Han Liu

Orcid: 0000-0002-2470-1755

Affiliations:
  • Northwestern University, Evanston, IL, USA
  • Princeton University, Department of Operations Research and Financial Engineering, NJ, USA
  • Johns Hopkins University, Department of Biostatistics and Computer Science, Baltimore, MD, USA
  • Carnegie Mellon University, Pittsburgh, PA, USA (PhD 2011)
  • University of Toronto, Department of Computer Science, ON, Canada (former)


According to our database1, Han Liu authored at least 187 papers between 2004 and 2024.

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Bibliography

2024
Scalable Multi-agent Reinforcement Learning for Factory-wide Dynamic Scheduling.
CoRR, 2024

Differentially Private Kernel Density Estimation.
CoRR, 2024

On Statistical Rates and Provably Efficient Criteria of Latent Diffusion Transformers (DiTs).
CoRR, 2024

Communication-Efficient Adaptive Batch Size Strategies for Distributed Local Gradient Methods.
CoRR, 2024

Computational Limits of Low-Rank Adaptation (LoRA) for Transformer-Based Models.
CoRR, 2024

Decoupled Alignment for Robust Plug-and-Play Adaptation.
CoRR, 2024

Enhancing Jailbreak Attack Against Large Language Models through Silent Tokens.
CoRR, 2024

Conv-CoA: Improving Open-domain Question Answering in Large Language Models via Conversational Chain-of-Action.
CoRR, 2024

HeteGraph-Mamba: Heterogeneous Graph Learning via Selective State Space Model.
CoRR, 2024

Nonparametric Modern Hopfield Models.
CoRR, 2024

Outlier-Efficient Hopfield Layers for Large Transformer-Based Models.
CoRR, 2024

Chain-of-Action: Faithful and Multimodal Question Answering through Large Language Models.
CoRR, 2024

USE: Dynamic User Modeling with Stateful Sequence Models.
CoRR, 2024

AdAdaGrad: Adaptive Batch Size Schemes for Adaptive Gradient Methods.
CoRR, 2024

DNABERT-S: Learning Species-Aware DNA Embedding with Genome Foundation Models.
CoRR, 2024

ML-Based Real-Time Control at the Edge: An Approach Using hls4ml.
Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2024

DOS<sup>®</sup>: A Deployment Operating System for Robots.
Proceedings of the IEEE International Conference on Robotics and Automation, 2024

BiSHop: Bi-Directional Cellular Learning for Tabular Data with Generalized Sparse Modern Hopfield Model.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Uniform Memory Retrieval with Larger Capacity for Modern Hopfield Models.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

On Computational Limits of Modern Hopfield Models: A Fine-Grained Complexity Analysis.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Outlier-Efficient Hopfield Layers for Large Transformer-Based Models.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

STanHop: Sparse Tandem Hopfield Model for Memory-Enhanced Time Series Prediction.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

DNABERT-2: Efficient Foundation Model and Benchmark For Multi-Species Genomes.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
Beyond PID Controllers: PPO with Neuralized PID Policy for Proton Beam Intensity Control in Mu2e.
CoRR, 2023

Efficient Action Robust Reinforcement Learning with Probabilistic Policy Execution Uncertainty.
CoRR, 2023

Learning Multiple Coordinated Agents under Directed Acyclic Graph Constraints.
CoRR, 2023

DNABERT-2: Efficient Foundation Model and Benchmark For Multi-Species Genome.
CoRR, 2023

Feature Programming for Multivariate Time Series Prediction.
CoRR, 2023

Non-Log-Concave and Nonsmooth Sampling via Langevin Monte Carlo Algorithms.
CoRR, 2023

On Sparse Modern Hopfield Model.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

EMS®: A Massive Computational Experiment Management System towards Data-driven Robotics.
Proceedings of the IEEE International Conference on Robotics and Automation, 2023

Feature Programming for Multivariate Time Series Prediction.
Proceedings of the International Conference on Machine Learning, 2023

Ising-Traffic: Using Ising Machine Learning to Predict Traffic Congestion under Uncertainty.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Predicting Drug Repurposing Candidates and Their Mechanisms from A Biomedical Knowledge Graph.
CoRR, 2022

Large-Scale Multi-Document Summarization with Information Extraction and Compression.
CoRR, 2022

Wasserstein Distributionally Robust Optimization via Wasserstein Barycenters.
CoRR, 2022

Learning to Infer Belief Embedded Communication.
CoRR, 2022

Switch Trajectory Transformer with Distributional Value Approximation for Multi-Task Reinforcement Learning.
CoRR, 2022

Bregman Proximal Langevin Monte Carlo via Bregman-Moreau Envelopes.
Proceedings of the International Conference on Machine Learning, 2022

Reinforcement Learning under a Multi-agent Predictive State Representation Model: Method and Theory.
Proceedings of the Tenth International Conference on Learning Representations, 2022

2021
Robust Scatter Matrix Estimation for High Dimensional Distributions With Heavy Tail.
IEEE Trans. Inf. Theory, 2021

Finite-Sample Analysis for Decentralized Batch Multiagent Reinforcement Learning With Networked Agents.
IEEE Trans. Autom. Control., 2021

DNABERT: pre-trained Bidirectional Encoder Representations from Transformers model for DNA-language in genome.
Bioinform., 2021

RoboFlow: a Data-centric Workflow Management System for Developing AI-enhanced Robots.
Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

Trade the Event: Corporate Events Detection for News-Based Event-Driven Trading.
Proceedings of the Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021, 2021

2020
Tensor Graphical Model: Non-Convex Optimization and Statistical Inference.
IEEE Trans. Pattern Anal. Mach. Intell., 2020

Agnostic Estimation for Phase Retrieval.
J. Mach. Learn. Res., 2020

Collision-free Navigation of Human-centered Robots via Markov Games.
Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

GLAD: Learning Sparse Graph Recovery.
Proceedings of the 8th International Conference on Learning Representations, 2020

Learning to Plan in High Dimensions via Neural Exploration-Exploitation Trees.
Proceedings of the 8th International Conference on Learning Representations, 2020

Few-shot Slot Tagging with Collapsed Dependency Transfer and Label-enhanced Task-adaptive Projection Network.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019
Symmetry, Saddle Points, and Global Optimization Landscape of Nonconvex Matrix Factorization.
IEEE Trans. Inf. Theory, 2019

Modelling and simulation of highly mixed traffic flow on two-lane two-way urban streets.
Simul. Model. Pract. Theory, 2019

Blessing of massive scale: spatial graphical model estimation with a total cardinality constraint approach.
Math. Program., 2019

Efficient, certifiably optimal clustering with applications to latent variable graphical models.
Math. Program., 2019

Layer-Wise Learning Strategy for Nonparametric Tensor Product Smoothing Spline Regression and Graphical Models.
J. Mach. Learn. Res., 2019

Picasso: A Sparse Learning Library for High Dimensional Data Analysis in R and Python.
J. Mach. Learn. Res., 2019

AdvCodec: Towards A Unified Framework for Adversarial Text Generation.
CoRR, 2019

Few-Shot Sequence Labeling with Label Dependency Transfer.
CoRR, 2019

On Fast Convergence of Proximal Algorithms for SQRT-Lasso Optimization: Don't Worry About its Nonsmooth Loss Function.
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Grid-Wise Control for Multi-Agent Reinforcement Learning in Video Game AI.
Proceedings of the 36th International Conference on Machine Learning, 2019

Marginal Policy Gradients: A Unified Family of Estimators for Bounded Action Spaces with Applications.
Proceedings of the 7th International Conference on Learning Representations, 2019

2018
Near-optimal stochastic approximation for online principal component estimation.
Math. Program., 2018

Max-norm optimization for robust matrix recovery.
Math. Program., 2018

On Semiparametric Exponential Family Graphical Models.
J. Mach. Learn. Res., 2018

Finite-Sample Analyses for Fully Decentralized Multi-Agent Reinforcement Learning.
CoRR, 2018

Parametrized Deep Q-Networks Learning: Reinforcement Learning with Discrete-Continuous Hybrid Action Space.
CoRR, 2018

Fully Implicit Online Learning.
CoRR, 2018

TStarBots: Defeating the Cheating Level Builtin AI in StarCraft II in the Full Game.
CoRR, 2018

A convex formulation for high-dimensional sparse sliced inverse regression.
CoRR, 2018

Diffusion Approximations for Online Principal Component Estimation and Global Convergence.
CoRR, 2018

Curse of Heterogeneity: Computational Barriers in Sparse Mixture Models and Phase Retrieval.
CoRR, 2018

Marginal Policy Gradients for Complex Control.
CoRR, 2018

RWEN: response-weighted elastic net for prediction of chemosensitivity of cancer cell lines.
Bioinform., 2018

Exponentially Weighted Imitation Learning for Batched Historical Data.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Sketching Method for Large Scale Combinatorial Inference.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Fully Decentralized Multi-Agent Reinforcement Learning with Networked Agents.
Proceedings of the 35th International Conference on Machine Learning, 2018

Graphical Nonconvex Optimization via an Adaptive Convex Relaxation.
Proceedings of the 35th International Conference on Machine Learning, 2018

The Edge Density Barrier: Computational-Statistical Tradeoffs in Combinatorial Inference.
Proceedings of the 35th International Conference on Machine Learning, 2018

Feedback-Based Tree Search for Reinforcement Learning.
Proceedings of the 35th International Conference on Machine Learning, 2018

Minimax-Optimal Privacy-Preserving Sparse PCA in Distributed Systems.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
Stochastic compositional gradient descent: algorithms for minimizing compositions of expected-value functions.
Math. Program., 2017

Post-Regularization Inference for Time-Varying Nonparanormal Graphical Models.
J. Mach. Learn. Res., 2017

On Faster Convergence of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization.
J. Mach. Learn. Res., 2017

Continual Learning in Generative Adversarial Nets.
CoRR, 2017

Homotopy Parametric Simplex Method for Sparse Learning.
CoRR, 2017

Estimating High-dimensional Non-Gaussian Multiple Index Models via Stein's Lemma.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Parametric Simplex Method for Sparse Learning.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

High-dimensional Non-Gaussian Single Index Models via Thresholded Score Function Estimation.
Proceedings of the 34th International Conference on Machine Learning, 2017

2016
Revisiting compressed sensing: exploiting the efficiency of simplex and sparsification methods.
Math. Program. Comput., 2016

Symmetry, Saddle Points, and Global Geometry of Nonconvex Matrix Factorization.
CoRR, 2016

A First Order Free Lunch for SQRT-Lasso.
CoRR, 2016

More Supervision, Less Computation: Statistical-Computational Tradeoffs in Weakly Supervised Learning.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Agnostic Estimation for Misspecified Phase Retrieval Models.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Online ICA: Understanding Global Dynamics of Nonconvex Optimization via Diffusion Processes.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Blind Attacks on Machine Learners.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

A Truth Discovery Approach with Theoretical Guarantee.
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

Sparse Nonlinear Regression: Parameter Estimation under Nonconvexity.
Proceedings of the 33nd International Conference on Machine Learning, 2016

On the Statistical Limits of Convex Relaxations.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Stochastic Variance Reduced Optimization for Nonconvex Sparse Learning.
Proceedings of the 33nd International Conference on Machine Learning, 2016

An Improved Convergence Analysis of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

A Lasso-based Sparse Knowledge Gradient Policy for Sequential Optimal Learning.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Low-Rank and Sparse Structure Pursuit via Alternating Minimization.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015
Optimal Feature Selection in High-Dimensional Discriminant Analysis.
IEEE Trans. Inf. Theory, 2015

Generalized alternating direction method of multipliers: new theoretical insights and applications.
Math. Program. Comput., 2015

Calibrated multivariate regression with application to neural semantic basis discovery.
J. Mach. Learn. Res., 2015

The flare package for high dimensional linear regression and precision matrix estimation in R.
J. Mach. Learn. Res., 2015

A direct estimation of high dimensional stationary vector autoregressions.
J. Mach. Learn. Res., 2015

Sparse Nonlinear Regression: Parameter Estimation and Asymptotic Inference.
CoRR, 2015

The Knowledge Gradient Policy Using A Sparse Additive Belief Model.
CoRR, 2015

glmgraph: an R package for variable selection and predictive modeling of structured genomic data.
Bioinform., 2015

A Nonconvex Optimization Framework for Low Rank Matrix Estimation.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Optimal Linear Estimation under Unknown Nonlinear Transform.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

High Dimensional EM Algorithm: Statistical Optimization and Asymptotic Normality.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Local Smoothness in Variance Reduced Optimization.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Non-convex Statistical Optimization for Sparse Tensor Graphical Model.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Robust Portfolio Optimization.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Robust Estimation of Transition Matrices in High Dimensional Heavy-tailed Vector Autoregressive Processes.
Proceedings of the 32nd International Conference on Machine Learning, 2015

2014
Calibrated Precision Matrix Estimation for High-Dimensional Elliptical Distributions.
IEEE Trans. Inf. Theory, 2014

Compressive Network Analysis.
IEEE Trans. Autom. Control., 2014

A Strictly Contractive Peaceman-Rachford Splitting Method for Convex Programming.
SIAM J. Optim., 2014

High Dimensional Semiparametric Scale-Invariant Principal Component Analysis.
IEEE Trans. Pattern Anal. Mach. Intell., 2014

The fastclime package for linear programming and large-scale precision matrix estimation in R.
J. Mach. Learn. Res., 2014

Graph estimation from multi-attribute data.
J. Mach. Learn. Res., 2014

Pathwise Coordinate Optimization for Sparse Learning: Algorithm and Theory.
CoRR, 2014

Nonconvex Statistical Optimization: Minimax-Optimal Sparse PCA in Polynomial Time.
CoRR, 2014

Accelerated Mini-batch Randomized Block Coordinate Descent Method.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Tighten after Relax: Minimax-Optimal Sparse PCA in Polynomial Time.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Multivariate Regression with Calibration.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Sparse PCA with Oracle Property.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Mode Estimation for High Dimensional Discrete Tree Graphical Models.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Context Aware Group Nearest Shrunken Centroids in Large-Scale Genomic Studies.
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

2013
CODA: high dimensional copula discriminant analysis.
J. Mach. Learn. Res., 2013

Optimization for Compressed Sensing: the Simplex Method and Kronecker Sparsification.
CoRR, 2013

Sparse Inverse Covariance Estimation with Calibration.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Robust Sparse Principal Component Regression under the High Dimensional Elliptical Model.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Markov Network Estimation From Multi-attribute Data.
Proceedings of the 30th International Conference on Machine Learning, 2013

Feature Selection in High-Dimensional Classification.
Proceedings of the 30th International Conference on Machine Learning, 2013

Principal Component Analysis on non-Gaussian Dependent Data.
Proceedings of the 30th International Conference on Machine Learning, 2013

Transition Matrix Estimation in High Dimensional Time Series.
Proceedings of the 30th International Conference on Machine Learning, 2013

Sparse Principal Component Analysis for High Dimensional Multivariate Time Series.
Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, 2013

2012
The huge Package for High-dimensional Undirected Graph Estimation in R.
J. Mach. Learn. Res., 2012

Sparse Additive Machine.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Marginal Regression For Multitask Learning.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Detecting Network Cliques with Radon Basis Pursuit.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Structured Sparse Canonical Correlation Analysis.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

<i>Teaching Case</i>: Implementation of an Interorganizational System: The Case of Medical Insurance E-Clearance.
J. Inf. Syst. Educ., 2012

Sparse Nonparametric Graphical Models
CoRR, 2012

The Nonparanormal SKEPTIC.
CoRR, 2012

Smooth-projected Neighborhood Pursuit for High-dimensional Nonparanormal Graph Estimation.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Exponential Concentration for Mutual Information Estimation with Application to Forests.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Transelliptical Graphical Models.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Transelliptical Component Analysis.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Semiparametric Principal Component Analysis.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

High Dimensional Semiparametric Gaussian Copula Graphical Models.
Proceedings of the 29th International Conference on Machine Learning, 2012

2011
Forest Density Estimation.
J. Mach. Learn. Res., 2011

2010
Nonparametric Learning in High Dimensions.
PhD thesis, 2010

Mining Historic Query Trails to Label Long and Rare Search Engine Queries.
ACM Trans. Web, 2010

The Group Dantzig Selector.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Stability Approach to Regularization Selection (StARS) for High Dimensional Graphical Models.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Graph-Valued Regression.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Multivariate Dyadic Regression Trees for Sparse Learning Problems.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Forest Density Estimation.
Proceedings of the COLT 2010, 2010

Learning Spatial-Temporal Varying Graphs with Applications to Climate Data Analysis.
Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, 2010

2009
Estimation Consistency of the Group Lasso and its Applications.
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

The Nonparanormal: Semiparametric Estimation of High Dimensional Undirected Graphs.
J. Mach. Learn. Res., 2009

Nonparametric Greedy Algorithms for the Sparse Learning Problem.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Blockwise coordinate descent procedures for the multi-task lasso, with applications to neural semantic basis discovery.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

A Framework for Efficient Association Rule Mining in XML Data.
Proceedings of the Database Technologies: Concepts, 2009

2008
Nonparametric regression and classification with joint sparsity constraints.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

2007
Sparse Nonparametric Density Estimation in High Dimensions Using the Rodeo.
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007

SpAM: Sparse Additive Models.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

2006
A Framework for Efficient Association Rule Mining in XML Data.
J. Database Manag., 2006

Towards the Prediction of Protein Abundance from Tandem Mass Spectrometry Data.
Proceedings of the Sixth SIAM International Conference on Data Mining, 2006

2005
D-GridMST: Clustering Large Distributed Spatial Databases.
Proceedings of the Classification and Clustering for Knowledge Discovery, 2005

XAR-miner: efficient association rules mining for XML data.
Proceedings of the 14th international conference on World Wide Web, 2005

X-warehouse: building query pattern-driven data.
Proceedings of the 14th international conference on World Wide Web, 2005

Visual Sign Language Recognition Based on HMMs and Auto-regressive HMMs.
Proceedings of the Gesture in Human-Computer Interaction and Simulation, 2005

2004
A robot path planning approach based on generalized semi-infinite optimization.
Proceedings of the 2004 IEEE Conference on Robotics, Automation and Mechatronics, 2004

An Extended Linear Strategy Bridging the Gap between Regression and SVD Decomposition for Modeling Peptide Tandem Mass Spectrometry Data.
Proceedings of the International Conference on Mathematics and Engineering Techniques in Medicine and Biological Scienes, 2004

An Effective and Efficient Data Cleaning Technique in Large Databases.
Proceedings of the International Conference on Information and Knowledge Engineering. IKE'04, 2004

Generalized Semi-Infinite Optimization and its Application in Robotics' Path Planning Problem.
Proceedings of the International Conference on Artificial Intelligence, 2004

Statistical Issues with Labeled Sample Size Analysis for Semi-Supervised Linear Discriminant Analysis.
Proceedings of the International Conference on Artificial Intelligence, 2004

A Novel Dimensionality Reduction Technique Based on Independent Component Analysis for Modeling Microarray Gene Expression Data.
Proceedings of the International Conference on Artificial Intelligence, 2004

An Efficient Method to Estimate Labelled Sample Size for Transductive LDA(QDA/MDA) Based on Bayes Risk.
Proceedings of the Machine Learning: ECML 2004, 2004

On Efficient and Effective Association Rule Mining from XML Data.
Proceedings of the Database and Expert Systems Applications, 15th International Conference, 2004

PC-Filter: A Robust Filtering Technique for Duplicate Record Detection in Large Databases.
Proceedings of the Database and Expert Systems Applications, 15th International Conference, 2004


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