Probabilistic Prediction of Protein Secondary Structure Using Causal Networks (Extended Abstract). - Arthur L. Delcher; Simon Kasif; Harry R. Goldberg; William H. Hsu (AAAI, 1993)

Protein Secondary-Structure Modeling with Probabilistic Networks. - Arthur L. Delcher; Simon Kasif; Harry R. Goldberg; William H. Hsu (ISMB, 1993)

Automatic Synthesis of Compression Techniques for Heterogeneous - William H. Hsu; Amy E. Zwarico (Softw. Pract. Exp., 1995)

Probabilistic Learning in Bayesian and Stochastic Neural Networks. - William H. Hsu (AAAI/IAAI, 1997)

A position paper on statistical inference techniques which integrate neural network and Bayesian network models. - William H. Hsu (ICNN, 1997)

Bayesian Network Models for Generation of Crisis Management Training Scenarios. - Eugene Grois; William H. Hsu; Mikhail Voloshin; David C. Wilkins (AAAI/IAAI, 1998)

Self-Organized-Expert Modular Network for Classification of Spatiotemporal Sequences. - Sylvian R. Ray; William H. Hsu (Intell. Data Anal., 1998)

Time Series Learning With Probabilistic Network Composites - William H. Hsu (1998)

Self-organizing systems for knowledge discovery in large databases. - William H. Hsu; Loretta S. Anvil; William M. Pottenger; David Tcheng; Michael Welge (IJCNN, 1999)

Construction of recurrent mixture models for time series classification. - William H. Hsu; Sylvian R. Ray (IJCNN, 1999)

Genetic Algorithms for Reformulation of Large-Scale KDD Problems with Many Irrelevant Attributes. - William H. Hsu; Yuhong Cheng; Haipeng Guo; Steven M. Gustafson (GECCO, 2000)

Genetic Wrappers for Constructive Induction in High-Performance Data Mining. - William H. Hsu; Michael Welge; Thomas Redman 001; David Clutter (GECCO, 2000)

A Multistrategy Approach to Classifier Learning from Time Series. - William H. Hsu; Sylvian R. Ray; David C. Wilkins (Mach. Learn., 2000)

Layered Learning in Genetic Programming for a Cooperative Robot Soccer Problem. - Steven M. Gustafson; William H. Hsu (EuroGP, 2001)

A Genetic Algorithm for Tuning Variable Orderings in Bayesian Network Structure Learning. - Haipeng Guo; Benjamin B. Perry; Julie A. Stilson; William H. Hsu (AAAI/IAAI, 2002)

An Ant Colony Approach For The Steiner Tree Problem. - Sanjoy Das; Shekhar V. Gosavi; William H. Hsu; Shilpa A. Vaze (GECCO, 2002)

An Ant Colony Algorithm for Steiner Trees: New Results. - Sanjoy Das; Shekhar V. Gosavi; William H. Hsu; Shilpa A. Vaze (GECCO Late Breaking Papers, 2002)

Genetic Programming And Multi-agent Layered Learning By Reinforcements. - William H. Hsu; Steven M. Gustafson (GECCO, 2002)

A Permutation Genetic Algorithm For Variable Ordering In Learning Bayesian Networks From Data. - William H. Hsu; Haipeng Guo; Benjamin B. Perry; Julie A. Stilson (GECCO, 2002)

Genetic Algorithm Wrappers For Feature Subset Selection In Supervised Inductive Learning. - William H. Hsu; Cecil P. Schmidt; James A. Louis (GECCO, 2002)

High-Performance Commercial Data Mining: A Multistrategy Machine Learning Application. - William H. Hsu; Michael Welge; Thomas Redman 001; David Clutter (Data Min. Knowl. Discov., 2002)

GA-Hardness Revisited. - Haipeng Guo; William H. Hsu (GECCO, 2003)

Empirical Comparison of Incremental Learning Strategies for Genetic Programming-Based Keep-Away Soccer Agents. - William H. Hsu; Scott J. Harmon; Edwin Rodríguez; Christopher Zhong (AAAI Technical Report (2), 2004)

An ACO Algorithm for the Most Probable Explanation Problem. - Haipeng Guo; Prashanth R. Boddhireddy; William H. Hsu (Australian Conference on Artificial Intelligence, 2004)

A Learning-Based Algorithm Selection Meta-reasoner for the Real-Time MPE Problem. - Haipeng Guo; William H. Hsu (Australian Conference on Artificial Intelligence, 2004)

Permutation Genetic Algorithms for Score-Based Bayesian Network Structure Learning. - William H. Hsu; Roby Joehanes (CCCT (1), 2004)

A Comparison of Hybrid Incremental Reuse Strategies for Reinforcement Learning in Genetic Programming. - Scott J. Harmon; Edwin Rodríguez; Christopher Zhong; William H. Hsu (GECCO (2), 2004)

Relational Graphical Models of Computational Workflows for Data Mining. - William H. Hsu (ICSNW, 2004)

Genetic wrappers for feature selection in decision tree induction and variable ordering in Bayesian network structure learning. - William H. Hsu (Inf. Sci., 2004)

Evolutionary tree genetic programming. - Ján Antolík; William H. Hsu (GECCO, 2005)

Dynamic System Prediction using Temporal Artificial Neural Networks and Multi-Objective Genetic Algorithms. - Praveen Koduru; William H. Hsu; Sanjoy Das; Stephen M. Welch; Judith L. Roe (Computational Intelligence, 2005)

Collaborative and Structural Recommendation of Friends using Weblog-based Social Network Analysis. - William H. Hsu; Andrew L. King; Martin S. R. Paradesi; Tejaswi Pydimarri; Tim Weninger (AAAI Spring Symposium: Computational Approaches to Analyzing Weblogs, 2006)

Structural Prediction of Protein-Protein Interactions in Saccharomyces cerevisiae. - Martin S. R. Paradesi; Doina Caragea; William H. Hsu (BIBE, 2007)

Structural Link Analysis from User Profiles and Friends Networks: A Feature Construction Approach. - William H. Hsu; Joseph P. Lancaster; Martin S. R. Paradesi; Tim Weninger (ICWSM, 2007)

A machine learning approach to algorithm selection for NP mathcal{NP} -hard optimization problems: a case study on the MPE problem. - Haipeng Guo; William H. Hsu (Ann. Oper. Res., 2007)

Text Extraction from the Web via Text-to-Tag Ratio. - Tim Weninger; William H. Hsu (DEXA Workshops, 2008)

Ontology-Aware Classification and Association Rule Mining for Interest and Link Prediction in Social Networks. - Waleed Aljandal; Vikas Bahirwani; Doina Caragea; William H. Hsu (AAAI Spring Symposium: Social Semantic Web: Where Web 2.0 Meets Web 3.0, 2009)

Speech-assisted radiology system for retrieval, reporting and annotation. - Tim Weninger; Daniel Greene; Jack Hart; William H. Hsu; Surya Ramachandran (CBMS, 2009)

Predicting protein-protein interactions using numerical associational features. - Waleed Aljandal; William H. Hsu; Jing Xia (CIBCB, 2009)

An evolutionary approach to constructive induction for link discovery. - Tim Weninger; William H. Hsu; Jing Xia; Waleed Aljandal (GECCO, 2009)

Graph Drawing Heuristics for Path Finding in Large Dimensionless Graphs. - Tim Weninger; Rodney Howell; William H. Hsu (IC-AI, 2009)

Protein Protein Interaction Analysis Using Fast Random Walk. - Jing Xia; William H. Hsu (IC-AI, 2009)

Bi-relational Network Analysis Using a Fast Random Walk with Restart. - Jing Xia; Doina Caragea; William H. Hsu (ICDM, 2009)

Ontology-Based Link Prediction in the LiveJournal Social Network. - Doina Caragea; Vikas Bahirwani; Waleed Aljandal; William H. Hsu (SARA, 2009)

Computational knowledge and information management in veterinary epidemiology. - Svitlana Volkova; William H. Hsu (ISI, 2010)

KSU KDD: Word Sense Induction by Clustering in Topic Space. - Wesam Elshamy; Doina Caragea; William H. Hsu (SemEval@ACL, 2010)

Boosting Biomedical Entity Extraction by Using Syntactic Patterns for Semantic Relation Discovery. - Svitlana Volkova; Doina Caragea; William H. Hsu; John Drouhard; Landon Fowles (Web Intelligence, 2010)

CETR: content extraction via tag ratios. - Tim Weninger; William H. Hsu; Jiawei Han 001 (WWW, 2010)

Simulative modeling to control the Foot and Mouth Disease epidemic. - Sohini Roy Chowdhury; Caterina M. Scoglio; William H. Hsu (ICCS, 2010)

Mitigation Strategies for Foot and Mouth Disease: A Learning-Based Approach. - Sohini Roy Chowdhury; Caterina M. Scoglio; William H. Hsu (Int. J. Artif. Life Res., 2011)

Visualization of Clandestine Labs from Seizure Reports: Thematic Mapping and Data Mining Research Directions. - William H. Hsu; Mohammed Abduljabbar; Ryuichi Osuga; Max Lu; Wesam Elshamy (EuroHCIR, 2012)

Opinion Mapping: Information Visualization Approaches for Comparative Sentiment Analysis. - William H. Hsu; Praveen Koduru (EuroHCIR, 2012)

HDPauthor: A New Hybrid Author-Topic Model using Latent Dirichlet Allocation and Hierarchical Dirichlet Processes. - Ming Yang 042; William H. Hsu (WWW (Companion Volume), 2016)

A spatially explicit classification model for affective computing in built environments. - Heath Yates; Brent C. Chamberlain; William H. Hsu (ACII Workshops, 2017)

Arousal Detection for Biometric Data in Built Environments using Machine Learning. - Heath Yates; Brent C. Chamberlain; Greg Norman; William H. Hsu (AffComp@IJCAI, 2017)

Corpus and Deep Learning Classifier for Collection of Cyber Threat Indicators in Twitter Stream. - Vahid Behzadan; Carlos A. Aguirre; Avishek Bose; William H. Hsu (IEEE BigData, 2018)

MATESC: Metadata-Analytic Text Extractor and Section Classifier for Scientific Publications. - Maria F. De La Torre; Carlos A. Aguirre; BreAnn M. Anshutz; William H. Hsu (KDIR, 2018)

Binary Classification of Arousal in Built Environments using Machine Learning. - Heath Yates; Brent C. Chamberlain; William H. Hsu (AffComp@IJCAI, 2018)

Towards Faster Annotation Interfaces for Learning to Filter in Information Extraction and Search. - Carlos A. Aguirre; Shelby Coen; Maria F. De La Torre; William H. Hsu; Margaret Rys (IUI Workshops, 2018)

Interactive Recommendations by Combining User-Item Preferences with Linked Open Data. - Surya Kallumadi; William H. Hsu (UMAP (Adjunct Publication), 2018)

Machine Learning for Predictive Analytics of Compute Cluster Jobs. - Dan Andresen; William H. Hsu; Huichen Yang; Adedolapo Okanlawon (CoRR, 2018)

Early-Season Stand Count Determination in Corn via Integration of Imagery from Unmanned Aerial Systems (UAS) and Supervised Learning Techniques. - Sebastian Varela; Pruthvidhar Reddy Dhodda; William H. Hsu; P. V. Vara Prasad; Yared Assefa; Nahuel R. Peralta; Terry Griffin 002; Ajay Sharda; Allison Ferguson; Ignacio Antonio Ciampitti (Remote. Sens., 2018)

A novel approach for detection and ranking of trendy and emerging cyber threat events in Twitter streams. - Avishek Bose; Vahid Behzadan; Carlos A. Aguirre; William H. Hsu (ASONAM, 2019)

Pipelines for Procedural Information Extraction from Scientific Literature: Towards Recipes using Machine Learning and Data Science. - Huichen Yang; Alice Lam; Thomas Yong-Jin Han; David Buttler; William H. Hsu; Carlos A. Aguirre; Maria F. De La Torre; Derek Christensen; Luis Bobadilla; Emily Davich; Jordan Roth; Lei Luo 007; et al. (OST@ICDAR, 2019)

Adversarial Exploitation of Policy Imitation. - Vahid Behzadan; William H. Hsu (AISafety@IJCAI, 2019)

Watermarking of DRL Policies with Sequential Triggers. - Vahid Behzadan; William H. Hsu (AISafety@IJCAI, 2019)

RL-Based Method for Benchmarking the Adversarial Resilience and Robustness of Deep Reinforcement Learning Policies. - Vahid Behzadan; William H. Hsu (SAFECOMP Workshops, 2019)

Improving HPC System Performance by Predicting Job Resources via Supervised Machine Learning. - Mohammed Tanash; Brandon Dunn; Daniel Andresen; William H. Hsu; Huichen Yang; Adedolapo Okanlawon (PEARC, 2019)

Analysis and Improvement of Adversarial Training in DQN Agents With Adversarially-Guided Exploration (AGE). - Vahid Behzadan; William H. Hsu (CoRR, 2019)

Sequential Triggers for Watermarking of Deep Reinforcement Learning Policies. - Vahid Behzadan; William H. Hsu (CoRR, 2019)

Hybridized Threshold Clustering for Massive Data. - Jianmei Luo; ChandraVyas Annakula; Aruna Sai Kannamareddy; Jasjeet S. Sekhon; William Henry Hsu; Michael Higgins (CoRR, 2019)

Shape-aware generative adversarial networks for attribute transfer. - Lei Luo 007; William H. Hsu (ICMV, 2020)

Vision-Based Layout Detection from Scientific Literature using Recurrent Convolutional Neural Networks. - Huichen Yang; William H. Hsu (ICPR, 2020)

Abstractive Text Summarization of Disaster-Related Documents. - Nasik Muhammad Nafi; Avishek Bose; Sarthak Khanal; Doina Caragea; William H. Hsu (ISCRAM, 2020)

Addressing Class Imbalance in Image-Based Plant Disease Detection: Deep Generative vs. Sampling-Based Approaches. - Nasik Muhammad Nafi; William H. Hsu (IWSSIP, 2020)

Data Augmentation Using Generative Adversarial Networks for Electrical Insulator Anomaly Detection. - Lei Luo 007; William H. Hsu; Shangxian Wang (MSIE, 2020)

Shape-aware Generative Adversarial Networks for Attribute Transfer. - Lei Luo 007; William H. Hsu; Shangxian Wang (CoRR, 2020)

Feature Selection for Learning to Predict Outcomes of Compute Cluster Jobs with Application to Decision Support. - Adedolapo Okanlawon; Huichen Yang; Avishek Bose; William H. Hsu; Dan Andresen; Mohammed Tanash (CoRR, 2020)

Named Entity Recognition from Synthesis Procedural Text in Materials Science Domain with Attention-Based Approach. - Huichen Yang; William H. Hsu (SDU@AAAI, 2021)

HPCGCN: A Predictive Framework on High Performance Computing Cluster Log Data Using Graph Convolutional Networks. - Avishek Bose; Huichen Yang; William H. Hsu; Daniel Andresen (IEEE BigData, 2021)

eGAN: Unsupervised Approach to Class Imbalance Using Transfer Learning. - Ademola Okerinde; William H. Hsu; Tom Theis; Nasik Muhammad Nafi; Lior Shamir (CAIP (1), 2021)

Towards Fine-Grained Control over Latent Space for Unpaired Image-to-Image Translation. - Lei Luo 007; William H. Hsu; Shangxian Wang (ICANN (3), 2021)

Automatic metadata information extraction from scientific literature using deep neural networks. - Huichen Yang; William H. Hsu (ICMV, 2021)

Tracing Relevant Twitter Accounts Active in Cyber Threat Intelligence Domain by Exploiting Content and Structure of Twitter Network. - Avishek Bose; Shreya Gopal Sundari; Vahid Behzadan; William H. Hsu (ISI, 2021)

Ensemble Prediction of Job Resources to Improve System Performance for Slurm-Based HPC Systems. - Mohammed Tanash; Huichen Yang; Daniel Andresen; William H. Hsu (PEARC, 2021)

AMMUNIT: An Attention-Based Multimodal Multi-domain UNsupervised Image-to-Image Translation Framework. - Lei Luo 007; William H. Hsu (ICANN (2), 2022)

Transformer-Based Approach for Document Layout Understanding. - Huichen Yang; William H. Hsu (ICIP, 2022)

Attention-based Partial Decoupling of Policy and Value for Generalization in Reinforcement Learning. - Nasik Muhammad Nafi; Creighton Glasscock; William H. Hsu (ICMLA, 2022)

Few-Shot Learning in Object Classification using Meta-Learning with Between-Class Attribute Transfer. - Majed Alsadhan; William H. Hsu (ICMLC, 2022)

High Performance Computing Queue Time Prediction Using Clustering and Regression. - Scott Hutchison; Daniel Andresen; Mitchell L. Neilsen; William H. Hsu; Benjamin Parsons (PPAM (2), 2022)

KDDIE at SemEval-2022 Task 11: Using DeBERTa for Named Entity Recognition. - Caleb Martin; Huichen Yang; William H. Hsu (SemEval@NAACL, 2022)

Multi-Horizon Learning in Procedurally-Generated Environments for Off-Policy Reinforcement Learning (Student Abstract). - Raja Farrukh Ali; Kevin Duong; Nasik Muhammad Nafi; William H. Hsu (AAAI, 2023)

Analyzing the Sensitivity to Policy-Value Decoupling in Deep Reinforcement Learning Generalization. - Nasik Muhammad Nafi; Raja Farrukh Ali; William H. Hsu (AAMAS, 2023)

Attention-Augmented Parametric Kernel Graph Neural Network (APKGNN) for Node Classification. - Avishek Bose; William H. Hsu (ICMLA, 2023)

Relevant Instance Segmentation in American Football Practice Images to Aid Risky Tackle Detection. - Nasik Muhammad Nafi; Ashley Rediger; Scott Dietrich; William H. Hsu (ICMLA, 2023)

Policy Optimization with Augmented Value Targets for Generalization in Reinforcement Learning. - Nasik Muhammad Nafi; Giovanni Poggi-Corradini; William H. Hsu (IJCNN, 2023)

Context-Augmented Key Phrase Extraction from Short Texts for Cyber Threat Intelligence Tasks. - Avishek Bose; Huichen Yang; Marissa Shivers; Ahat Orazgeldiyev; William H. Hsu (ISI, 2023)

KDDIE at SemEval-2023 Task 2: External Knowledge Injection for Named Entity Recognition. - Caleb Martin; Huichen Yang; William H. Hsu (SemEval@ACL, 2023)

Policy Optimization using Horizon Regularized Advantage to Improve Generalization in Reinforcement Learning. - Nasik Muhammad Nafi; Raja Farrukh Ali; William H. Hsu; Kevin Duong; Mason Vick (AAMAS, 2024)

Parallel Backfill: Improving HPC System Performance by Scheduling Jobs in Parallel. - Donald Riffel; Daniel Andresen; Scott Hutchison; William H. Hsu (PEARC, 2024)

Unifying Interpretability and Explainability for Alzheimer's Disease Progression Prediction. - Raja Farrukh Ali; Stephanie Milani; John Woods; Emmanuel Adenij; Ayesha Farooq; Clayton Mansel; Jeffrey Burns; William H. Hsu (CoRR, 2024)

A Minimalist Approach to Augmentation-based Self-supervised Representation Learning for On-policy Reinforcement Learning. - Nasik Muhammad Nafi; William H. Hsu (AAMAS, 2025)