Han Liu

262 papers A* 48A 17C 2Misc 6Journal 138Unranked 48
YearRankTypeTitle / Venue / Authors
2026 J jnl
Cell-JEPA: Latent Representation Learning for Single-Cell Transcriptomics.
CoRR
Ali ElSheikh, Rui-Xi Wang, Weimin Wu, Yibo Wen, Payam Dibaeinia, Jennifer Yuntong Zhang, Jerry Yao-Chieh Hu, Mei Knudson, Sudarshan Babu, Shao-Hua Sun, Aly A. Khan, Han Liu
2026 J jnl
Phys4D: Fine-Grained Physics-Consistent 4D Modeling from Video Diffusion.
CoRR
Haoran Lu, Shang Wu, Jianshu Zhang, Maojiang Su, Guo Ye, Chenwei Xu, Lie Lu, Pranav Maneriker, Fan Du, Manling Li, Zhaoran Wang, Han Liu
2026 — conf
PromptFE: Automated Feature Engineering by Prompting.
EACL (Volume 1: Long Papers)
Yufeng Zou, Jean Utke, Diego Klabjan, Han Liu
2026 J jnl
Training-Free Adaptation of Diffusion Models via Doob's
CoRR
Qijie Zhu, Zeqi Ye, Han Liu, Zhaoran Wang, Minshuo Chen
2025 J jnl
A Theoretical Analysis of Discrete Flow Matching Generative Models.
CoRR
Maojiang Su, Mingcheng Lu, Jerry Yao-Chieh Hu, Shang Wu, Zhao Song, Alex Daniel Reneau, Han Liu
2025 — conf
Adaptive Batch Size Schedules for Distributed Training of Language Models with Data and Model Parallelism.
CPAL
Tim Tsz-Kit Lau, Weijian Li, Chenwei Xu, Han Liu, Mladen Kolar
2025 J jnl
Are Hallucinations Bad Estimations?
CoRR
Hude Liu, Jerry Yao-Chieh Hu, Jennifer Yuntong Zhang, Zhao Song, Han Liu
2025 J jnl
Attention Mechanism, Max-Affine Partition, and Universal Approximation.
CoRR
Hude Liu, Jerry Yao-Chieh Hu, Zhao Song, Han Liu
2025 A* conf
Chain-of-Action: Faithful and Multimodal Question Answering through Large Language Models.
ICLR
Zhenyu Pan, Haozheng Luo, Manling Li, Han Liu
2025 A* conf
Computational Limits of Low-Rank Adaptation (LoRA) Fine-Tuning for Transformer Models.
ICLR
Jerry Yao-Chieh Hu, Maojiang Su, En-Jui Kuo, Zhao Song, Han Liu
2025 J jnl
DNABERT-S: pioneering species differentiation with species-aware DNA embeddings.
Bioinform.
Zhihan Zhou, Weimin Wu, Harrison Ho, Jiayi Wang, Lizhen Shi, Ramana V. Davuluri, Zhong Wang, Han Liu
2025 J jnl
DeepVRegulome: DNABERT-based deep-learning framework for predicting the functional impact of short genomic variants on the human regulome.
CoRR
Pratik Dutta, Matthew Obusan, Rekha Sathian, Max Chao, Pallavi Surana, Nimisha Papineni, Yanrong Ji, Zhihan Zhou, Han Liu, Alisa Yurovsky, Ramana V. Davuluri
2025 — conf
Do Code LLMs Understand Design Patterns?
LLM4Code@ICSE
Zhenyu Pan, Xuefeng Song, Yunkun Wang, Rongyu Cao, Binhua Li, Yongbin Li, Han Liu
2025 J jnl
Do Code LLMs Understand Design Patterns?
CoRR
Zhenyu Pan, Xuefeng Song, Yunkun Wang, Rongyu Cao, Binhua Li, Yongbin Li, Han Liu
2025 A* conf
Fast and Low-Cost Genomic Foundation Models via Outlier Removal.
ICML
Haozheng Luo, Chenghao Qiu, Maojiang Su, Zhihan Zhou, Zoe Mehta, Guo Ye, Jerry Yao-Chieh Hu, Han Liu
2025 J jnl
Fast and Low-Cost Genomic Foundation Models via Outlier Removal.
CoRR
Haozheng Luo, Chenghao Qiu, Maojiang Su, Zhihan Zhou, Zoe Mehta, Guo Ye, Jerry Yao-Chieh Hu, Han Liu
2025 A* conf
Fundamental Limits of Prompt Tuning Transformers: Universality, Capacity and Efficiency.
ICLR
Jerry Yao-Chieh Hu, Wei-Po Wang, Ammar Gilani, Chenyang Li, Zhao Song, Han Liu
2025 J jnl
GenoArmory: A Unified Evaluation Framework for Adversarial Attacks on Genomic Foundation Models.
CoRR
Haozheng Luo, Chenghao Qiu, Yimin Wang, Shang Wu, Jiahao Yu, Han Liu, Binghui Wang, Yan Chen
2025 J jnl
Genome-Factory: An Integrated Library for Tuning, Deploying, and Interpreting Genomic Models.
CoRR
Weimin Wu, Xuefeng Song, Yibo Wen, Qinjie Lin, Zhihan Zhou, Jerry Yao-Chieh Hu, Zhong Wang, Han Liu
2025 J jnl
In-Context Algorithm Emulation in Fixed-Weight Transformers.
CoRR
Jerry Yao-Chieh Hu, Hude Liu, Jennifer Yuntong Zhang, Han Liu
2025 A* conf
In-Context Deep Learning via Transformer Models.
ICML
Weimin Wu, Maojiang Su, Jerry Yao-Chieh Hu, Zhao Song, Han Liu
2025 A* conf
In-Context Learning as Conditioned Associative Memory Retrieval.
ICML
Weimin Wu, Teng-Yun Hsiao, Jerry Yao-Chieh Hu, Wenxin Zhang, Han Liu
2025 A* conf
Incorporating Gradients to Rules: Towards Lightweight, Adaptive Provenance-based Intrusion Detection.
NDSS
Lingzhi Wang, Xiangmin Shen, Weijian Li, Zhenyuan Li, R. Sekar, Han Liu, Yan Chen
2025 J jnl
Learning multiple coordinated agents under directed acyclic graph constraints.
Expert Syst. Appl.
Jaeyeon Jang, Diego Klabjan, Han Liu, Nital S. Patel, Xiuqi Li, Balakrishnan Ananthanarayanan, Husam Dauod, Tzung-Han Juang
2025 J jnl
MetaSpatial: Reinforcing 3D Spatial Reasoning in VLMs for the Metaverse.
CoRR
Zhenyu Pan, Han Liu
2025 A* conf
Mind the Inconspicuous: Revealing the Hidden Weakness in Aligned LLMs' Refusal Boundaries.
USENIX Security Symposium
Jiahao Yu, Haozheng Luo, Jerry Yao-Chieh Hu, Yan Chen, Wenbo Guo, Han Liu, Xinyu Xing
2025 J jnl
Minimalist Softmax Attention Provably Learns Constrained Boolean Functions.
CoRR
Jerry Yao-Chieh Hu, Xiwen Zhang, Maojiang Su, Zhao Song, Han Liu
2025 A* conf
Nonparametric Modern Hopfield Models.
ICML
Jerry Yao-Chieh Hu, Bo-Yu Chen, Dennis Wu, Feng Ruan, Han Liu
2025 J jnl
On Flow Matching KL Divergence.
CoRR
Maojiang Su, Jerry Yao-Chieh Hu, Sophia Pi, Han Liu
2025 A* conf
On Statistical Rates of Conditional Diffusion Transformers: Approximation, Estimation and Minimax Optimality.
ICLR
Jerry Yao-Chieh Hu, Weimin Wu, Yi-Chen Lee, Yu-Chao Huang, Minshuo Chen, Han Liu
2025 J jnl
Scalable multi-agent reinforcement learning for factory-wide dynamic scheduling in semiconductor manufacturing.
Eng. Appl. Artif. Intell.
Jaeyeon Jang, Diego Klabjan, Han Liu, Nital S. Patel, Xiuqi Li, Balakrishnan Ananthanarayanan, Husam Dauod, Tzung-Han Juang
2025 A conf
Statistical Guarantees for Lifelong Reinforcement Learning using PAC-Bayes Theory.
AISTATS
Zhi Zhang, Chris Chow, Yasi Zhang, Yanchao Sun, Haochen Zhang, Eric Hanchen Jiang, Han Liu, Furong Huang, Yuchen Cui, Oscar Hernan Madrid Padilla
2024 J jnl
AdAdaGrad: Adaptive Batch Size Schemes for Adaptive Gradient Methods.
CoRR
Tim Tsz-Kit Lau, Han Liu, Mladen Kolar
2024 J jnl
Adaptive Batch Size Schedules for Distributed Training of Language Models with Data and Model Parallelism.
CoRR
Tim Tsz-Kit Lau, Weijian Li, Chenwei Xu, Han Liu, Mladen Kolar
2024 J jnl
AlignAb: Pareto-Optimal Energy Alignment for Designing Nature-Like Antibodies.
CoRR
Yibo Wen, Chenwei Xu, Jerry Yao-Chieh Hu, Han Liu
2024 A* conf
BiSHop: Bi-Directional Cellular Learning for Tabular Data with Generalized Sparse Modern Hopfield Model.
ICML
Chenwei Xu, Yu-Chao Huang, Jerry Yao-Chieh Hu, Weijian Li, Ammar Gilani, Hsi-Sheng Goan, Han Liu
2024 J jnl
BiSHop: Bi-Directional Cellular Learning for Tabular Data with Generalized Sparse Modern Hopfield Model.
CoRR
Chenwei Xu, Yu-Chao Huang, Jerry Yao-Chieh Hu, Weijian Li, Ammar Gilani, Hsi-Sheng Goan, Han Liu
2024 J jnl
Chain-of-Action: Faithful and Multimodal Question Answering through Large Language Models.
CoRR
Zhenyu Pan, Haozheng Luo, Manling Li, Han Liu
2024 J jnl
Codev-Bench: How Do LLMs Understand Developer-Centric Code Completion?
CoRR
Zhenyu Pan, Rongyu Cao, Yongchang Cao, Yingwei Ma, Binhua Li, Fei Huang, Han Liu, Yongbin Li
2024 J jnl
Communication-Efficient Adaptive Batch Size Strategies for Distributed Local Gradient Methods.
CoRR
Tim Tsz-Kit Lau, Weijian Li, Chenwei Xu, Han Liu, Mladen Kolar
2024 J jnl
Computational Limits of Low-Rank Adaptation (LoRA) for Transformer-Based Models.
CoRR
Jerry Yao-Chieh Hu, Maojiang Su, En-Jui Kuo, Zhao Song, Han Liu
2024 J jnl
Conv-CoA: Improving Open-domain Question Answering in Large Language Models via Conversational Chain-of-Action.
CoRR
Zhenyu Pan, Haozheng Luo, Manling Li, Han Liu
2024 A* conf
DNABERT-2: Efficient Foundation Model and Benchmark For Multi-Species Genomes.
ICLR
Zhihan Zhou, Yanrong Ji, Weijian Li, Pratik Dutta, Ramana V. Davuluri, Han Liu
2024 J jnl
DNABERT-S: Learning Species-Aware DNA Embedding with Genome Foundation Models.
CoRR
Zhihan Zhou, Weimin Wu, Harrison Ho, Jiayi Wang, Lizhen Shi, Ramana V. Davuluri, Zhong Wang, Han Liu
2024 A* conf
DOS
ICRA
Guo Ye, Qinjie Lin, Zening Luo, Han Liu
2024 J jnl
Decoupled Alignment for Robust Plug-and-Play Adaptation.
CoRR
Haozheng Luo, Jiahao Yu, Wenxin Zhang, Jialong Li, Jerry Yao-Chieh Hu, Xinyu Xing, Han Liu
2024 J jnl
Differentially Private Kernel Density Estimation.
CoRR
Erzhi Liu, Jerry Yao-Chieh Hu, Alex Daniel Reneau, Zhao Song, Han Liu
2024 J jnl
Efficient Action Robust Reinforcement Learning with Probabilistic Policy Execution Uncertainty.
Trans. Mach. Learn. Res.
Guanlin Liu, Zhihan Zhou, Han Liu, Lifeng Lai
2024 J jnl
Enhancing Jailbreak Attack Against Large Language Models through Silent Tokens.
CoRR
Jiahao Yu, Haozheng Luo, Jerry Yao-Chieh Hu, Wenbo Guo, Han Liu, Xinyu Xing
2024 J jnl
Fundamental Limits of Prompt Tuning Transformers: Universality, Capacity and Efficiency.
CoRR
Jerry Yao-Chieh Hu, Wei-Po Wang, Ammar Gilani, Chenyang Li, Zhao Song, Han Liu
2024 A* conf
Global Convergence in Training Large-Scale Transformers.
NeurIPS
Cheng Gao, Yuan Cao, Zihao Li, Yihan He, Mengdi Wang, Han Liu, Jason M. Klusowski, Jianqing Fan
2024 J jnl
Global Convergence in Training Large-Scale Transformers.
CoRR
Cheng Gao, Yuan Cao, Zihao Li, Yihan He, Mengdi Wang, Han Liu, Jason M. Klusowski, Jianqing Fan
2024 J jnl
HeteGraph-Mamba: Heterogeneous Graph Learning via Selective State Space Model.
CoRR
Zhenyu Pan, Yoonsung Jeong, Xiaoda Liu, Han Liu
2024 J jnl
Incorporating Gradients to Rules: Towards Lightweight, Adaptive Provenance-based Intrusion Detection.
CoRR
Lingzhi Wang, Xiangmin Shen, Weijian Li, Zhenyuan Li, R. Sekar, Han Liu, Yan Chen
2024 — conf
ML-Based Real-Time Control at the Edge: An Approach Using hls4ml.
IPDPS (Workshops)
Rui Shi, Seda Ogrenci, Jeremy M. Arnold, J. R. Berlioz, Pierrick Hanlet, Kyle J. Hazelwood, Michelle A. Ibrahim, Han Liu, V. P. Nagaslaev, Aakaash Narayanan, D. J. Nicklaus, Jovan Mitrevski, Gauri Pradhan, A. L. Saewert, B. A. Schupbach, Kiyomi Seiya, Mattson Thieme, R. M. Thurman-Keup, N. V. Tran
2024 A conf
Multivariate Time Series Forecasting By Graph Attention Networks With Theoretical Guarantees.
AISTATS
Zhi Zhang, Weijian Li, Han Liu
2024 J jnl
Nonparametric Modern Hopfield Models.
CoRR
Jerry Yao-Chieh Hu, Bo-Yu Chen, Dennis Wu, Feng Ruan, Han Liu
2024 A* conf
On Computational Limits of Modern Hopfield Models: A Fine-Grained Complexity Analysis.
ICML
Jerry Yao-Chieh Hu, Thomas Lin, Zhao Song, Han Liu
2024 J jnl
On Computational Limits of Modern Hopfield Models: A Fine-Grained Complexity Analysis.
CoRR
Jerry Yao-Chieh Hu, Thomas Lin, Zhao Song, Han Liu
2024 J jnl
On Differentially Private String Distances.
CoRR
Jerry Yao-Chieh Hu, Erzhi Liu, Han Liu, Zhao Song, Lichen Zhang
2024 A* conf
On Statistical Rates and Provably Efficient Criteria of Latent Diffusion Transformers (DiTs).
NeurIPS
Jerry Yao-Chieh Hu, Weimin Wu, Zhuoru Li, Sophia Pi, Zhao Song, Han Liu
2024 J jnl
On Statistical Rates and Provably Efficient Criteria of Latent Diffusion Transformers (DiTs).
CoRR
Jerry Yao-Chieh Hu, Weimin Wu, Zhuoru Li, Zhao Song, Han Liu
2024 J jnl
On Statistical Rates of Conditional Diffusion Transformers: Approximation, Estimation and Minimax Optimality.
CoRR
Jerry Yao-Chieh Hu, Weimin Wu, Yi-Chen Lee, Yu-Chao Huang, Minshuo Chen, Han Liu
2024 A* conf
One-Layer Transformer Provably Learns One-Nearest Neighbor In Context.
NeurIPS
Zihao Li, Yuan Cao, Cheng Gao, Yihan He, Han Liu, Jason M. Klusowski, Jianqing Fan, Mengdi Wang
2024 J jnl
One-Layer Transformer Provably Learns One-Nearest Neighbor In Context.
CoRR
Zihao Li, Yuan Cao, Cheng Gao, Yihan He, Han Liu, Jason M. Klusowski, Jianqing Fan, Mengdi Wang
2024 A* conf
Outlier-Efficient Hopfield Layers for Large Transformer-Based Models.
ICML
Jerry Yao-Chieh Hu, Pei-Hsuan Chang, Haozheng Luo, Hong-Yu Chen, Weijian Li, Wei-Po Wang, Han Liu
2024 J jnl
Outlier-Efficient Hopfield Layers for Large Transformer-Based Models.
CoRR
Jerry Yao-Chieh Hu, Pei-Hsuan Chang, Robin Luo, Hong-Yu Chen, Weijian Li, Wei-Po Wang, Han Liu
2024 A* conf
Provably Optimal Memory Capacity for Modern Hopfield Models: Transformer-Compatible Dense Associative Memories as Spherical Codes.
NeurIPS
Jerry Yao-Chieh Hu, Dennis Wu, Han Liu
2024 J jnl
Provably Optimal Memory Capacity for Modern Hopfield Models: Transformer-Compatible Dense Associative Memories as Spherical Codes.
CoRR
Jerry Yao-Chieh Hu, Dennis Wu, Han Liu
2024 A* conf
STanHop: Sparse Tandem Hopfield Model for Memory-Enhanced Time Series Prediction.
ICLR
Dennis Wu, Jerry Yao-Chieh Hu, Weijian Li, Bo-Yu Chen, Han Liu
2024 J jnl
Scalable Multi-agent Reinforcement Learning for Factory-wide Dynamic Scheduling.
CoRR
Jaeyeon Jang, Diego Klabjan, Han Liu, Nital S. Patel, Xiuqi Li, Balakrishnan Ananthanarayanan, Husam Dauod, Tzung-Han Juang
2024 J jnl
Statistical Guarantees for Lifelong Reinforcement Learning using PAC-Bayesian Theory.
CoRR
Zhi Zhang, Chris Chow, Yasi Zhang, Yanchao Sun, Haochen Zhang, Eric Hanchen Jiang, Han Liu, Furong Huang, Yuchen Cui, Oscar Hernan Madrid Padilla
2024 J jnl
Transformers are Deep Optimizers: Provable In-Context Learning for Deep Model Training.
CoRR
Weimin Wu, Maojiang Su, Jerry Yao-Chieh Hu, Zhao Song, Han Liu
2024 J jnl
USE: Dynamic User Modeling with Stateful Sequence Models.
CoRR
Zhihan Zhou, Qixiang Fang, Leonardo Neves, Francesco Barbieri, Yozen Liu, Han Liu, Maarten W. Bos, Ron Dotsch
2024 A* conf
Uniform Memory Retrieval with Larger Capacity for Modern Hopfield Models.
ICML
Dennis Wu, Jerry Yao-Chieh Hu, Teng-Yun Hsiao, Han Liu
2024 J jnl
Uniform Memory Retrieval with Larger Capacity for Modern Hopfield Models.
CoRR
Dennis Wu, Jerry Yao-Chieh Hu, Teng-Yun Hsiao, Han Liu
2024 — conf
sEMG-vision Tra: A Gesture Recognition Method Based on Surface EMG Signal-Vision Fusion.
SOLI
Weili Ding, Shuhui Zhang, Han Liu
2023 J jnl
Beyond PID Controllers: PPO with Neuralized PID Policy for Proton Beam Intensity Control in Mu2e.
CoRR
Chenwei Xu, Jerry Yao-Chieh Hu, Aakaash Narayanan, Mattson Thieme, Vladimir Nagaslaev, Mark Austin, Jeremy Arnold, Jose Berlioz, Pierrick Hanlet, Aisha Ibrahim, Dennis Nicklaus, Jovan Mitrevski, Jason Michael St. John, Gauri Pradhan, Andrea Saewert, Kiyomi Seiya, Brian Schupbach, Randy Thurman-Keup, Nhan Tran, Rui Shi, Seda Ogrenci, Alexis Maya-Isabelle Shuping, Kyle J. Hazelwood, Han Liu
2023 J jnl
DNABERT-2: Efficient Foundation Model and Benchmark For Multi-Species Genome.
CoRR
Zhihan Zhou, Yanrong Ji, Weijian Li, Pratik Dutta, Ramana V. Davuluri, Han Liu
2023 A* conf
EMS®: A Massive Computational Experiment Management System towards Data-driven Robotics.
ICRA
Qinjie Lin, Guo Ye, Han Liu
2023 J jnl
Efficient Action Robust Reinforcement Learning with Probabilistic Policy Execution Uncertainty.
CoRR
Guanlin Liu, Zhihan Zhou, Han Liu, Lifeng Lai
2023 A* conf
Feature Programming for Multivariate Time Series Prediction.
ICML
Alex Daniel Reneau, Jerry Yao-Chieh Hu, Ammar Gilani, Han Liu
2023 J jnl
Feature Programming for Multivariate Time Series Prediction.
CoRR
Alex Daniel Reneau, Jerry Yao-Chieh Hu, Chenwei Xu, Weijian Li, Ammar Gilani, Han Liu
2023 A* conf
Ising-Traffic: Using Ising Machine Learning to Predict Traffic Congestion under Uncertainty.
AAAI
Zhenyu Pan, Anshujit Sharma, Jerry Yao-Chieh Hu, Zhuo Liu, Ang Li, Han Liu, Michael C. Huang, Tong Geng
2023 J jnl
Learning Multiple Coordinated Agents under Directed Acyclic Graph Constraints.
CoRR
Jaeyeon Jang, Diego Klabjan, Han Liu, Nital S. Patel, Xiuqi Li, Balakrishnan Ananthanarayanan, Husam Dauod, Tzung-Han Juang
2023 J jnl
ML-based Real-Time Control at the Edge: An Approach Using hls4ml.
CoRR
Rui Shi, Seda Ogrenci, Jeremy M. Arnold, J. R. Berlioz, Pierrick Hanlet, Kyle J. Hazelwood, Michelle A. Ibrahim, Han Liu, V. P. Nagaslaev, Aakaash Narayanan, D. J. Nicklaus, Jovan Mitrevski, Gauri Pradhan, A. L. Saewert, B. A. Schupbach, Kiyomi Seiya, Mattson Thieme, R. M. Thurman-Keup, N. V. Tran
2023 J jnl
Non-Log-Concave and Nonsmooth Sampling via Langevin Monte Carlo Algorithms.
CoRR
Tim Tsz-Kit Lau, Han Liu, Thomas Pock
2023 A* conf
On Sparse Modern Hopfield Model.
NeurIPS
Jerry Yao-Chieh Hu, Donglin Yang, Dennis Wu, Chenwei Xu, Bo-Yu Chen, Han Liu
2023 J jnl
On Sparse Modern Hopfield Model.
CoRR
Jerry Yao-Chieh Hu, Donglin Yang, Dennis Wu, Chenwei Xu, Bo-Yu Chen, Han Liu
2023 J jnl
STanHop: Sparse Tandem Hopfield Model for Memory-Enhanced Time Series Prediction.
CoRR
Dennis Wu, Jerry Yao-Chieh Hu, Weijian Li, Bo-Yu Chen, Han Liu
2023 J jnl
Sparse PCA with Oracle Property.
CoRR
Quanquan Gu, Zhaoran Wang, Han Liu
2022 A* conf
Bregman Proximal Langevin Monte Carlo via Bregman-Moreau Envelopes.
ICML
Tim Tsz-Kit Lau, Han Liu
2022 J jnl
Bregman Proximal Langevin Monte Carlo via Bregman-Moreau Envelopes.
CoRR
Tim Tsz-Kit Lau, Han Liu
2022 J jnl
Interdisciplinary Discovery of Nanomaterials Based on Convolutional Neural Networks.
CoRR
Tong Xie, Yuwei Wan, Weijian Li, Qingyuan Linghu, Shaozhou Wang, Yalun Cai, Han Liu, Chunyu Kit, Clara Grazian, Bram Hoex
2022 J jnl
Large-Scale Multi-Document Summarization with Information Extraction and Compression.
CoRR
Ning Wang, Han Liu, Diego Klabjan
2022 J jnl
Learning to Infer Belief Embedded Communication.
CoRR
Guo Ye, Han Liu, Biswa Sengupta
2022 J jnl
Predicting Drug Repurposing Candidates and Their Mechanisms from A Biomedical Knowledge Graph.
CoRR
Chunyu Ma, Zhihan Zhou, Han Liu, David Koslicki
2022 A* conf
Reinforcement Learning under a Multi-agent Predictive State Representation Model: Method and Theory.
ICLR
Zhi Zhang, Zhuoran Yang, Han Liu, Pratap Tokekar, Furong Huang
2022 J jnl
Switch Trajectory Transformer with Distributional Value Approximation for Multi-Task Reinforcement Learning.
CoRR
Qinjie Lin, Han Liu, Biswa Sengupta
2022 J jnl
Wasserstein Distributionally Robust Optimization via Wasserstein Barycenters.
CoRR
Tim Tsz-Kit Lau, Han Liu
2021 J jnl
DNABERT: pre-trained Bidirectional Encoder Representations from Transformers model for DNA-language in genome.
Bioinform.
Yanrong Ji, Zhihan Zhou, Han Liu, Ramana V. Davuluri
2021 J jnl
Finite-Sample Analysis for Decentralized Batch Multiagent Reinforcement Learning With Networked Agents.
IEEE Trans. Autom. Control.
Kaiqing Zhang, Zhuoran Yang, Han Liu, Tong Zhang, Tamer Basar
2021 Misc conf
RoboFlow: a Data-centric Workflow Management System for Developing AI-enhanced Robots.
CoRL
Qinjie Lin, Guo Ye, Jiayi Wang, Han Liu
2021 J jnl
Robust Scatter Matrix Estimation for High Dimensional Distributions With Heavy Tail.
IEEE Trans. Inf. Theory
Junwei Lu, Fang Han, Han Liu
2021 — conf
Trade the Event: Corporate Events Detection for News-Based Event-Driven Trading.
ACL/IJCNLP (Findings)
Zhihan Zhou, Liqian Ma, Han Liu
2021 J jnl
Trade the Event: Corporate Events Detection for News-Based Event-Driven Trading.
CoRR
Zhihan Zhou, Liqian Ma, Han Liu
2020 J jnl
Agnostic Estimation for Phase Retrieval.
J. Mach. Learn. Res.
Matey Neykov, Zhaoran Wang, Han Liu
2020 A* conf
Collision-free Navigation of Human-centered Robots via Markov Games.
ICRA
Guo Ye, Qinjie Lin, Tzung-Han Juang, Han Liu
2020 A* conf
Few-shot Slot Tagging with Collapsed Dependency Transfer and Label-enhanced Task-adaptive Projection Network.
ACL
Yutai Hou, Wanxiang Che, Yongkui Lai, Zhihan Zhou, Yijia Liu, Han Liu, Ting Liu
2020 J jnl
Few-shot Slot Tagging with Collapsed Dependency Transfer and Label-enhanced Task-adaptive Projection Network.
CoRR
Yutai Hou, Wanxiang Che, Yongkui Lai, Zhihan Zhou, Yijia Liu, Han Liu, Ting Liu
2020 A* conf
GLAD: Learning Sparse Graph Recovery.
ICLR
Harsh Shrivastava, Xinshi Chen, Binghong Chen, Guanghui Lan, Srinivas Aluru, Han Liu, Le Song
2020 A* conf
Learning to Plan in High Dimensions via Neural Exploration-Exploitation Trees.
ICLR
Binghong Chen, Bo Dai, Qinjie Lin, Guo Ye, Han Liu, Le Song
2020 J jnl
Picasso: A Sparse Learning Library for High Dimensional Data Analysis in R and Python.
CoRR
Jason Ge, Xingguo Li, Haoming Jiang, Han Liu, Tong Zhang, Mengdi Wang, Tuo Zhao
2020 J jnl
Tensor Graphical Model: Non-Convex Optimization and Statistical Inference.
IEEE Trans. Pattern Anal. Mach. Intell.
Xiang Lyu, Will Wei Sun, Zhaoran Wang, Han Liu, Jian Yang, Guang Cheng
2020 J jnl
The flare Package for High Dimensional Linear Regression and Precision Matrix Estimation in R.
CoRR
Xingguo Li, Tuo Zhao, Xiaoming Yuan, Han Liu
2020 J jnl
The huge Package for High-dimensional Undirected Graph Estimation in R.
CoRR
Tuo Zhao, Han Liu, Kathryn Roeder, John Lafferty, Larry A. Wasserman
2019 — conf
AOMO: An AI-aided Optimizer for Microservices Orchestration.
SIGCOMM Posters and Demos
Xue Leng, Tzung-Han Juang, Yan Chen, Han Liu
2019 J jnl
AdvCodec: Towards A Unified Framework for Adversarial Text Generation.
CoRR
Boxin Wang, Hengzhi Pei, Han Liu, Bo Li
2019 J jnl
Blessing of massive scale: spatial graphical model estimation with a total cardinality constraint approach.
Math. Program.
Ethan X. Fang, Han Liu, Mengdi Wang
2019 J jnl
Efficient, certifiably optimal clustering with applications to latent variable graphical models.
Math. Program.
Carson Eisenach, Han Liu
2019 J jnl
Few-Shot Sequence Labeling with Label Dependency Transfer.
CoRR
Yutai Hou, Zhihan Zhou, Yijia Liu, Ning Wang, Wanxiang Che, Han Liu, Ting Liu
2019 A* conf
Grid-Wise Control for Multi-Agent Reinforcement Learning in Video Game AI.
ICML
Lei Han, Peng Sun, Yali Du, Jiechao Xiong, Qing Wang, Xinghai Sun, Han Liu, Tong Zhang
2019 J jnl
Layer-Wise Learning Strategy for Nonparametric Tensor Product Smoothing Spline Regression and Graphical Models.
J. Mach. Learn. Res.
Kean Ming Tan, Junwei Lu, Tong Zhang, Han Liu
2019 — conf
Marginal Policy Gradients: A Unified Family of Estimators for Bounded Action Spaces with Applications.
ICLR (Poster)
Carson Eisenach, Haichuan Yang, Ji Liu, Han Liu
2019 J jnl
Modelling and simulation of highly mixed traffic flow on two-lane two-way urban streets.
Simul. Model. Pract. Theory
Jian Sun, Han Liu, Zian Ma
2019 J jnl
More Supervision, Less Computation: Statistical-Computational Tradeoffs in Weakly Supervised Learning.
CoRR
Xinyang Yi, Zhaoran Wang, Zhuoran Yang, Constantine Caramanis, Han Liu
2019 A conf
On Fast Convergence of Proximal Algorithms for SQRT-Lasso Optimization: Don't Worry About its Nonsmooth Loss Function.
UAI
Xingguo Li, Haoming Jiang, Jarvis D. Haupt, Raman Arora, Han Liu, Mingyi Hong, Tuo Zhao
2019 J jnl
Picasso: A Sparse Learning Library for High Dimensional Data Analysis in R and Python.
J. Mach. Learn. Res.
Jason Ge, Xingguo Li, Haoming Jiang, Han Liu, Tong Zhang, Mengdi Wang, Tuo Zhao
2019 J jnl
Symmetry, Saddle Points, and Global Optimization Landscape of Nonconvex Matrix Factorization.
IEEE Trans. Inf. Theory
Xingguo Li, Junwei Lu, Raman Arora, Jarvis D. Haupt, Han Liu, Zhaoran Wang, Tuo Zhao
2018 J jnl
A convex formulation for high-dimensional sparse sliced inverse regression.
CoRR
Kean Ming Tan, Zhaoran Wang, Tong Zhang, Han Liu, R. Dennis Cook
2018 J jnl
Curse of Heterogeneity: Computational Barriers in Sparse Mixture Models and Phase Retrieval.
CoRR
Jianqing Fan, Han Liu, Zhaoran Wang, Zhuoran Yang
2018 J jnl
Diffusion Approximations for Online Principal Component Estimation and Global Convergence.
CoRR
Chris Junchi Li, Mengdi Wang, Han Liu, Tong Zhang
2018 A* conf
Exponentially Weighted Imitation Learning for Batched Historical Data.
NeurIPS
Qing Wang, Jiechao Xiong, Lei Han, Peng Sun, Han Liu, Tong Zhang
2018 A* conf
Feedback-Based Tree Search for Reinforcement Learning.
ICML
Daniel R. Jiang, Emmanuel Ekwedike, Han Liu
2018 J jnl
Feedback-Based Tree Search for Reinforcement Learning.
CoRR
Daniel R. Jiang, Emmanuel Ekwedike, Han Liu
2018 J jnl
Finite-Sample Analyses for Fully Decentralized Multi-Agent Reinforcement Learning.
CoRR
Kaiqing Zhang, Zhuoran Yang, Han Liu, Tong Zhang, Tamer Basar
2018 A* conf
Fully Decentralized Multi-Agent Reinforcement Learning with Networked Agents.
ICML
Kaiqing Zhang, Zhuoran Yang, Han Liu, Tong Zhang, Tamer Basar
2018 J jnl
Fully Decentralized Multi-Agent Reinforcement Learning with Networked Agents.
CoRR
Kaiqing Zhang, Zhuoran Yang, Han Liu, Tong Zhang, Tamer Basar
2018 J jnl
Fully Implicit Online Learning.
CoRR
Chao-Bing Song, Ji Liu, Han Liu, Yong Jiang, Tong Zhang
2018 A* conf
Graphical Nonconvex Optimization via an Adaptive Convex Relaxation.
ICML
Qiang Sun, Kean Ming Tan, Han Liu, Tong Zhang
2018 J jnl
Marginal Policy Gradients for Complex Control.
CoRR
Carson Eisenach, Haichuan Yang, Ji Liu, Han Liu
2018 J jnl
Max-norm optimization for robust matrix recovery.
Math. Program.
Ethan X. Fang, Han Liu, Kim-Chuan Toh, Wen-Xin Zhou
2018 A conf
Minimax-Optimal Privacy-Preserving Sparse PCA in Distributed Systems.
AISTATS
Jason Ge, Zhaoran Wang, Mengdi Wang, Han Liu
2018 J jnl
Near-optimal stochastic approximation for online principal component estimation.
Math. Program.
Chris Junchi Li, Mengdi Wang, Han Liu, Tong Zhang
2018 J jnl
On Semiparametric Exponential Family Graphical Models.
J. Mach. Learn. Res.
Zhuoran Yang, Yang Ning, Han Liu
2018 J jnl
Online ICA: Understanding Global Dynamics of Nonconvex Optimization via Diffusion Processes.
CoRR
Chris Junchi Li, Zhaoran Wang, Han Liu
2018 J jnl
Parametrized Deep Q-Networks Learning: Reinforcement Learning with Discrete-Continuous Hybrid Action Space.
CoRR
Jiechao Xiong, Qing Wang, Zhuoran Yang, Peng Sun, Lei Han, Yang Zheng, Haobo Fu, Tong Zhang, Ji Liu, Han Liu
2018 J jnl
RWEN: response-weighted elastic net for prediction of chemosensitivity of cancer cell lines.
Bioinform.
Amrita Basu, Ritwik Mitra, Han Liu, Stuart L. Schreiber, Paul A. Clemons
2018 A* conf
Sketching Method for Large Scale Combinatorial Inference.
NeurIPS
Wei Sun, Junwei Lu, Han Liu
2018 Misc conf
Symmetry. Saddle Points, and Global Optimization Landscape of Nonconvex Matrix Factorization.
ITA
Xingguo Li, Jarvis D. Haupt, Junwei Lu, Zhaoran Wang, Raman Arora, Han Liu, Tuo Zhao
2018 J jnl
TStarBots: Defeating the Cheating Level Builtin AI in StarCraft II in the Full Game.
CoRR
Peng Sun, Xinghai Sun, Lei Han, Jiechao Xiong, Qing Wang, Bo Li, Yang Zheng, Ji Liu, Yongsheng Liu, Han Liu, Tong Zhang
2018 A* conf
The Edge Density Barrier: Computational-Statistical Tradeoffs in Combinatorial Inference.
ICML
Hao Lu, Yuan Cao, Junwei Lu, Han Liu, Zhaoran Wang
2017 J jnl
Continual Learning in Generative Adversarial Nets.
CoRR
Ari Seff, Alex Beatson, Daniel Suo, Han Liu
2017 — conf
Estimating High-dimensional Non-Gaussian Multiple Index Models via Stein's Lemma.
NIPS
Zhuoran Yang, Krishnakumar Balasubramanian, Zhaoran Wang, Han Liu
2017 A* conf
High-dimensional Non-Gaussian Single Index Models via Thresholded Score Function Estimation.
ICML
Zhuoran Yang, Krishnakumar Balasubramanian, Han Liu
2017 J jnl
Homotopy Parametric Simplex Method for Sparse Learning.
CoRR
Haotian Pang, Tuo Zhao, Robert J. Vanderbei, Han Liu
2017 J jnl
On Faster Convergence of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization.
J. Mach. Learn. Res.
Xingguo Li, Tuo Zhao, Raman Arora, Han Liu, Mingyi Hong
2017 — conf
Parametric Simplex Method for Sparse Learning.
NIPS
Haotian Pang, Han Liu, Robert J. Vanderbei, Tuo Zhao
2017 J jnl
Post-Regularization Inference for Time-Varying Nonparanormal Graphical Models.
J. Mach. Learn. Res.
Junwei Lu, Mladen Kolar, Han Liu
2017 J jnl
Stochastic compositional gradient descent: algorithms for minimizing compositions of expected-value functions.
Math. Program.
Mengdi Wang, Ethan X. Fang, Han Liu
2016 J jnl
A First Order Free Lunch for SQRT-Lasso.
CoRR
Xingguo Li, Jarvis D. Haupt, Raman Arora, Han Liu, Mingyi Hong, Tuo Zhao
2016 A conf
A Lasso-based Sparse Knowledge Gradient Policy for Sequential Optimal Learning.
AISTATS
Yan Li, Han Liu, Warren B. Powell
2016 A* conf
A Truth Discovery Approach with Theoretical Guarantee.
KDD
Houping Xiao, Jing Gao, Zhaoran Wang, Shiyu Wang, Lu Su, Han Liu
2016 — conf
Agnostic Estimation for Misspecified Phase Retrieval Models.
NIPS
Matey Neykov, Zhaoran Wang, Han Liu
2016 A conf
An Improved Convergence Analysis of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization.
AISTATS
Xingguo Li, Tuo Zhao, Raman Arora, Han Liu, Mingyi Hong
2016 J jnl
An Improved Convergence Analysis of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization.
CoRR
Xingguo Li, Tuo Zhao, Raman Arora, Han Liu, Mingyi Hong
2016 — conf
Blind Attacks on Machine Learners.
NIPS
Alex Beatson, Zhaoran Wang, Han Liu
2016 A conf
Low-Rank and Sparse Structure Pursuit via Alternating Minimization.
AISTATS
Quanquan Gu, Zhaoran Wang, Han Liu
2016 — conf
More Supervision, Less Computation: Statistical-Computational Tradeoffs in Weakly Supervised Learning.
NIPS
Xinyang Yi, Zhaoran Wang, Zhuoran Yang, Constantine Caramanis, Han Liu
2016 A* conf
On the Statistical Limits of Convex Relaxations.
ICML
Zhaoran Wang, Quanquan Gu, Han Liu
2016 — conf
Online ICA: Understanding Global Dynamics of Nonconvex Optimization via Diffusion Processes.
NIPS
Chris Junchi Li, Zhaoran Wang, Han Liu
2016 J jnl
Revisiting compressed sensing: exploiting the efficiency of simplex and sparsification methods.
Math. Program. Comput.
Robert J. Vanderbei, Kevin Lin, Han Liu, Lie Wang
2016 A* conf
Sparse Nonlinear Regression: Parameter Estimation under Nonconvexity.
ICML
Zhuoran Yang, Zhaoran Wang, Han Liu, Yonina C. Eldar, Tong Zhang
2016 A* conf
Stochastic Variance Reduced Optimization for Nonconvex Sparse Learning.
ICML
Xingguo Li, Tuo Zhao, Raman Arora, Han Liu, Jarvis D. Haupt
2016 J jnl
Stochastic Variance Reduced Optimization for Nonconvex Sparse Learning.
CoRR
Xingguo Li, Tuo Zhao, Raman Arora, Han Liu, Jarvis D. Haupt
2016 J jnl
Symmetry, Saddle Points, and Global Geometry of Nonconvex Matrix Factorization.
CoRR
Xingguo Li, Zhaoran Wang, Junwei Lu, Raman Arora, Jarvis D. Haupt, Han Liu, Tuo Zhao
2015 — conf
A Nonconvex Optimization Framework for Low Rank Matrix Estimation.
NIPS
Tuo Zhao, Zhaoran Wang, Han Liu
2015 J jnl
A direct estimation of high dimensional stationary vector autoregressions.
J. Mach. Learn. Res.
Fang Han, Huanran Lu, Han Liu
2015 J jnl
Calibrated multivariate regression with application to neural semantic basis discovery.
J. Mach. Learn. Res.
Han Liu, Lie Wang, Tuo Zhao
2015 J jnl
Generalized alternating direction method of multipliers: new theoretical insights and applications.
Math. Program. Comput.
Ethan X. Fang, Bingsheng He, Han Liu, Xiaoming Yuan
2015 — conf
High Dimensional EM Algorithm: Statistical Optimization and Asymptotic Normality.
NIPS
Zhaoran Wang, Quanquan Gu, Yang Ning, Han Liu
2015 — conf
Local Smoothness in Variance Reduced Optimization.
NIPS
Daniel Vainsencher, Han Liu, Tong Zhang
2015 — conf
Non-convex Statistical Optimization for Sparse Tensor Graphical Model.
NIPS
Wei Sun, Zhaoran Wang, Han Liu, Guang Cheng
2015 J jnl
Optimal Feature Selection in High-Dimensional Discriminant Analysis.
IEEE Trans. Inf. Theory
Mladen Kolar, Han Liu
2015 — conf
Optimal Linear Estimation under Unknown Nonlinear Transform.
NIPS
Xinyang Yi, Zhaoran Wang, Constantine Caramanis, Han Liu
2015 J jnl
Optimal linear estimation under unknown nonlinear transform.
CoRR
Xinyang Yi, Zhaoran Wang, Constantine Caramanis, Han Liu
2015 A* conf
Robust Estimation of Transition Matrices in High Dimensional Heavy-tailed Vector Autoregressive Processes.
ICML
Huitong Qiu, Sheng Xu, Fang Han, Han Liu, Brian Caffo
2015 — conf
Robust Portfolio Optimization.
NIPS
Huitong Qiu, Fang Han, Han Liu, Brian Caffo
2015 J jnl
Sparse Nonlinear Regression: Parameter Estimation and Asymptotic Inference.
CoRR
Zhuoran Yang, Zhaoran Wang, Han Liu, Yonina C. Eldar, Tong Zhang
2015 J jnl
The Knowledge Gradient Policy Using A Sparse Additive Belief Model.
CoRR
Yan Li, Han Liu, Warren B. Powell
2015 J jnl
The flare package for high dimensional linear regression and precision matrix estimation in R.
J. Mach. Learn. Res.
Xingguo Li, Tuo Zhao, Xiaoming Yuan, Han Liu
2015 J jnl
glmgraph: an R package for variable selection and predictive modeling of structured genomic data.
Bioinform.
Li Chen, Han Liu, Jean-Pierre A. Kocher, Hongzhe Li, Jun Chen
2014 J jnl
A Strictly Contractive Peaceman-Rachford Splitting Method for Convex Programming.
SIAM J. Optim.
Bingsheng He, Han Liu, Zhaoran Wang, Xiaoming Yuan
2014 — conf
Accelerated Mini-batch Randomized Block Coordinate Descent Method.
NIPS
Tuo Zhao, Mo Yu, Yiming Wang, Raman Arora, Han Liu
2014 J jnl
Calibrated Precision Matrix Estimation for High-Dimensional Elliptical Distributions.
IEEE Trans. Inf. Theory
Tuo Zhao, Han Liu
2014 J jnl
Compressive Network Analysis.
IEEE Trans. Autom. Control.
Xiaoye Jiang, Yuan Yao, Han Liu, Leonidas J. Guibas
2014 A conf
Context Aware Group Nearest Shrunken Centroids in Large-Scale Genomic Studies.
AISTATS
Juemin Yang, Fang Han, Rafael A. Irizarry, Han Liu
2014 J jnl
Graph estimation from multi-attribute data.
J. Mach. Learn. Res.
Mladen Kolar, Han Liu, Eric P. Xing
2014 J jnl
High Dimensional Semiparametric Scale-Invariant Principal Component Analysis.
IEEE Trans. Pattern Anal. Mach. Intell.
Fang Han, Han Liu
2014 — conf
Mode Estimation for High Dimensional Discrete Tree Graphical Models.
NIPS
Chao Chen, Han Liu, Dimitris N. Metaxas, Tianqi Zhao
2014 — conf
Multivariate Regression with Calibration.
NIPS
Han Liu, Lie Wang, Tuo Zhao
2014 J jnl
Nonconvex Statistical Optimization: Minimax-Optimal Sparse PCA in Polynomial Time.
CoRR
Zhaoran Wang, Huanran Lu, Han Liu
2014 J jnl
Pathwise Coordinate Optimization for Sparse Learning: Algorithm and Theory.
CoRR
Tuo Zhao, Han Liu, Tong Zhang
2014 — conf
Sparse PCA with Oracle Property.
NIPS
Quanquan Gu, Zhaoran Wang, Han Liu
2014 J jnl
The fastclime package for linear programming and large-scale precision matrix estimation in R.
J. Mach. Learn. Res.
Haotian Pang, Han Liu, Robert J. Vanderbei
2014 — conf
Tighten after Relax: Minimax-Optimal Sparse PCA in Polynomial Time.
NIPS
Zhaoran Wang, Huanran Lu, Han Liu
2013 J jnl
CODA: high dimensional copula discriminant analysis.
J. Mach. Learn. Res.
Fang Han, Tuo Zhao, Han Liu
2013 J jnl
Calibrated Multivariate Regression with Application to Neural Semantic Basis Discovery.
CoRR
Han Liu, Lie Wang, Tuo Zhao
2013 — conf
Feature Selection in High-Dimensional Classification.
ICML (1)
Mladen Kolar, Han Liu
2013 — conf
Markov Network Estimation From Multi-attribute Data.
ICML (3)
Mladen Kolar, Han Liu, Eric P. Xing
2013 J jnl
Optimization for Compressed Sensing: the Simplex Method and Kronecker Sparsification.
CoRR
Robert J. Vanderbei, Han Liu, Lie Wang, Kevin Lin
2013 — conf
Principal Component Analysis on non-Gaussian Dependent Data.
ICML (1)
Fang Han, Han Liu
2013 — conf
Robust Sparse Principal Component Regression under the High Dimensional Elliptical Model.
NIPS
Fang Han, Han Liu
2013 — conf
Sparse Inverse Covariance Estimation with Calibration.
NIPS
Tuo Zhao, Han Liu
2013 A conf
Sparse Principal Component Analysis for High Dimensional Multivariate Time Series.
AISTATS
Zhaoran Wang, Fang Han, Han Liu
2013 — conf
Transition Matrix Estimation in High Dimensional Time Series.
ICML (2)
Fang Han, Han Liu
2012 A conf
Detecting Network Cliques with Radon Basis Pursuit.
AISTATS
Xiaoye Jiang, Yuan Yao, Han Liu, Leonidas J. Guibas
2012 — conf
Exponential Concentration for Mutual Information Estimation with Application to Forests.
NIPS
Han Liu, John D. Lafferty, Larry A. Wasserman
2012 A* conf
High Dimensional Semiparametric Gaussian Copula Graphical Models.
ICML
Han Liu, Fang Han, Ming Yuan, John D. Lafferty, Larry A. Wasserman
2012 A conf
Marginal Regression For Multitask Learning.
AISTATS
Mladen Kolar, Han Liu
2012 — conf
Semiparametric Principal Component Analysis.
NIPS
Fang Han, Han Liu
2012 — conf
Smooth-projected Neighborhood Pursuit for High-dimensional Nonparanormal Graph Estimation.
NIPS
Tuo Zhao, Kathryn Roeder, Han Liu
2012 A conf
Sparse Additive Machine.
AISTATS
Tuo Zhao, Han Liu
2012 J jnl
Sparse Nonparametric Graphical Models
CoRR
John D. Lafferty, Han Liu, Larry A. Wasserman
2012 A conf
Structured Sparse Canonical Correlation Analysis.
AISTATS
Xi Chen, Han Liu, Jaime G. Carbonell
2012 J jnl
The Nonparanormal SKEPTIC.
CoRR
Han Liu, Fang Han, Ming Yuan, John D. Lafferty, Larry A. Wasserman
2012 J jnl
The huge Package for High-dimensional Undirected Graph Estimation in R.
J. Mach. Learn. Res.
Tuo Zhao, Han Liu, Kathryn Roeder, John D. Lafferty, Larry A. Wasserman
2012 — conf
Transelliptical Component Analysis.
NIPS
Fang Han, Han Liu
2012 — conf
Transelliptical Graphical Models.
NIPS
Han Liu, Fang Han, Cun-Hui Zhang
2011 J jnl
Compressive Network Analysis
CoRR
Xiaoye Jiang, Yuan Yao, Han Liu, Leonidas J. Guibas
2011 J jnl
Forest Density Estimation.
J. Mach. Learn. Res.
Han Liu, Min Xu, Haijie Gu, Anupam Gupta, John D. Lafferty, Larry A. Wasserman
2010 A* conf
Forest Density Estimation.
COLT
Anupam Gupta, John D. Lafferty, Han Liu, Larry A. Wasserman, Min Xu
2010 — conf
Graph-Valued Regression.
NIPS
Han Liu, Xi Chen, John D. Lafferty, Larry A. Wasserman
2010 A* conf
Learning Spatial-Temporal Varying Graphs with Applications to Climate Data Analysis.
AAAI
Xi Chen, Yan Liu, Han Liu, Jaime G. Carbonell
2010 J jnl
Mining Historic Query Trails to Label Long and Rare Search Engine Queries.
ACM Trans. Web
Peter Bailey, Ryen W. White, Han Liu, Giridhar Kumaran
2010 — conf
Multivariate Dyadic Regression Trees for Sparse Learning Problems.
NIPS
Han Liu, Xi Chen
2010 — —
Nonparametric Learning in High Dimensions.
Han Liu
2010 — conf
Stability Approach to Regularization Selection (StARS) for High Dimensional Graphical Models.
NIPS
Han Liu, Kathryn Roeder, Larry A. Wasserman
2010 A conf
The Group Dantzig Selector.
AISTATS
Han Liu, Jian Zhang, Xiaoye Jiang, Jun Liu
2009 — ch.
A Framework for Efficient Association Rule Mining in XML Data.
Database Technologies: Concepts, Methodologies, Tools, and Applications
Ji Zhang, Han Liu, Tok Wang Ling, Robert M. Bruckner, A Min Tjoa
2009 A* conf
Blockwise coordinate descent procedures for the multi-task lasso, with applications to neural semantic basis discovery.
ICML
Han Liu, Mark Palatucci, Jian Zhang
2009 A conf
Estimation Consistency of the Group Lasso and its Applications.
AISTATS
Han Liu, Jian Zhang
2009 — conf
Nonparametric Greedy Algorithms for the Sparse Learning Problem.
NIPS
Han Liu, Xi Chen
2009 J jnl
The Nonparanormal: Semiparametric Estimation of High Dimensional Undirected Graphs.
J. Mach. Learn. Res.
Han Liu, John D. Lafferty, Larry A. Wasserman
2008 — conf
Nonparametric regression and classification with joint sparsity constraints.
NIPS
Han Liu, John D. Lafferty, Larry A. Wasserman
2007 — conf
SpAM: Sparse Additive Models.
NIPS
Pradeep Ravikumar, Han Liu, John D. Lafferty, Larry A. Wasserman
2007 A conf
Sparse Nonparametric Density Estimation in High Dimensions Using the Rodeo.
AISTATS
Han Liu, John D. Lafferty, Larry A. Wasserman
2006 J jnl
A Framework for Efficient Association Rule Mining in XML Data.
J. Database Manag.
Ji Zhang, Han Liu, Tok Wang Ling, Robert M. Bruckner, A Min Tjoa
2006 A conf
Towards the Prediction of Protein Abundance from Tandem Mass Spectrometry Data.
SDM
Anthony J. Bonner, Han Liu
2005 — ch.
D-GridMST: Clustering Large Distributed Spatial Databases.
Classification and Clustering for Knowledge Discovery
Ji Zhang, Han Liu
2005 — conf
Visual Sign Language Recognition Based on HMMs and Auto-regressive HMMs.
Gesture Workshop
Xiaolin Yang, Feng Jiang, Han Liu, Hongxun Yao, Wen Gao, Chunli Wang
2005 — conf
X-warehouse: building query pattern-driven data.
WWW (Special interest tracks and posters)
Ji Zhang, Wei Wang, Han Liu, Sheng Zhang
2005 — conf
XAR-miner: efficient association rules mining for XML data.
WWW (Special interest tracks and posters)
Sheng Zhang, Ji Zhang, Han Liu, Wei Wang
2004 Misc conf
A Novel Dimensionality Reduction Technique Based on Independent Component Analysis for Modeling Microarray Gene Expression Data.
IC-AI
Han Liu, Rafal Kustra, Ji Zhang
2004 — conf
A robot path planning approach based on generalized semi-infinite optimization.
RAM
Han Liu, Qianying Tang, Yongji Wang
2004 Misc conf
An Effective and Efficient Data Cleaning Technique in Large Databases.
IKE
Ji Zhang, Han Liu
2004 — conf
An Efficient Method to Estimate Labelled Sample Size for Transductive LDA(QDA/MDA) Based on Bayes Risk.
ECML
Han Liu, Xiaobin Yuan, Qianying Tang, Rafal Kustra
2004 — conf
An Extended Linear Strategy Bridging the Gap between Regression and SVD Decomposition for Modeling Peptide Tandem Mass Spectrometry Data.
METMBS
Han Liu
2004 Misc conf
Generalized Semi-Infinite Optimization and its Application in Robotics' Path Planning Problem.
IC-AI
Han Liu, Xiaolin Yang, Ji Zhang, Yongji Wang
2004 C conf
On Efficient and Effective Association Rule Mining from XML Data.
DEXA
Ji Zhang, Tok Wang Ling, Robert M. Bruckner, A Min Tjoa, Han Liu
2004 C conf
PC-Filter: A Robust Filtering Technique for Duplicate Record Detection in Large Databases.
DEXA
Ji Zhang, Tok Wang Ling, Robert M. Bruckner, Han Liu
2004 Misc conf
Statistical Issues with Labeled Sample Size Analysis for Semi-Supervised Linear Discriminant Analysis.
IC-AI
Han Liu, Di Wu, Ji Zhang, Xiaolin Yang, Xiaobin Yuan, Rafal Kustra