran Wang, Huanran Lu, Han Liu

JMLR 2013 CODA: High Dimensional Copula Discriminant Analysis Fang Han, Tuo Zhao, Han Liu

ICML 2013 Feature Selection in High-Dimensional Classification Mladen Kolar, Han Liu

ICML 2013 Markov Network Estimation from Multi-Attribute Data Mladen Kolar, Han Liu, Eric Xing

ICML 2013 Principal Component Analysis on Non-Gaussian Dependent Data Fang Han, Han Liu

NeurIPS 2013 Robust Sparse Principal Component Regression Under the High Dimensional Elliptical Model Fang Han, Han Liu

NeurIPS 2013 Sparse Inverse Covariance Estimation with Calibration Tuo Zhao, Han Liu

AISTATS 2013 Sparse Principal Component Analysis for High Dimensional Multivariate Time Series Zhaoran Wang, Fang Han, Han Liu

ICML 2013 Transition Matrix Estimation in High Dimensional Time Series Fang Han, Han Liu

AISTATS 2012 Detecting Network Cliques with Radon Basis Pursuit Xiaoye Jiang, Yuan Yao, Han Liu, Leonidas Guibas

NeurIPS 2012 Exponential Concentration for Mutual Information Estimation with Application to Forests Han Liu, Larry Wasserman, John D. Lafferty

ICML 2012 High Dimensional Semiparametric Gaussian Copula Graphical Models Han Liu, Fang Han, Ming Yuan, John D. Lafferty, Larry A. Wasserman

AISTATS 2012 Marginal Regression for Multitask Learning Mladen Kolar, Han Liu

NeurIPS 2012 Semiparametric Principal Component Analysis Fang Han, Han Liu

NeurIPS 2012 Smooth-Projected Neighborhood Pursuit for High-Dimensional Nonparanormal Graph Estimation Tuo Zhao, Kathryn Roeder, Han Liu

AISTATS 2012 Sparse Additive Machine Tuo Zhao, Han Liu

MLOSS 2012 The Huge Package for High-Dimensional Undirected Graph Estimation in R Tuo Zhao, Han Liu, Kathryn Roeder, John Lafferty, Larry Wasserman

NeurIPS 2012 Transelliptical Component Analysis Fang Han, Han Liu

NeurIPS 2012 Transelliptical Graphical Models Han Liu, Fang Han, Cun-hui Zhang

JMLR 2011 Forest Density Estimation Han Liu, Min Xu, Haijie Gu, Anupam Gupta, John Lafferty, Larry Wasserman

COLT 2010 Forest Density Estimation Anupam Gupta, John D. Lafferty, Han Liu, Larry A. Wasserman, Min Xu

NeurIPS 2010 Graph-Valued Regression Han Liu, Xi Chen, Larry Wasserman, John D. Lafferty

AAAI 2010 Learning Spatial-Temporal Varying Graphs with Applications to Climate Data Analysis Xi Chen, Yan Liu, Han Liu, Jaime G. Carbonell

NeurIPS 2010 Multivariate Dyadic Regression Trees for Sparse Learning Problems Han Liu, Xi Chen

NeurIPS 2010 Stability Approach to Regularization Selection (StARS) for High Dimensional Graphical Models Han Liu, Kathryn Roeder, Larry Wasserman

AISTATS 2010 The Group Dantzig Selector Han Liu, Jian Zhang, Xiaoye Jiang, Jun Liu

ICML 2009 Blockwise Coordinate Descent Procedures for the Multi-Task Lasso, with Applications to Neural Semantic Basis Discovery Han Liu, Mark Palatucci, Jian Zhang

AISTATS 2009 Estimation Consistency of the Group Lasso and Its Applications Han Liu, Jian Zhang

NeurIPS 2009 Nonparametric Greedy Algorithms for the Sparse Learning Problem Han Liu, Xi Chen

JMLR 2009 The Nonparanormal: Semiparametric Estimation of High Dimensional Undirected Graphs Han Liu, John Lafferty, Larry Wasserman

NeurIPS 2008 Nonparametric Regression and Classification with Joint Sparsity Constraints Han Liu, Larry Wasserman, John D. Lafferty

NeurIPS 2007 SpAM: Sparse Additive Models Han Liu, Larry Wasserman, John D. Lafferty, Pradeep K. Ravikumar

AISTATS 2007 Sparse Nonparametric Density Estimation in High Dimensions Using the Rodeo Han Liu, John Lafferty, Larry Wasserman

ECML-PKDD 2004 An Efficient Method to Estimate Labelled Sample Size for Transductive LDA(QDA/MDA) Based on Bayes Risk Han Liu, Xiaobin Yuan, Qianying Tang, Rafal Kustra