← Authors

Han Liu

160 papers · 2007–2026 · 17 conferences · across top CS/AI conferences

Achievements

πŸ—ΊοΈ Taxonomy Completionist (41) 🐝 Cross-Pollinator (9) πŸƒ Academic Marathon (18) 🌍 Conference Polyglot (16) 🌈 Renaissance Researcher (7) 🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🌟 Keyword Trendsetter Combo (3) 🏠 Conference Loyalist (41) πŸ† Keyword Champion (5) πŸ”¬ Deep Specialist (14) 🀝 Dynamic Duo (22) πŸ† Grand Slam πŸ‘‘ Triple Crown πŸ“ˆ Trend Setter πŸš€ Conference Pioneer πŸ—ƒοΈ Keyword Collector (211) ⚑ Prolific Year (11) πŸ’Ž Century Club (155) πŸ”₯ Unstoppable (19)

Conferences

NIPS (41) ICML (24) AAAI (16) JMLR (15) ICLR (13) AISTATS (12) ACL (8) EMNLP (7) IJCAI (7) CVPR (5) NAACL (3) EACL (2) IJCNLP (2) MICCAI (2) CORL (1) MIDL (1) UAI (1)

Top co-authors

Xiaotong Zhang (22) Zhaoran Wang (17) Jerry Yao-Chieh Hu (17) Tuo Zhao (16) Xianchao Zhang (12) Fang Han (12) Fenglong Ma (12) Feng Zhang (11) Hong Yu (10) Tong Zhang (9)

Research topics

Statistics (6) Probability (2)

Keywords

graphical model (15) high-dimensional statistics (9) sparse learning (8) convex optimization (8) sparse estimation (7) large language model (7) principal component analysis (7) adversarial attack (6) semiparametric model (6) nonconvex optimization (6) few-shot learning (6) feature selection (6) high-dimensional datum (6) text classification (5) high-dimensional regression (5) graph estimation (5) variable selection (5) attention mechanism (5) high dimensional statistics (5) dialogue system (5)

Papers

PromptFE: Automated Feature Engineering by Prompting EACL 2026
DS2-Instruct: Domain-Specific Data Synthesis for Large Language Models Instruction Tuning EACL 2026
KnowLCP: Knowledge Augmented Lane Change Prediction for Autonomous Driving AAAI 2026
MRT: Learning Compact Representations with Mixed RWKV-Transformer for Extreme Image Compression AAAI 2026
BiO-HMC: Dynamic Human-Machine Collaboration for Consensus Decision-Making via Bilevel Optimization AAAI 2026
A Non-contrast Head CT Foundation Model for Comprehensive Neuro-Trauma Triage MICCAI 2025
EcoLoRA: Communication-Efficient Federated Fine-Tuning of Large Language Models EMNLP 2025
Shadow-Activated Backdoor Attacks on Multimodal Large Language Models ACL 2025
AdaDHP: Fine-Grained Fine-Tuning via Dual Hadamard Product and Adaptive Parameter Selection ACL 2025
ECG2TOK: ECG Pre-Training with Self-Distillation Semantic Tokenizers IJCAI 2025
Improving Accuracy and Calibration via Differentiated Deep Mutual Learning CVPR 2025
In-Context Deep Learning via Transformer Models ICML 2025
In-Context Learning as Conditioned Associative Memory Retrieval ICML 2025
Fast and Low-Cost Genomic Foundation Models via Outlier Removal ICML 2025
Nonparametric Modern Hopfield Models ICML 2025
Statistical Guarantees for Lifelong Reinforcement Learning using PAC-Bayes Theory AISTATS 2025
EGSRAL:An Enhanced 3D Gaussian Splatting Based Renderer with Automated Labeling for Large-Scale Driving Scene AAAI 2025
Multi-Label Few-Shot Image Classification via Pairwise Feature Augmentation and Flexible Prompt Learning AAAI 2025
Uncertainty-Aware Contrastive Learning with Hard Negative Sampling for Code Search Tasks AAAI 2025
Dual-View Interaction-Aware Lane Change Prediction for Autonomous Driving AAAI 2025
Fundamental Limits of Prompt Tuning Transformers: Universality, Capacity and Efficiency ICLR 2025
Computational Limits of Low-Rank Adaptation (LoRA) Fine-Tuning for Transformer Models ICLR 2025
Chain-of-Action: Faithful and Multimodal Question Answering through Large Language Models ICLR 2025
On Statistical Rates of Conditional Diffusion Transformers: Approximation, Estimation and Minimax Optimality ICLR 2025
SEP-MLDC: A Simple and Effective Paradigm for Multi-Label Document Classification NAACL 2025
Pairwise Prompt-Based Tuning with Parameter Efficient Fast Adaptation for Generalized Zero-Shot Intent Detection NAACL 2025
BIPEFT: Budget-Guided Iterative Search for Parameter Efficient Fine-Tuning of Large Pretrained Language Models EMNLP 2024
Liberating Seen Classes: Boosting Few-Shot and Zero-Shot Text Classification via Anchor Generation and Classification Reframing AAAI 2024
EIVEN: Efficient Implicit Attribute Value Extraction using Multimodal LLM NAACL 2024
Depression Detection via Capsule Networks with Contrastive Learning AAAI 2024
STanHop: Sparse Tandem Hopfield Model for Memory-Enhanced Time Series Prediction ICLR 2024
Beyond Reverse KL: Generalizing Direct Preference Optimization with Diverse Divergence Constraints ICLR 2024
DNABERT-2: Efficient Foundation Model and Benchmark For Multi-Species Genomes ICLR 2024
A Goal Interaction Graph Planning Framework for Conversational Recommendation AAAI 2024
SELP: A Semantically-Driven Approach for Separated and Accurate Class Prototypes in Few-Shot Text Classification ACL 2024
PRISM: A Promptable and Robust Interactive Segmentation Model with Visual Prompts MICCAI 2024
VQAttack: Transferable Adversarial Attacks on Visual Question Answering via Pre-trained Models AAAI 2024
Global Convergence in Training Large-Scale Transformers NIPS 2024
On Statistical Rates and Provably Efficient Criteria of Latent Diffusion Transformers (DiTs) NIPS 2024
Provably Optimal Memory Capacity for Modern Hopfield Models: Transformer-Compatible Dense Associative Memories as Spherical Codes NIPS 2024
One-Layer Transformer Provably Learns One-Nearest Neighbor In Context NIPS 2024
Let’s Ask GNN: Empowering Large Language Model for Graph In-Context Learning EMNLP 2024
A Coarse-to-Fine Prototype Learning Approach for Multi-Label Few-Shot Intent Detection EMNLP 2024
BiSHop: Bi-Directional Cellular Learning for Tabular Data with Generalized Sparse Modern Hopfield Model ICML 2024
Uniform Memory Retrieval with Larger Capacity for Modern Hopfield Models ICML 2024
On Computational Limits of Modern Hopfield Models: A Fine-Grained Complexity Analysis ICML 2024
Outlier-Efficient Hopfield Layers for Large Transformer-Based Models ICML 2024
Multivariate Time Series Forecasting By Graph Attention Networks With Theoretical Guarantees AISTATS 2024
Sequential LLM Framework for Fashion Recommendation EMNLP 2024
SlowLiDAR: Increasing the Latency of LiDAR-Based Detection Using Adversarial Examples CVPR 2023
RIATIG: Reliable and Imperceptible Adversarial Text-to-Image Generation With Natural Prompts CVPR 2023
Boosting Decision-Based Black-Box Adversarial Attack with Gradient Priors IJCAI 2023
Feature Programming for Multivariate Time Series Prediction ICML 2023
On Sparse Modern Hopfield Model NIPS 2023
HQA-Attack: Toward High Quality Black-Box Hard-Label Adversarial Attack on Text NIPS 2023
VLATTACK: Multimodal Adversarial Attacks on Vision-Language Tasks via Pre-trained Models NIPS 2023
Ising-Traffic: Using Ising Machine Learning to Predict Traffic Congestion under Uncertainty AAAI 2023
Boosting Few-Shot Text Classification via Distribution Estimation AAAI 2023
SSPAttack: A Simple and Sweet Paradigm for Black-Box Hard-Label Textual Adversarial Attack AAAI 2023
Real-Time Image Demoir$\acute{e}$ing on Mobile Devices ICLR 2023
Aligning Offline Metrics and Human Judgments of Value for Code Generation Models ACL 2023
Learning Human-Compatible Representations for Case-Based Decision Support ICLR 2023
Bregman Proximal Langevin Monte Carlo via Bregman-Moreau Envelopes ICML 2022
Cross-Dataset Collaborative Learning for Semantic Segmentation in Autonomous Driving AAAI 2022
Reinforcement Learning under a Multi-agent Predictive State Representation Model: Method and Theory ICLR 2022
Domain Generalization for Retinal Vessel Segmentation with Vector Field Transformer MIDL 2022
Trade the Event: Corporate Events Detection for News-Based Event-Driven Trading ACL 2021
Posterior Promoted GAN With Distribution Discriminator for Unsupervised Image Synthesis CVPR 2021
Converse, Focus and Guess - Towards Multi-Document Driven Dialogue AAAI 2021
RoboFlow: a Data-centric Workflow Management System for Developing AI-enhanced Robots CORL 2021
An Explicit-Joint and Supervised-Contrastive Learning Framework for Few-Shot Intent Classification and Slot Filling EMNLP 2021
Trade the Event: Corporate Events Detection for News-Based Event-Driven Trading IJCNLP 2021
GLAD: Learning Sparse Graph Recovery ICLR 2020
Unknown Intent Detection Using Gaussian Mixture Model with an Application to Zero-shot Intent Classification ACL 2020
Few-shot Slot Tagging with Collapsed Dependency Transfer and Label-enhanced Task-adaptive Projection Network ACL 2020
Agnostic Estimation for Phase Retrieval JMLR 2020
Learning to Plan in High Dimensions via Neural Exploration-Exploitation Trees ICLR 2020
Reconstructing Capsule Networks for Zero-shot Intent Classification EMNLP 2019
Fast Low-rank Metric Learning for Large-scale and High-dimensional Data NIPS 2019
Label Efficient Semi-Supervised Learning via Graph Filtering CVPR 2019
Marginal Policy Gradients: A Unified Family of Estimators for Bounded Action Spaces with Applications ICLR 2019
Grid-Wise Control for Multi-Agent Reinforcement Learning in Video Game AI ICML 2019
Attributed Graph Clustering via Adaptive Graph Convolution IJCAI 2019
Reconstructing Capsule Networks for Zero-shot Intent Classification IJCNLP 2019
Picasso: A Sparse Learning Library for High Dimensional Data Analysis in R and Python JMLR 2019
Layer-Wise Learning Strategy for Nonparametric Tensor Product Smoothing Spline Regression and Graphical Models JMLR 2019
On Fast Convergence of Proximal Algorithms for SQRT-Lasso Optimization: Don’t Worry About its Nonsmooth Loss Function UAI 2019
Graphical Nonconvex Optimization via an Adaptive Convex Relaxation ICML 2018
Minimax-Optimal Privacy-Preserving Sparse PCA in Distributed Systems AISTATS 2018
Discrete Factorization Machines for Fast Feature-based Recommendation IJCAI 2018
On Semiparametric Exponential Family Graphical Models JMLR 2018
Post-Regularization Inference for Time-Varying Nonparanormal Graphical Models JMLR 2018
On Faster Convergence of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization JMLR 2018
Fully Decentralized Multi-Agent Reinforcement Learning with Networked Agents ICML 2018
Sketching Method for Large Scale Combinatorial Inference NIPS 2018
Feedback-Based Tree Search for Reinforcement Learning ICML 2018
The Edge Density Barrier: Computational-Statistical Tradeoffs in Combinatorial Inference ICML 2018
Exponentially Weighted Imitation Learning for Batched Historical Data NIPS 2018
Multi-Task Clustering with Model Relation Learning IJCAI 2018
CANE: Context-Aware Network Embedding for Relation Modeling ACL 2017
Diffusion Approximations for Online Principal Component Estimation and Global Convergence NIPS 2017
High-dimensional Non-Gaussian Single Index Models via Thresholded Score Function Estimation ICML 2017
Parametric Simplex Method for Sparse Learning NIPS 2017
Estimating High-dimensional Non-Gaussian Multiple Index Models via Stein’s Lemma NIPS 2017
Self-Adapted Multi-Task Clustering IJCAI 2016
Low-Rank and Sparse Structure Pursuit via Alternating Minimization AISTATS 2016
Agnostic Estimation for Misspecified Phase Retrieval Models NIPS 2016
Blind Attacks on Machine Learners NIPS 2016
Stochastic Variance Reduced Optimization for Nonconvex Sparse Learning ICML 2016
On the Statistical Limits of Convex Relaxations ICML 2016
Sparse Nonlinear Regression: Parameter Estimation under Nonconvexity ICML 2016
Online ICA: Understanding Global Dynamics of Nonconvex Optimization via Diffusion Processes NIPS 2016
More Supervision, Less Computation: Statistical-Computational Tradeoffs in Weakly Supervised Learning NIPS 2016
A Lasso-based Sparse Knowledge Gradient Policy for Sequential Optimal Learning AISTATS 2016
An Improved Convergence Analysis of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization AISTATS 2016
The flare Package for High Dimensional Linear Regression and Precision Matrix Estimation in R JMLR 2015
Non-convex Statistical Optimization for Sparse Tensor Graphical Model NIPS 2015
Optimal Linear Estimation under Unknown Nonlinear Transform NIPS 2015
A Nonconvex Optimization Framework for Low Rank Matrix Estimation NIPS 2015
Local Smoothness in Variance Reduced Optimization NIPS 2015
High Dimensional EM Algorithm: Statistical Optimization and Asymptotic Normality NIPS 2015
Robust Portfolio Optimization NIPS 2015
Robust Estimation of Transition Matrices in High Dimensional Heavy-tailed Vector Autoregressive Processes ICML 2015
A Direct Estimation of High Dimensional Stationary Vector Autoregressions JMLR 2015
Calibrated Multivariate Regression with Application to Neural Semantic Basis Discovery JMLR 2015
Multi-Task Multi-View Clustering for Non-Negative Data IJCAI 2015
Multivariate Regression with Calibration NIPS 2014
Mode Estimation for High Dimensional Discrete Tree Graphical Models NIPS 2014
Sparse PCA with Oracle Property NIPS 2014
Accelerated Mini-batch Randomized Block Coordinate Descent Method NIPS 2014
Tighten after Relax: Minimax-Optimal Sparse PCA in Polynomial Time NIPS 2014
The FASTCLIME Package for Linear Programming and Large-Scale Precision Matrix Estimation in R JMLR 2014
Graph Estimation From Multi-Attribute Data JMLR 2014
Context Aware Group Nearest Shrunken Centroids in Large-Scale Genomic Studies AISTATS 2014
Feature Selection in High-Dimensional Classification ICML 2013
Principal Component Analysis on non-Gaussian Dependent Data ICML 2013
CODA: High Dimensional Copula Discriminant Analysis JMLR 2013
Sparse Principal Component Analysis for High Dimensional Multivariate Time Series AISTATS 2013
Sparse Inverse Covariance Estimation with Calibration NIPS 2013
Robust Sparse Principal Component Regression under the High Dimensional Elliptical Model NIPS 2013
Markov Network Estimation From Multi-attribute Data ICML 2013
Transition Matrix Estimation in High Dimensional Time Series ICML 2013
Smooth-projected Neighborhood Pursuit for High-dimensional Nonparanormal Graph Estimation NIPS 2012
Exponential Concentration for Mutual Information Estimation with Application to Forests NIPS 2012
The huge Package for High-dimensional Undirected Graph Estimation in R JMLR 2012
Sparse Additive Machine AISTATS 2012
Semiparametric Principal Component Analysis NIPS 2012
Marginal Regression For Multitask Learning AISTATS 2012
Detecting Network Cliques with Radon Basis Pursuit AISTATS 2012
Transelliptical Graphical Models NIPS 2012
Transelliptical Component Analysis NIPS 2012
Forest Density Estimation JMLR 2011
Graph-Valued Regression NIPS 2010
Multivariate Dyadic Regression Trees for Sparse Learning Problems NIPS 2010
The Group Dantzig Selector AISTATS 2010
Stability Approach to Regularization Selection (StARS) for High Dimensional Graphical Models NIPS 2010
Nonparametric Greedy Algorithms for the Sparse Learning Problem NIPS 2009
The Nonparanormal: Semiparametric Estimation of High Dimensional Undirected Graphs JMLR 2009
Nonparametric regression and classification with joint sparsity constraints NIPS 2008
SpAM: Sparse Additive Models NIPS 2007