Representation Requirements for Supporting Decision Model Formulation. - Tze-Yun Leong (UAI, 1991)

Representing Context-Sensitive Knowledge in a Network Formalism: A Preliminary Report. - Tze-Yun Leong (UAI, 1992)

An integrated approach to dynamic decision making under uncertainty. - Tze-Yun Leong (1994)

Multiple Perspective Reasoning. - Tze-Yun Leong (KR, 1996)

Learning Conditional Probabilities for Dynamic Influence Structures in Medical Decision Models. - Cungen Cao 002; Tze-Yun Leong (AMIA, 1997)

Induction of Diagnostic Test Strategies with Multi-Level Information Measures. - Cungen Cao 002; Tze-Yun Leong; Adrian Peng Kheong Leong (MedInfo, 1998)

Modelling Medical Decisions in DynaMoL: A New General Framework of Dynamic Decision Analysis. - Tze-Yun Leong; Cungen Cao 002 (MedInfo, 1998)

Consistency Management in Multiple Perspective Medical Decision Analysis. - Jianye Zheng; Tze-Yun Leong (MedInfo, 1998)

Knowledge-Based Formulation of Dynamic Decision Models. - Chenggang Wang; Tze-Yun Leong (PRICAI, 1998)

Multiple Perspective Dynamic Decision Making. - Tze-Yun Leong (Artif. Intell., 1998)

Dynamic decision analysis in medicine: a data-driven approach. - Cungen Cao 002; Tze-Yun Leong; Adrian Peng Kheong Leong; Francis C. Seow (Int. J. Medical Informatics, 1998)

Decision analytic approach to severe head injury management. - David Harmanec; Tze-Yun Leong; Suman Sundaresh; Kim-Leng Poh; Tseng-Tsai Yeo; Ivan Ng; Thomas W. Lew (AMIA, 1999)

PROBES: a framework for probability elicitation from experts. - Aik-Hiang Lau; Tze-Yun Leong (AMIA, 1999)

Supporting multi-level multi-perspective dynamic decision making in medicine. - Suman Sundaresh; Tze-Yun Leong; Peter Haddawy (AMIA, 1999)

Using linear regression functions to abstract high-frequency data in medicine. - Jian Li; Tze-Yun Leong (AMIA, 2000)

Application of K-nearest neighbors algorithm on breast cancer diagnosis problem. - Manish Sarkar; Tze-Yun Leong (AMIA, 2000)

A data preprocessing framework for supporting probability-learning in dynamic decision modeling in medicine. - Fu Zhao; Tze-Yun Leong (AMIA, 2000)

Automating Dynamic Decision Model Construction to Support Clinical Practice Guideline Development. - Ai-Ling Zhu; Tze-Yun Leong (EWGLP, 2000)

Causal Mechanism-based Model Constructions. - Tsai-Ching Lu; Marek J. Druzdzel; Tze-Yun Leong (UAI, 2000)

PDL: a definition language for trend pattern representation and detection in medicine. - Jian Li; Tze-Yun Leong (AMIA, 2001)

Fuzzy K-means clustering with missing values. - Manish Sarkar; Tze-Yun Leong (AMIA, 2001)

Application of Fuzzy Similarity-Based Fractal Dimensions to Characterize Medical Time Series. - Manish Sarkar; Tze-Yun Leong (ICML, 2001)

Constructing Influence Views from Data to Support Dynamic Decision Making in Medicine. - XinZhi Qi; Tze-Yun Leong (MedInfo, 2001)

Nonparametric Techniques to Extract Fuzzy Rules for Breast Cancer Diagnosis Problem. - Manish Sarkar; Tze-Yun Leong (MedInfo, 2001)

Building decision support systems for treating severe head injuries. - Charles Sheeba Dora; Manish Sarkar; Suman Sundaresh; David Harmanec; Tseng-Tsai Yeo; Kim-Leng Poh; Tze-Yun Leong (SMC, 2001)

Top-down approaches to abstract medical time series using linear segments. - Manish Sarkar; Tze-Yun Leong (SMC, 2001)

Mining of Correlated Rules in Genome Sequences. - Li Lin; Limsoon Wong; Tze-Yun Leong; Pohsan Lai (AMIA, 2002)

Automated Knowledge Extraction for Decision Model Construction: A Data Mining Approach. - Ai-Ling Zhu; Jian Li; Tze-Yun Leong (AMIA, 2003)

Characterization of medical time series using fuzzy similarity-based fractal dimensions. - Manish Sarkar; Tze-Yun Leong (Artif. Intell. Medicine, 2003)

Classifying Biomedical Citations without Labeled Training Examples. - Xiaoli Li 001; Rohit Joshi; Sreeram Ramachandaran; Tze-Yun Leong (ICDM, 2004)

We Did the Right Thing: An Intervention Analysis Approach to Modeling Intervened SARS Propagation in Singapore. - Bin Han; Tze-Yun Leong (MedInfo, 2004)

Cost-Effectiveness Analysis of Colorectal Cancer Screening Strategies in Singapore: A Dynamic Decision Analytic Approach. - Swee-Seong Wong; Adrian Peng Kheong Leong; Tze-Yun Leong (MedInfo, 2004)

Translation Initiation Sites Prediction with Mixture Gaussian Models. - Guoliang Li 002; Tze-Yun Leong; Louxin Zhang (WABI, 2004)

Organizing Committee. - Marek J. Druzdzel; Tze-Yun Leong (AAAI Spring Symposium: Challenges to Decision Support in a Changing World, 2005)

Preface. - Marek J. Druzdzel; Tze-Yun Leong (AAAI Spring Symposium: Challenges to Decision Support in a Changing World, 2005)

Integration of Probabilistic Graphic Models for Decision Support. - Chang-an Jiang; Kim-Leng Poh; Tze-Yun Leong (AAAI Spring Symposium: Challenges to Decision Support in a Changing World, 2005)

Challenges in an Adaptive Modeling Framework for Systems Biology. - Rohit Joshi; Tze-Yun Leong (AAAI Spring Symposium: Challenges to Decision Support in a Changing World, 2005)

A Framework to Learn Bayesian Network from Changing, Multiple-Source Biomedical Data. - Guoliang Li 002; Tze-Yun Leong (AAAI Spring Symposium: Challenges to Decision Support in a Changing World, 2005)

Pgmc: a Framework for Probabilistic Graphical Model Combination. - Chang-an Jiang; Tze-Yun Leong; Kim-Leng Poh (AMIA, 2005)

LinkageTracker: A Discriminative Pattern Tracking Approach to Linkage Disequilibrium Mapping. - Li Lin; Limsoon Wong; Tze-Yun Leong; Pohsan Lai (DASFAA, 2005)

Reports on the 2005 AAAI Spring Symposium Series. - Michael L. Anderson; Thomas Barkowsky; Pauline Berry; Douglas S. Blank; Timothy Chklovski; Pedro M. Domingos; Marek J. Druzdzel; Christian Freksa; John Gersh; Mary Hegarty; Tze-Yun Leong; Henry Lieberman; et al. (AI Mag., 2005)

Translation Initiation Sites Prediction with Mixture Gaussian Models in Human cDNA Sequences. - Guoliang Li 002; Tze-Yun Leong; Louxin Zhang (IEEE Trans. Knowl. Data Eng., 2005)

Set-based Cascading Approaches for Magnetic Resonance (MR) Image Segmentation (SCAMIS). - Jiang Liu 001; Tze-Yun Leong; Chee Kin Ban; Boon Pin Tan; Borys Shuter; Shih-Chang Wang (AMIA, 2006)

Patient-Specific Inference and Situation-Dependent Classification Using Context-Sensitive Networks. - Rohit Joshi; Tze-Yun Leong (AMIA, 2006)

A Set-based Hybrid Approach (SHA) for MRI Segmentation. - Jiang Liu 001; Tze-Yun Leong; Chee Kin Ban; Boon Pin Tan; Borys Shuter; Shih-Chang Wang (ICARCV, 2006)

Predicting Coronary Artery Disease with Medical Profile and Gene Polymorphisms Data. - Qiongyu Chen; Guoliang Li 002; Tze-Yun Leong; Chew-Kiat Heng (MedInfo, 2007)

Biomedical Knowledge Discovery with Topological Constraints Modeling in Bayesian Networks: A Preliminary Report. - Guoliang Li 002; Tze-Yun Leong (MedInfo, 2007)

ECTracker - An Efficient Algorithm for Haplotype Analysis and Classification. - Li Lin; Limsoon Wong; Tze-Yun Leong; Pohsan Lai (MedInfo, 2007)

Identifying Causal Effects from Data for the Clinical Ventilation Process Modelling. - Bin Han 009; Guoliang Li 002; Tze-Yun Leong; Yanchun Zhang; Lihua Li 002; Wei Liu 040; Lei Zhu; Weidong Xu (BMEI (1), 2008)

Text Mining in Radiology Reports. - Tianxia Gong; Chew Lim Tan; Tze-Yun Leong; Cheng Kiang Lee; Boon Chuan Pang; C. C. Tchoyoson Lim; Qi Tian 002; Suisheng Tang; Zhuo Zhang 001 (ICDM, 2008)

Hemorrhage slices detection in brain CT images. - Ruizhe Liu; Chew Lim Tan; Tze-Yun Leong; Cheng Kiang Lee; Boon Chuan Pang; C. C. Tchoyoson Lim; Qi Tian 002; Suisheng Tang; Zhuo Zhang 001 (ICPR, 2008)

Computer-based decision support for critical and emergency care. - Tze-Yun Leong; Dominik Aronsky; M. Michael Shabot (J. Biomed. Informatics, 2008)

A Surprise Triggered Adaptive and Reactive (STAR) Framework for Online Adaptation in Non-stationary Environments. - Truong-Huy Dinh Nguyen; Tze-Yun Leong (AIIDE, 2009)

Active Learning for Causal Bayesian Network Structure with Non-symmetrical Entropy. - Guoliang Li 002; Tze-Yun Leong (PAKDD, 2009)

An Analytic Characterization of Model Minimization in Factored Markov Decision Processes. - Wenyuan Guo; Tze-Yun Leong (AAAI, 2010)

Towards A Multi-Level Game Model for Influenza Epidemics. - Qiongyu Chen; Tze-Yun Leong (MedInfo, 2010)

A Model Driven Approach to Imbalanced Data Sampling in Medical Decision Making. - Hong-Li Yin; Tze-Yun Leong (MedInfo, 2010)

TBIdoc: 3D content-based CT image retrieval system for traumatic brain injury. - Shimiao Li; Tianxia Gong; Jie Wang; Ruizhe Liu; Chew Lim Tan; Tze-Yun Leong; Boon Chuan Pang; C. C. Tchoyoson Lim; Cheng Kiang Lee; Qi Tian 002; Zhuo Zhang 001 (Computer-Aided Diagnosis, 2010)

CAPIR: Collaborative Action Planning with Intention Recognition. - Truong-Huy Dinh Nguyen; David Hsu; Wee Sun Lee; Tze-Yun Leong; Leslie Pack Kaelbling; Tomás Lozano-Pérez; Andrew Haydn Grant (AIIDE, 2011)

An automated pathological class level annotation system for volumetric brain images. - Thien Anh Dinh; Tomi Silander; C. C. Tchoyoson Lim; Tze-Yun Leong (AMIA, 2012)

Transferring Expectations in Model-based Reinforcement Learning. - Trung Thanh Nguyen 005; Tomi Silander; Tze-Yun Leong (NIPS, 2012)

Bootstrapping Monte Carlo Tree Search with an Imperfect Heuristic. - Truong-Huy Dinh Nguyen; Wee Sun Lee; Tze-Yun Leong (ECML/PKDD (2), 2012)

A Dynamic Programming Algorithm for Learning Chain Event Graphs. - Tomi Silander; Tze-Yun Leong (Discovery Science, 2013)

Online Feature Selection for Model-based Reinforcement Learning. - Trung Thanh Nguyen 005; Zhuoru Li; Tomi Silander; Tze-Yun Leong (ICML (1), 2013)

Writing for Publication in Biomedical Informatics Journals. - Dominik Aronsky; Jan L. Talmon; Reinhold Haux; Nicolette de Keizer; Tze-Yun Leong; Charles Safran; Christoph U. Lehmann (MedInfo, 2013)

Unsupervised Medical Image Classification by Combining Case-Based Classifiers. - Thien Anh Dinh; Tomi Silander; Bolan Su; Tianxia Gong; Boon Chuan Pang; C. C. Tchoyoson Lim; Cheng Kiang Lee; Chew Lim Tan; Tze-Yun Leong (MedInfo, 2013)

Causal Mechanism-based Model Construction - Tsai-Ching Lu; Marek J. Druzdzel; Tze-Yun Leong (CoRR, 2013)

Bootstrapping Simulation-Based Algorithms with a Suboptimal Policy. - Truong-Huy Dinh Nguyen; Tomi Silander; Wee Sun Lee; Tze-Yun Leong (ICAPS, 2014)

Automated Prediction of Glasgow Outcome Scale for Traumatic Brain Injury. - Bolan Su; Thien Anh Dinh; Abhinit Kumar Ambastha; Tianxia Gong; Tomi Silander; Shijian Lu; C. C. Tchoyoson Lim; Boon Chuan Pang; Cheng Kiang Lee; Tze-Yun Leong; Chew Lim Tan (ICPR, 2014)

Automatic detection and quantification of brain midline shift using anatomical marker model. - Ruizhe Liu; Shimiao Li; Bolan Su; Chew Lim Tan; Tze-Yun Leong; Boon Chuan Pang; C. C. Tchoyoson Lim; Cheng Kiang Lee (Comput. Medical Imaging Graph., 2014)

Fusing Heterogeneous Data for Alzheimer's Disease Classification. - Parvathy Sudhir Pillai; Tze-Yun Leong (MedInfo, 2015)

A Core Task Abstraction Approach to Hierarchical Reinforcement Learning: (Extended Abstract). - Zhuoru Li; Akshay Narayan 002; Tze-Yun Leong (AAMAS, 2016)

Toward A Collaborative AI Framework for Assistive Dementia Care. - Tze-Yun Leong (AAAI Workshops, 2017)

An Efficient Approach to Model-Based Hierarchical Reinforcement Learning. - Zhuoru Li; Akshay Narayan 002; Tze-Yun Leong (AAAI, 2017)

SEAPoT-RL: Selective Exploration Algorithm for Policy Transfer in RL. - Akshay Narayan 002; Zhuoru Li; Tze-Yun Leong (AAAI, 2017)

A Deep Learning Approach to Neuroanatomical Characterisation of Alzheimer's Disease. - Abhinit Kumar Ambastha; Tze-Yun Leong (MedInfo, 2017)

Scalable transfer learning in heterogeneous, dynamic environments. - Trung Thanh Nguyen 005; Tomi Silander; Zhuoru Li; Tze-Yun Leong (Artif. Intell., 2017)

Knowledge-Driven Interpretation of Multi-View Data in Medicine. - Parvathy Sudhir Pillai; Lei Feng; Tze-Yun Leong (MIE, 2018)

Knowledge-driven generative subspaces for modeling multi-view dependencies in medical data. - Parvathy Sudhir Pillai; Tze-Yun Leong (CoRR, 2018)

Effects of Task Similarity on Policy Transfer with Selective Exploration in Reinforcement Learning. - Akshay Narayan 002; Tze-Yun Leong (AAMAS, 2019)

Modeling Multi-View Dependence in Bayesian Networks for Alzheimer's Disease Detection. - Parvathy Sudhir Pillai; Tze-Yun Leong (MedInfo, 2019)

Adaptive Knowledge Transfer based on Transfer Neural Kernel Network. - Pengfei Wei 001; Xinghua Qu; Yiping Ke; Tze-Yun Leong; Yew-Soon Ong (AAMAS, 2020)

Succinct Adaptive Manifold Transfer. - Pengfei Wei 001; Yiping Ke; Zhiqiang Xu 003; Tze-Yun Leong (CIKM, 2020)

Randomized Transferable Machine. - Pengfei Wei 001; Tze-Yun Leong (ICPR, 2020)

A Causal Modeling Framework with Stochastic Confounders. - Thanh Vinh Vo; Pengfei Wei; Wicher Bergsma; Tze-Yun Leong (CoRR, 2020)

Hierarchial Reinforcement Learning in StarCraft II with Human Expertise in Subgoals Selection. - Xinyi Xu; Tiancheng Huang; Pengfei Wei 001; Akshay Narayan 002; Tze-Yun Leong (CoRR, 2020)

Causal Modeling with Stochastic Confounders. - Thanh Vinh Vo; Pengfei Wei 001; Wicher Bergsma; Tze-Yun Leong (AISTATS, 2021)

Adaptive Multi-Source Causal Inference. - Thanh Vinh Vo; Pengfei Wei; Trong Nghia Hoang; Tze-Yun Leong (CoRR, 2021)

Federated Estimation of Causal Effects from Observational Data. - Thanh Vinh Vo; Trong Nghia Hoang; Young Lee; Tze-Yun Leong (CoRR, 2021)

Adaptive Multi-Source Causal Inference from Observational Data. - Thanh Vinh Vo; Pengfei Wei 001; Trong Nghia Hoang; Tze-Yun Leong (CIKM, 2022)

An Adaptive Kernel Approach to Federated Learning of Heterogeneous Causal Effects. - Thanh Vinh Vo; Arnab Bhattacharyya 001; Young Lee; Tze-Yun Leong (NeurIPS, 2022)

Bayesian federated estimation of causal effects from observational data. - Thanh Vinh Vo; Young Lee; Trong Nghia Hoang; Tze-Yun Leong (UAI, 2022)

Subdomain Adaptation With Manifolds Discrepancy Alignment. - Pengfei Wei 001; Yiping Ke; Xinghua Qu; Tze-Yun Leong (IEEE Trans. Cybern., 2022)

Hierarchical Reinforcement Learning with Human-AI Collaborative Sub-Goals Optimization. - Haozhe Ma; Thanh Vinh Vo; Tze-Yun Leong (AAMAS, 2023)

Discovering Low-Dimensional Causal Pathways between Multiple Interacting Neuronal Populations. - Evangelos Sigalas; Thanh Vinh Vo; Tze-Yun Leong; Camilo Libedinsky (CogSci, 2023)

Adversarial Learning Networks: Source-free Unsupervised Domain Incremental Learning. - Abhinit Kumar Ambastha; Tze-Yun Leong (CoRR, 2023)

Federated Learning of Causal Effects from Incomplete Observational Data. - Thanh Vinh Vo; Young Lee; Tze-Yun Leong (CoRR, 2023)

Mixed-Initiative Bayesian Sub-Goal Optimization in Hierarchical Reinforcement Learning. - Haozhe Ma; Thanh Vinh Vo; Tze-Yun Leong (AAMAS, 2024)

Decoupled Prompt-Adapter Tuning for Continual Activity Recognition. - Di Fu; Thanh Vinh Vo; Haozhe Ma; Tze-Yun Leong (CoLLAs, 2024)

Reward Shaping for Reinforcement Learning with An Assistant Reward Agent. - Haozhe Ma; Kuankuan Sima; Thanh Vinh Vo; Di Fu; Tze-Yun Leong (ICML, 2024)

Knowledge Sharing and Transfer via Centralized Reward Agent for Multi-Task Reinforcement Learning. - Haozhe Ma; Zhengding Luo; Thanh Vinh Vo; Kuankuan Sima; Tze-Yun Leong (CoRR, 2024)

Highly Efficient Self-Adaptive Reward Shaping for Reinforcement Learning. - Haozhe Ma; Zhengding Luo; Thanh Vinh Vo; Kuankuan Sima; Tze-Yun Leong (ICLR, 2025)

JEDI: Latent End-to-end Diffusion Mitigates Agent-Human Performance Asymmetry in Model-Based Reinforcement Learning. - Jing Yu Lim; Zarif Ikram; Samson Yu 001; Haozhe Ma; Tze-Yun Leong; Dianbo Liu (CoRR, 2025)

Causal Policy Learning in Reinforcement Learning: Backdoor-Adjusted Soft Actor-Critic. - Thanh Vinh Vo; Young Lee; Haozhe Ma; Chien Lu; Tze-Yun Leong (CoRR, 2025)

Exploration by Random Reward Perturbation. - Haozhe Ma; Guoji Fu; Zhengding Luo; Jiele Wu; Tze-Yun Leong (CoRR, 2025)

Federated causal inference from observational data. - Thanh Vinh Vo; Young Lee; Tze-Yun Leong (Mach. Learn., 2025)