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William H. Hsu
William Henry Hsu
Person information
- affiliation: Kansas State University, Manhattan, KS, USA
- affiliation (PhD 1998): University of Illinois, Urbana-Champaign, Champaign, IL, USA
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2020 – today
- 2024
- [c87]Nasik Muhammad Nafi, Raja Farrukh Ali, William H. Hsu, Kevin Duong, Mason Vick:
Policy Optimization using Horizon Regularized Advantage to Improve Generalization in Reinforcement Learning. AAMAS 2024: 1427-1435 - [c86]Nasik Muhammad Nafi, Raja Farrukh Ali, William H. Hsu:
Analyzing the Sensitivity to Policy-Value Decoupling in Deep Reinforcement Learning Generalization. IJCNN 2024: 1-8 - [c85]Donald Riffel
, Daniel Andresen
Parallel Backfill: Improving HPC System Performance by Scheduling Jobs in Parallel. PEARC 2024: 69:1-69:4 - [i15]Raja Farrukh Ali, Stephanie Milani, John Woods, Emmanuel Adenij, Ayesha Farooq, Clayton Mansel, Jeffrey Burns, William H. Hsu:
Unifying Interpretability and Explainability for Alzheimer's Disease Progression Prediction. CoRR abs/2406.07777 (2024) - 2023
- [c84]Raja Farrukh Ali, Kevin Duong, Nasik Muhammad Nafi, William H. Hsu:
Multi-Horizon Learning in Procedurally-Generated Environments for Off-Policy Reinforcement Learning (Student Abstract). AAAI 2023: 16150-16151 - [c83]Nasik Muhammad Nafi, Raja Farrukh Ali, William H. Hsu:
Analyzing the Sensitivity to Policy-Value Decoupling in Deep Reinforcement Learning Generalization. AAMAS 2023: 2625-2627 - [c82]Nasik Muhammad Nafi, Ashley Rediger, Scott Dietrich, William H. Hsu:
Relevant Instance Segmentation in American Football Practice Images to Aid Risky Tackle Detection. ICMLA 2023: 725-729 - [c81]Avishek Bose, William H. Hsu:
Attention-Augmented Parametric Kernel Graph Neural Network (APKGNN) for Node Classification. ICMLA 2023: 744-751 - [c80]Nasik Muhammad Nafi, Giovanni Poggi-Corradini, William H. Hsu:
Policy Optimization with Augmented Value Targets for Generalization in Reinforcement Learning. IJCNN 2023: 1-8 - [c79]Avishek Bose, Huichen Yang, Marissa Shivers, Ahat Orazgeldiyev, William H. Hsu:
Context-Augmented Key Phrase Extraction from Short Texts for Cyber Threat Intelligence Tasks. ISI 2023: 1-6 - [c78]Caleb Martin, Huichen Yang, William H. Hsu:
KDDIE at SemEval-2023 Task 2: External Knowledge Injection for Named Entity Recognition. SemEval@ACL 2023: 1498-1501 - 2022
- [c77]Lei Luo, William H. Hsu:
AMMUNIT: An Attention-Based Multimodal Multi-domain UNsupervised Image-to-Image Translation Framework. ICANN (2) 2022: 358-370 - [c76]Huichen Yang, William H. Hsu:
Transformer-Based Approach for Document Layout Understanding. ICIP 2022: 4043-4047 - [c75]Nasik Muhammad Nafi, Creighton Glasscock, William H. Hsu:
Attention-based Partial Decoupling of Policy and Value for Generalization in Reinforcement Learning. ICMLA 2022: 15-22 - [c74]Majed Alsadhan, William H. Hsu:
Few-Shot Learning in Object Classification using Meta-Learning with Between-Class Attribute Transfer. ICMLC 2022: 560-565 - [c73]Scott Hutchison
High Performance Computing Queue Time Prediction Using Clustering and Regression. PPAM (2) 2022: 260-272 - [c72]Caleb Martin, Huichen Yang, William H. Hsu:
KDDIE at SemEval-2022 Task 11: Using DeBERTa for Named Entity Recognition. SemEval@NAACL 2022: 1531-1535 - 2021
- [c71]Huichen Yang, William H. Hsu:
Named Entity Recognition from Synthesis Procedural Text in Materials Science Domain with Attention-Based Approach. SDU@AAAI 2021 - [c70]Avishek Bose, Huichen Yang, William H. Hsu, Daniel Andresen:
HPCGCN: A Predictive Framework on High Performance Computing Cluster Log Data Using Graph Convolutional Networks. IEEE BigData 2021: 4113-4118 - [c69]Ademola Okerinde, William H. Hsu, Tom Theis, Nasik Muhammad Nafi, Lior Shamir:
eGAN: Unsupervised Approach to Class Imbalance Using Transfer Learning. CAIP (1) 2021: 322-331 - [c68]Lei Luo, William H. Hsu, Shangxian Wang:
Towards Fine-Grained Control over Latent Space for Unpaired Image-to-Image Translation. ICANN (3) 2021: 408-420 - [c67]Huichen Yang, William H. Hsu:
Automatic metadata information extraction from scientific literature using deep neural networks. ICMV 2021: 1208414 - [c66]Avishek Bose, Shreya Gopal Sundari, Vahid Behzadan, William H. Hsu:
Tracing Relevant Twitter Accounts Active in Cyber Threat Intelligence Domain by Exploiting Content and Structure of Twitter Network. ISI 2021: 1-6 - [c65]Mohammed Tanash
Ensemble Prediction of Job Resources to Improve System Performance for Slurm-Based HPC Systems. PEARC 2021: 21:1-21:8 - [e2]Deepti Lamba, William H. Hsu:
Artificial Intelligence Diversity, Belonging, Equity, and Inclusion, AIDBEI 2021, virtual, February 9, 2021. Proceedings of Machine Learning Research 142, PMLR 2021 [contents] - [i14]Ademola Okerinde, Lior Shamir, William H. Hsu, Tom Theis, Nasik Muhammad Nafi:
eGAN: Unsupervised approach to class imbalance using transfer learning. CoRR abs/2104.04162 (2021) - 2020
- [c64]Lei Luo, William H. Hsu:
Shape-aware generative adversarial networks for attribute transfer. ICMV 2020: 1160515 - [c63]Huichen Yang, William H. Hsu:
Vision-Based Layout Detection from Scientific Literature using Recurrent Convolutional Neural Networks. ICPR 2020: 6455-6462 - [c62]Nasik Muhammad Nafi, Avishek Bose, Sarthak Khanal, Doina Caragea, William H. Hsu:
Abstractive Text Summarization of Disaster-Related Documents. ISCRAM 2020: 881-892 - [c61]Nasik Muhammad Nafi, William H. Hsu:
Addressing Class Imbalance in Image-Based Plant Disease Detection: Deep Generative vs. Sampling-Based Approaches. IWSSIP 2020: 243-248 - [c60]Lei Luo, William H. Hsu, Shangxian Wang:
Data Augmentation Using Generative Adversarial Networks for Electrical Insulator Anomaly Detection. MSIE 2020: 231-236 - [i13]Lei Luo, William H. Hsu, Shangxian Wang:
Shape-aware Generative Adversarial Networks for Attribute Transfer. CoRR abs/2010.05259 (2020) - [i12]Huichen Yang, William H. Hsu:
Vision-Based Layout Detection from Scientific Literature using Recurrent Convolutional Neural Networks. CoRR abs/2010.11727 (2020) - [i11]Adedolapo Okanlawon, Huichen Yang, Avishek Bose, William H. Hsu, Dan Andresen, Mohammed Tanash:
Feature Selection for Learning to Predict Outcomes of Compute Cluster Jobs with Application to Decision Support. CoRR abs/2012.07982 (2020)
2010 – 2019
- 2019
- [c59]Avishek Bose, Vahid Behzadan, Carlos A. Aguirre, William H. Hsu:
A novel approach for detection and ranking of trendy and emerging cyber threat events in Twitter streams. ASONAM 2019: 871-878 - [c58]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, Yihong Theis:
Pipelines for Procedural Information Extraction from Scientific Literature: Towards Recipes using Machine Learning and Data Science. OST@ICDAR 2019: 41-46 - [c57]Vahid Behzadan, William H. Hsu:
Adversarial Exploitation of Policy Imitation. AISafety@IJCAI 2019 - [c56]Vahid Behzadan, William H. Hsu:
Watermarking of DRL Policies with Sequential Triggers. AISafety@IJCAI 2019 - [c55]Vahid Behzadan, William H. Hsu:
RL-Based Method for Benchmarking the Adversarial Resilience and Robustness of Deep Reinforcement Learning Policies. SAFECOMP Workshops 2019: 314-325 - [c54]Mohammed Tanash
Improving HPC System Performance by Predicting Job Resources via Supervised Machine Learning. PEARC 2019: 69:1-69:8 - [i10]Vahid Behzadan, William H. Hsu:
RL-Based Method for Benchmarking the Adversarial Resilience and Robustness of Deep Reinforcement Learning Policies. CoRR abs/1906.01110 (2019) - [i9]Vahid Behzadan, William H. Hsu:
Analysis and Improvement of Adversarial Training in DQN Agents With Adversarially-Guided Exploration (AGE). CoRR abs/1906.01119 (2019) - [i8]Vahid Behzadan, William H. Hsu:
Adversarial Exploitation of Policy Imitation. CoRR abs/1906.01121 (2019) - [i7]Vahid Behzadan, William H. Hsu:
Sequential Triggers for Watermarking of Deep Reinforcement Learning Policies. CoRR abs/1906.01126 (2019) - [i6]Jianmei Luo, ChandraVyas Annakula, Aruna Sai Kannamareddy, Jasjeet S. Sekhon, William Henry Hsu, Michael Higgins:
Hybridized Threshold Clustering for Massive Data. CoRR abs/1907.02907 (2019) - [i5]Avishek Bose, Vahid Behzadan, Carlos A. Aguirre, William H. Hsu:
A Novel Approach for Detection and Ranking of Trendy and Emerging Cyber Threat Events in Twitter Streams. CoRR abs/1907.07768 (2019) - [i4]Huichen Yang, Carlos A. Aguirre, Maria F. De La Torre, Derek Christensen, Luis Bobadilla, Emily Davich, Jordan Roth, Lei Luo, Yihong Theis, Alice Lam, Thomas Yong-Jin Han, David Buttler, William H. Hsu:
Pipelines for Procedural Information Extraction from Scientific Literature: Towards Recipes using Machine Learning and Data Science. CoRR abs/1912.07747 (2019) - 2018
- [j8]Sebastian Varela
Early-Season Stand Count Determination in Corn via Integration of Imagery from Unmanned Aerial Systems (UAS) and Supervised Learning Techniques. Remote. Sens. 10(2): 343 (2018) - [c53]Vahid Behzadan, Carlos A. Aguirre, Avishek Bose, William H. Hsu:
Corpus and Deep Learning Classifier for Collection of Cyber Threat Indicators in Twitter Stream. IEEE BigData 2018: 5002-5007 - [c52]Maria F. De La Torre, Carlos A. Aguirre, BreAnn M. Anshutz, William H. Hsu:
MATESC: Metadata-Analytic Text Extractor and Section Classifier for Scientific Publications. KDIR 2018: 259-265 - [c51]Heath Yates, Brent C. Chamberlain, William H. Hsu:
Binary Classification of Arousal in Built Environments using Machine Learning. AffComp@IJCAI 2018: 35-51 - [c50]Carlos A. Aguirre, Shelby Coen, Maria F. De La Torre, William H. Hsu, Margaret Rys:
Towards Faster Annotation Interfaces for Learning to Filter in Information Extraction and Search. IUI Workshops 2018 - [c49]Surya Kallumadi, William H. Hsu:
Interactive Recommendations by Combining User-Item Preferences with Linked Open Data. UMAP (Adjunct Publication) 2018: 121-125 - [e1]William H. Hsu, Heath Yates:
Workshop on Artificial Intelligence in Affective Computing, AffComp@IJCAI 2018, Stockholm, Sweden, 15 July 2018,. Proceedings of Machine Learning Research 86, PMLR 2018 [contents] - [i3]Dan Andresen, William H. Hsu, Huichen Yang, Adedolapo Okanlawon:
Machine Learning for Predictive Analytics of Compute Cluster Jobs. CoRR abs/1806.01116 (2018) - 2017
- [c48]Heath Yates, Brent C. Chamberlain
A spatially explicit classification model for affective computing in built environments. ACII Workshops 2017: 100-104 - [c47]Heath Yates, Brent C. Chamberlain, Greg Norman, William H. Hsu:
Arousal Detection for Biometric Data in Built Environments using Machine Learning. AffComp@IJCAI 2017: 58-72 - 2016
- [c46]Ming Yang, William H. Hsu:
HDPauthor: A New Hybrid Author-Topic Model using Latent Dirichlet Allocation and Hierarchical Dirichlet Processes. WWW (Companion Volume) 2016: 619-624 - 2015
- [i2]William H. Hsu, Mohammed Abduljabbar, Ryuichi Osuga, Max Lu, Wesam Elshamy:
Visualization of Clandestine Labs from Seizure Reports: Thematic Mapping and Data Mining Research Directions. CoRR abs/1503.01549 (2015) - 2013
- [i1]Wesam Elshamy, Doina Caragea, William H. Hsu:
KSU KDD: Word Sense Induction by Clustering in Topic Space. CoRR abs/1302.7056 (2013) - 2012
- [c45]William H. Hsu, Praveen Koduru:
Opinion Mapping: Information Visualization Approaches for Comparative Sentiment Analysis. EuroHCIR 2012: 25-28 - [c44]William H. Hsu, Mohammed Abduljabbar, Ryuichi Osuga, Max Lu, Wesam Elshamy:
Visualization of Clandestine Labs from Seizure Reports: Thematic Mapping and Data Mining Research Directions. EuroHCIR 2012: 43-46 - 2011
- [j7]Sohini Roy Chowdhury, Caterina M. Scoglio, William H. Hsu:
Mitigation Strategies for Foot and Mouth Disease: A Learning-Based Approach. Int. J. Artif. Life Res. 2(2): 42-76 (2011) - 2010
- [c43]Svitlana Volkova, William H. Hsu:
Computational knowledge and information management in veterinary epidemiology. ISI 2010: 120-125 - [c42]Wesam Elshamy, Doina Caragea, William H. Hsu:
KSU KDD: Word Sense Induction by Clustering in Topic Space. SemEval@ACL 2010: 367-370 - [c41]Svitlana Volkova, Doina Caragea
Boosting Biomedical Entity Extraction by Using Syntactic Patterns for Semantic Relation Discovery. Web Intelligence 2010: 272-278 - [c40]Tim Weninger
CETR: content extraction via tag ratios. WWW 2010: 971-980 - [c39]Sohini Roy Chowdhury, Caterina M. Scoglio
Simulative modeling to control the Foot and Mouth Disease epidemic. ICCS 2010: 2261-2270
2000 – 2009
- 2009
- [c38]Waleed Aljandal, Vikas Bahirwani, Doina Caragea, William H. Hsu:
Ontology-Aware Classification and Association Rule Mining for Interest and Link Prediction in Social Networks. AAAI Spring Symposium: Social Semantic Web: Where Web 2.0 Meets Web 3.0 2009: 3-8 - [c37]Tim Weninger
Speech-assisted radiology system for retrieval, reporting and annotation. CBMS 2009: 1-6 - [c36]Waleed Aljandal, William H. Hsu, Jing Xia:
Predicting protein-protein interactions using numerical associational features. CIBCB 2009: 135-139 - [c35]Tim Weninger
An evolutionary approach to constructive induction for link discovery. GECCO 2009: 1941-1942 - [c34]Tim Weninger, William H. Hsu, Jing Xia, Waleed Aljandal:
An evolutionary approach to constructive induction for link discovery. GECCO (Companion) 2009: 2167-2172 - [c33]Tim Weninger, Rodney Howell, William H. Hsu:
Graph Drawing Heuristics for Path Finding in Large Dimensionless Graphs. IC-AI 2009: 501-507 - [c32]Jing Xia, William H. Hsu:
Protein Protein Interaction Analysis Using Fast Random Walk. IC-AI 2009: 857-863 - [c31]Jing Xia, Doina Caragea
Bi-relational Network Analysis Using a Fast Random Walk with Restart. ICDM 2009: 1052-1057 - [c30]Doina Caragea, Vikas Bahirwani, Waleed Aljandal, William H. Hsu:
Ontology-Based Link Prediction in the LiveJournal Social Network. SARA 2009 - 2008
- [c29]Tim Weninger
Text Extraction from the Web via Text-to-Tag Ratio. DEXA Workshops 2008: 23-28 - 2007
- [j6]Haipeng Guo, William H. Hsu:
A machine learning approach to algorithm selection for NP\mathcal{NP} -hard optimization problems: a case study on the MPE problem. Ann. Oper. Res. 156(1): 61-82 (2007) - [c28]Martin S. R. Paradesi, Doina Caragea
Structural Prediction of Protein-Protein Interactions in Saccharomyces cerevisiae. BIBE 2007: 1270-1274 - [c27]William H. Hsu, Joseph P. Lancaster, Martin S. R. Paradesi, Tim Weninger:
Structural Link Analysis from User Profiles and Friends Networks: A Feature Construction Approach. ICWSM 2007 - 2006
- [c26]William H. Hsu, Andrew L. King, Martin S. R. Paradesi, Tejaswi Pydimarri, Tim Weninger:
Collaborative and Structural Recommendation of Friends using Weblog-based Social Network Analysis. AAAI Spring Symposium: Computational Approaches to Analyzing Weblogs 2006: 55-60 - 2005
- [c25]Ján Antolík
Evolutionary tree genetic programming. GECCO 2005: 1789-1790 - [c24]Praveen Koduru, William H. Hsu, Sanjoy Das, Stephen M. Welch, Judith L. Roe:
Dynamic System Prediction using Temporal Artificial Neural Networks and Multi-Objective Genetic Algorithms. Computational Intelligence 2005: 214-219 - 2004
- [j5]William H. Hsu:
Genetic wrappers for feature selection in decision tree induction and variable ordering in Bayesian network structure learning. Inf. Sci. 163(1-3): 103-122 (2004) - [c23]William H. Hsu, Scott J. Harmon, Edwin Rodríguez, Christopher Zhong:
Empirical Comparison of Incremental Learning Strategies for Genetic Programming-Based Keep-Away Soccer Agents. AAAI Technical Report (2) 2004: 43-51 - [c22]Haipeng Guo, William H. Hsu:
A Learning-Based Algorithm Selection Meta-reasoner for the Real-Time MPE Problem. Australian Conference on Artificial Intelligence 2004: 307-318 - [c21]Haipeng Guo, Prashanth R. Boddhireddy, William H. Hsu:
An ACO Algorithm for the Most Probable Explanation Problem. Australian Conference on Artificial Intelligence 2004: 778-790 - [c20]William H. Hsu, Roby Joehanes:
Permutation Genetic Algorithms for Score-Based Bayesian Network Structure Learning. CCCT (1) 2004: 273-280 - [c19]Scott J. Harmon, Edwin Rodríguez, Christopher Zhong, William H. Hsu:
A Comparison of Hybrid Incremental Reuse Strategies for Reinforcement Learning in Genetic Programming. GECCO (2) 2004: 706-707 - [c18]William H. Hsu:
Relational Graphical Models of Computational Workflows for Data Mining. ICSNW 2004: 309-310 - 2003
- [c17]Haipeng Guo, William H. Hsu:
GA-Hardness Revisited. GECCO 2003: 1584-1585 - 2002
- [j4]William H. Hsu, Michael Welge, Thomas Redman, David Clutter:
High-Performance Commercial Data Mining: A Multistrategy Machine Learning Application. Data Min. Knowl. Discov. 6(4): 361-391 (2002) - [c16]Haipeng Guo, Benjamin B. Perry, Julie A. Stilson, William H. Hsu:
A Genetic Algorithm for Tuning Variable Orderings in Bayesian Network Structure Learning. AAAI/IAAI 2002: 951-952 - [c15]Sanjoy Das, Shekhar V. Gosavi, William H. Hsu, Shilpa A. Vaze:
An Ant Colony Algorithm for Steiner Trees: New Results. GECCO Late Breaking Papers 2002: 69-75 - [c14]Sanjoy Das, Shekhar V. Gosavi, William H. Hsu, Shilpa A. Vaze:
An Ant Colony Approach For The Steiner Tree Problem. GECCO 2002: 135 - [c13]William H. Hsu, Haipeng Guo, Benjamin B. Perry, Julie A. Stilson:
A Permutation Genetic Algorithm For Variable Ordering In Learning Bayesian Networks From Data. GECCO 2002: 383-390 - [c12]William H. Hsu, Cecil P. Schmidt, James A. Louis:
Genetic Algorithm Wrappers For Feature Subset Selection In Supervised Inductive Learning. GECCO 2002: 680 - [c11]William H. Hsu, Steven M. Gustafson:
Genetic Programming And Multi-agent Layered Learning By Reinforcements. GECCO 2002: 764-771 - 2001
- [c10]Steven M. Gustafson, William H. Hsu:
Layered Learning in Genetic Programming for a Cooperative Robot Soccer Problem. EuroGP 2001: 291-301 - 2000
- [j3]William H. Hsu, Sylvian R. Ray, David C. Wilkins:
A Multistrategy Approach to Classifier Learning from Time Series. Mach. Learn. 38(1-2): 213-236 (2000) - [c9]William H. Hsu, Michael Welge, Thomas Redman, David Clutter:
Genetic Wrappers for Constructive Induction in High-Performance Data Mining. GECCO 2000: 765 - [c8]William H. Hsu, Yuhong Cheng, Haipeng Guo, Steven M. Gustafson:
Genetic Algorithms for Reformulation of Large-Scale KDD Problems with Many Irrelevant Attributes. GECCO 2000: 1081
1990 – 1999
- 1999
- [c7]William H. Hsu, Sylvian R. Ray:
Construction of recurrent mixture models for time series classification. IJCNN 1999: 1574-1579 - [c6]William H. Hsu, Loretta S. Anvil, William M. Pottenger, David Tcheng, Michael Welge:
Self-organizing systems for knowledge discovery in large databases. IJCNN 1999: 2480-2485 - 1998
- [b1]William H. Hsu:
Time Series Learning With Probabilistic Network Composites. University of Illinois Urbana-Champaign, USA, 1998 - [j2]Sylvian R. Ray, William H. Hsu:
Self-Organized-Expert Modular Network for Classification of Spatiotemporal Sequences. Intell. Data Anal. 2(1-4): 287-301 (1998) - [c5]Eugene Grois, William H. Hsu, Mikhail Voloshin, David C. Wilkins:
Bayesian Network Models for Generation of Crisis Management Training Scenarios. AAAI/IAAI 1998: 1113-1120 - 1997
- [c4]William H. Hsu:
Probabilistic Learning in Bayesian and Stochastic Neural Networks. AAAI/IAAI 1997: 810 - [c3]William H. Hsu:
A position paper on statistical inference techniques which integrate neural network and Bayesian network models. ICNN 1997: 1972-1977 - 1995
- [j1]William H. Hsu, Amy E. Zwarico:
Automatic Synthesis of Compression Techniques for Heterogeneous. Softw. Pract. Exp. 25(10): 1097-1116 (1995) - 1993
- [c2]Arthur L. Delcher, Simon Kasif, Harry R. Goldberg, William H. Hsu:
Probabilistic Prediction of Protein Secondary Structure Using Causal Networks (Extended Abstract). AAAI 1993: 316-321 - [c1]Arthur L. Delcher, Simon Kasif, Harry R. Goldberg, William H. Hsu:
Protein Secondary-Structure Modeling with Probabilistic Networks. ISMB 1993: 109-117
Coauthor Index
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