| 2025 | AIME | Augmentation-Free Contrastive Learning for EKG Classification. | Junheng Wang, Milos Hauskrecht |
| 2024 | AIME | Enhancing Hypotension Prediction in Real-Time Patient Monitoring Through Deep Learning: A Novel Application of XResNet with Contrastive Learning and Value Attention Mechanisms. | Xiangru Chen, Milos Hauskrecht |
| 2023 | AIME | Machine Learning Models for Automatic Gene Ontology Annotation of Biological Texts. | Jayati H. Jui, Milos Hauskrecht |
| 2023 | AIME | Learning EKG Diagnostic Models with Hierarchical Class Label Dependencies. | Junheng Wang, Milos Hauskrecht |
| 2022 | AIME | Learning to Adapt Dynamic Clinical Event Sequences with Residual Mixture of Experts. | Jeongmin Lee, Milos Hauskrecht |
| 2022 | AIME | Hierarchical Deep Multi-task Learning for Classification of Patient Diagnoses. | Salim Malakouti, Milos Hauskrecht |
| 2021 | AIME | Improving Prediction of Low-Prior Clinical Events with Simultaneous General Patient-State Representation Learning. | Matthew Barren, Milos Hauskrecht |
| 2021 | AIME | Neural Clinical Event Sequence Prediction Through Personalized Online Adaptive Learning. | Jeongmin Lee, Milos Hauskrecht |
| 2021 | FlAIRS | A General Two-stage Multi-label Ranking Framework. | Yanbing Xue, Milos Hauskrecht |
| 2021 | ICML | Event Outlier Detection in Continuous Time. | Siqi Liu, Milos Hauskrecht |
| 2020 | AIME | Multi-scale Temporal Memory for Clinical Event Time-Series Prediction. | Jeongmin Lee, Milos Hauskrecht |
| 2020 | CIKM | Hierarchical Active Learning with Overlapping Regions. | Zhipeng Luo, Milos Hauskrecht |
| 2020 | FlAIRS | Clinical Event Time-Series Modeling with Periodic Events. | Jeongmin Lee, Milos Hauskrecht |
| 2020 | FlAIRS | Not All Samples are Equal: Class Dependent Hierarchical Multi-Task Learning for Patient Diagnosis Classification. | Salim Malakouti, Milos Hauskrecht |
| 2020 | PSB | Monitoring ICU Mortality Risk with a Long Short-Term Memory Recurrent Neural Network. | Ke Yu, Mingda Zhang, Tianyi Cui, Milos Hauskrecht |
| 2019 | AAAI | Active Learning of Multi-Class Classification Models from Ordered Class Sets. | Yanbing Xue, Milos Hauskrecht |
| 2019 | AIME | Recent Context-Aware LSTM for Clinical Event Time-Series Prediction. | Jeongmin Lee, Milos Hauskrecht |
| 2019 | AIME | Predicting Patient's Diagnoses and Diagnostic Categories from Clinical-Events in EHR Data. | Seyedsalim Malakouti, Milos Hauskrecht |
| 2019 | AIME | Mining Compact Predictive Pattern Sets Using Classification Model. | Matteo Mantovani, Carlo Combi, Milos Hauskrecht |
| 2019 | SDM | Region-Based Active Learning with Hierarchical and Adaptive Region Construction. | Zhipeng Luo, Milos Hauskrecht |
| 2018 | AMIA | Using Machine Learning to Predict the Information Seeking Behavior of Clinicians Using an Electronic Medical Record System. | Andrew J. King, Gregory F. Cooper, Harry Hochheiser, Gilles Clermont, Milos Hauskrecht, Shyam Visweswaran |
| 2018 | FlAIRS | Multivariate Conditional Outlier Detection: Identifying Unusual Input-Output Associations in Data. | Charmgil Hong, Milos Hauskrecht |
| 2018 | FlAIRS | Active Learning of Multi-Class Classifiers with Auxiliary Probabilistic Information. | Yanbing Xue, Milos Hauskrecht |
| 2018 | IJCAI | Hierarchical Active Learning with Group Proportion Feedback. | Zhipeng Luo, Milos Hauskrecht |
| 2018 | SIGIR | A Flexible Forecasting Framework for Hierarchical Time Series with Seasonal Patterns: A Case Study of Web Traffic. | Zitao Liu, Yan Yan, Milos Hauskrecht |
| 2017 | AIME | Change-Point Detection Method for Clinical Decision Support System Rule Monitoring. | Siqi Liu, Adam Wright, Milos Hauskrecht |
| 2017 | CIKM | A Personalized Predictive Framework for Multivariate Clinical Time Series via Adaptive Model Selection. | Zitao Liu, Milos Hauskrecht |
| 2017 | FlAIRS | Online Conditional Outlier Detection in Nonstationary Time Series. | Siqi Liu, Adam Wright, Milos Hauskrecht |
| 2017 | FlAIRS | Group-Based Active Learning of Classification Models. | Zhipeng Luo, Milos Hauskrecht |
| 2017 | FlAIRS | Efficient Learning of Classification Models from Soft-label Information by Binning and Ranking. | Yanbing Xue, Milos Hauskrecht |
| 2017 | SDM | Active Learning of Classification Models with Likert-Scale Feedback. | Yanbing Xue, Milos Hauskrecht |
| 2016 | AAAI | Multivariate Conditional Outlier Detection and Its Clinical Application. | Charmgil Hong, Milos Hauskrecht |
| 2016 | AAAI | Learning Adaptive Forecasting Models from Irregularly Sampled Multivariate Clinical Data. | Zitao Liu, Milos Hauskrecht |
| 2016 | ECAI | Learning of Classification Models from Noisy Soft-Labels. | Yanbing Xue, Milos Hauskrecht |
| 2016 | SDM | Learning Linear Dynamical Systems from Multivariate Time Series: A Matrix Factorization Based Framework. | Zitao Liu, Milos Hauskrecht |
| 2015 | AAAI | Multivariate Conditional Anomaly Detection and Its Clinical Application. | Charmgil Hong, Milos Hauskrecht |
| 2015 | AAAI | A Regularized Linear Dynamical System Framework for Multivariate Time Series Analysis. | Zitao Liu, Milos Hauskrecht |
| 2015 | AAAI | Obtaining Well Calibrated Probabilities Using Bayesian Binning. | Mahdi Pakdaman Naeini, Gregory F. Cooper, Milos Hauskrecht |
| 2015 | ICDM | Missing Value Estimation for Hierarchical Time Series: A Study of Hierarchical Web Traffic. | Zitao Liu, Yan Yan, Jian Yang, Milos Hauskrecht |
| 2015 | SDM | Efficient Online Relative Comparison Kernel Learning. | Eric Heim, Matthew Berger, Lee M. Seversky, Milos Hauskrecht |
| 2015 | SDM | A Generalized Mixture Framework for Multi-label Classification. | Charmgil Hong, Iyad Batal, Milos Hauskrecht |
| 2015 | SDM | Binary Classifier Calibration Using a Bayesian Non-Parametric Approach. | Mahdi Pakdaman Naeini, Gregory F. Cooper, Milos Hauskrecht |
| 2014 | AMIA | Identifying Clinical Decision Support Failures using Change-point Detection. | Adam Wright, Francine L. Maloney, Rachel B. Ramoni, Milos Hauskrecht, Peter J. Emb, Pamela M. Neri, Dean F. Sittig, David W. Bates |
| 2014 | CIKM | A Mixtures-of-Trees Framework for Multi-Label Classification. | Charmgil Hong, Iyad Batal, Milos Hauskrecht |
| 2014 | SDM | An Optimization-based Framework to Learn Conditional Random Fields for Multi-label Classification. | Mahdi Pakdaman Naeini, Iyad Batal, Zitao Liu, Charmgil Hong, Milos Hauskrecht |
| 2013 | AAAI | Conditional Outlier Approach for Detection of Unusual Patient Care Actions. | Milos Hauskrecht, Shyam Visweswaran, Gregory F. Cooper, Gilles Clermont |
| 2013 | AIME | Clinical Time Series Prediction with a Hierarchical Dynamical System. | Zitao Liu, Milos Hauskrecht |
| 2013 | AMIA | Data-driven identification of unusual clinical actions in the ICU. | Milos Hauskrecht, Shyam Visweswaran, Gregory F. Cooper, Gilles Clermont |
| 2013 | CIKM | An efficient probabilistic framework for multi-dimensional classification. | Iyad Batal, Charmgil Hong, Milos Hauskrecht |
| 2013 | UAI | The Bregman Variational Dual-Tree Framework. | Saeed Amizadeh, Bo Thiesson, Milos Hauskrecht |
| 2013 | SDM | Modeling Clinical Time Series Using Gaussian Process Sequences. | Milos Hauskrecht, Zitao Liu, Lei Wu |
| 2012 | AMIA | Learning Medical Diagnosis Models from Multiple Experts. | Hamed Valizadegan, Quang Nguyen, Milos Hauskrecht |
| 2012 | KDD | Mining recent temporal patterns for event detection in multivariate time series data. | Iyad Batal, Dmitriy Fradkin, James H. Harrison Jr., Fabian Moerchen, Milos Hauskrecht |
| 2012 | UAI | Variational Dual-Tree Framework for Large-Scale Transition Matrix Approximation. | Saeed Amizadeh, Bo Thiesson, Milos Hauskrecht |
| 2012 | SDM | Sampling Strategies to Evaluate the Performance of Unknown Predictors. | Hamed Valizadegan, Saeed Amizadeh, Milos Hauskrecht |
| 2011 | ICDM | Learning Classification with Auxiliary Probabilistic Information. | Quang Nguyen, Hamed Valizadegan, Milos Hauskrecht |
| 2011 | ICDM | Conditional Anomaly Detection with Soft Harmonic Functions. | Michal Valko, Branislav Kveton, Hamed Valizadegan, Gregory F. Cooper, Milos Hauskrecht |
| 2011 | IJCAI | An Efficient Framework for Constructing Generalized Locally-Induced Text Metrics. | Saeed Amizadeh, Shuguang Wang, Milos Hauskrecht |
| 2011 | UIST | MARBLS: a visual environment for building clinical alert rules. | Dave Krebs, Alexander Conrad, Milos Hauskrecht, Jingtao Wang |
| 2010 | AAAI | Latent Variable Model for Learning in Pairwise Markov Networks. | Saeed Amizadeh, Milos Hauskrecht |
| 2010 | CIKM | Constructing classification features using minimal predictive patterns. | Iyad Batal, Milos Hauskrecht |
| 2010 | SIGIR | Effective query expansion with the resistance distance based term similarity metric. | Shuguang Wang, Milos Hauskrecht |
| 2009 | AMIA | A Temporal Abstraction Framework for Classifying Clinical Temporal Data. | Iyad Batal, Lucia Sacchi, Riccardo Bellazzi, Milos Hauskrecht |
| 2009 | CIKM | Boosting KNN text classification accuracy by using supervised term weighting schemes. | Iyad Batal, Milos Hauskrecht |
| 2009 | FlAIRS | Multivariate Time Series Classification with Temporal Abstractions. | Iyad Batal, Lucia Sacchi, Riccardo Bellazzi, Milos Hauskrecht |
| 2009 | FlAIRS | Improving Biomedical Document Retrieval by Mining Domain Knowledge. | Shuguang Wang, Milos Hauskrecht |
| 2009 | IC3K | Document Retrieval using a Probabilistic Knowledge Model. | Shuguang Wang, Shyam Visweswaran, Milos Hauskrecht |
| 2009 | ICMLA | A Supervised Time Series Feature Extraction Technique Using DCT and DWT. | Iyad Batal, Milos Hauskrecht |
| 2008 | FlAIRS | Distance Metric Learning for Conditional Anomaly Detection. | Michal Valko, Milos Hauskrecht |
| 2008 | ISAIM | Approximation Strategies for Routing in Stochastic Dynamic Networks. | Toms Singliar, Milos Hauskrecht |
| 2008 | SIGIR | Improving biomedical document retrieval using domain knowledge. | Shuguang Wang, Milos Hauskrecht |
| 2008 | UAI | Partitioned Linear Programming Approximations for MDPs. | Branislav Kveton, Milos Hauskrecht |
| 2007 | AMIA | Evidence-based Anomaly Detection in Clinical Domains. | Milos Hauskrecht, Michal Valko, Branislav Kveton, Shyam Visweswaran, Gregory F. Cooper |
| 2006 | AAAI | Learning Basis Functions in Hybrid Domains. | Branislav Kveton, Milos Hauskrecht |
| 2006 | ISAIM | Approximate Linear Programming for Solving Hybrid Factored MDPs. | Milos Hauskrecht |
| 2005 | IJCAI | An MCMC Approach to Solving Hybrid Factored MDPs. | Branislav Kveton, Milos Hauskrecht |
| 2005 | SDM | Variational Learning for Noisy-OR Component Analysis. | Toms Singliar, Milos Hauskrecht |
| 2004 | PSB | Modeling Cellular Processes with Variational Bayesian Cooperative Vector Quantizer. | Xinghua Lu, Milos Hauskrecht, Roger S. Day |
| 2004 | UAI | Solving Factored MDPs with Continuous and Discrete Variables. | Carlos Guestrin, Milos Hauskrecht, Branislav Kveton |
| 2003 | UAI | Monte-Carlo optimizations for resource allocation problems in stochastic network systems. | Milos Hauskrecht, Toms Singliar |
| 2001 | UAI | A Clustering Approach to Solving Large Stochastic Matching Problems. | Milos Hauskrecht, Eli Upfal |
| 1999 | IJCAI | Computing Near Optimal Strategies for Stochastic Investment Planning Problems. | Milos Hauskrecht, Gopal Pandurangan, Eli Upfal |
| 1998 | AAAI | Solving Very Large Weakly Coupled Markov Decision Processes. | Nicolas Meuleau, Milos Hauskrecht, Kee-Eung Kim, Leonid Peshkin, Leslie Pack Kaelbling, Thomas L. Dean, Craig Boutilier |
| 1998 | AMIA | Modeling treatment of ischemic heart disease with partially observable Markov decision processes. | Milos Hauskrecht, Hamish Fraser |
| 1998 | UAI | Hierarchical Solution of Markov Decision Processes using Macro-actions. | Milos Hauskrecht, Nicolas Meuleau, Leslie Pack Kaelbling, Thomas L. Dean, Craig Boutilier |
| 1997 | AAAI | Incremental Methods for Computing Bounds in Partially Observable Markov Decision Processes. | Milos Hauskrecht |
| 1997 | AIME | Dynamic Decision Making in Stochastic Partially Observable Domains: Ischemic Heart Disease Example. | Milos Hauskrecht |