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ORCIDArtur Dubrawski
Artur W. Dubrawski
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- affiliation: Carnegie Mellon University, Pittsburgh, USA
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2020 – today
- 2024
[j18]Benedikt Boecking
, Vincent Jeanselme, Artur Dubrawski:
Constrained clustering and multiple kernel learning without pairwise constraint relaxation. Adv. Data Anal. Classif. 18(2): 309-324 (2024)- [c85]Yifu Cai, Arvind Srinivasan, Mononito Goswami, Arjun Choudhry, Artur Dubrawski:
JoLT: Jointly Learned Representations of Language and Time-Series for Clinical Time-Series Interpretation (Student Abstract). AAAI 2024: 23447-23448 - [c84]Angela Chen, Nicholas Gisolfi, Artur Dubrawski:
Data-Driven Discovery of Design Specifications (Student Abstract). AAAI 2024: 23449-23450 - [c83]Eric Enouen, Sebastian Caldas, Mononito Goswami, Artur Dubrawski:
PICSR: Prototype-Informed Cross-Silo Router for Federated Learning (Student Abstract). AAAI 2024: 23482-23483 - [c82]Ryan Schuerkamp, Xinyu Li, Brian Kunzer, Leonard S. Weiss, Hernando Gómez, Francis X. Guyette, Michael R. Pinsky, Artur Dubrawski:
Adapting Animal Models to Assess Sufficiency of Fluid Resuscitation in Humans (Student Abstract). AAAI 2024: 23644-23646 - [c81]Raghavv Goel, Cecilia G. Morales, Manpreet Singh, Artur Dubrawski, Jonh Galeotti, Howie Choset:
Motion-aware Needle Segmentation in Ultrasound Images. CVPR Workshops 2024: 7886-7891 - [c80]Lukasz Sztukiewicz, Jack Henry Good, Artur Dubrawski:
Exploring Loss Design Techniques For Decision Tree Robustness To Label Noise. Tiny Papers @ ICLR 2024 - [c79]Ifigeneia Apostolopoulou, Benjamin Eysenbach, Frank Nielsen, Artur Dubrawski:
A Rate-Distortion View of Uncertainty Quantification. ICML 2024 - [c78]Mononito Goswami, Konrad Szafer, Arjun Choudhry, Yifu Cai, Shuo Li, Artur Dubrawski:
MOMENT: A Family of Open Time-series Foundation Models. ICML 2024 - [c77]Raghavv Goel, Cecilia G. Morales, Manpreet Singh, Artur Dubrawski, John M. Galeotti, Howie Choset:
Motion-Aware Needle Segmentation in Ultrasound Images. ISBI 2024: 1-4 - [c76]Rohini Banerjee, Cecilia G. Morales, Artur Dubrawski:
Enhanced Uncertainty Estimation in Ultrasound Image Segmentation with MSU-Net. ASMUS@MICCAI 2024: 143-153 - [i57]Chufan Gao, Nicholas Gisolfi, Artur Dubrawski:
Signal Quality Auditing for Time-series Data. CoRR abs/2402.00803 (2024) - [i56]Mononito Goswami, Konrad Szafer, Arjun Choudhry, Yifu Cai, Shuo Li, Artur Dubrawski:
MOMENT: A Family of Open Time-series Foundation Models. CoRR abs/2402.03885 (2024) - [i55]Lukasz Sztukiewicz, Jack Henry Good, Artur Dubrawski:
Exploring Loss Design Techniques For Decision Tree Robustness To Label Noise. CoRR abs/2405.17672 (2024) - [i54]Ifigeneia Apostolopoulou, Benjamin Eysenbach, Frank Nielsen, Artur Dubrawski:
A Rate-Distortion View of Uncertainty Quantification. CoRR abs/2406.10775 (2024) - [i53]Rohini Banerjee, Cecilia G. Morales, Artur Dubrawski:
Enhanced Uncertainty Estimation in Ultrasound Image Segmentation with MSU-Net. CoRR abs/2407.21273 (2024) - [i52]Ignacy Stepka, Nicholas Gisolfi, Artur Dubrawski:
A SAT-based approach to rigorous verification of Bayesian networks. CoRR abs/2408.00986 (2024) - [i51]Cecilia G. Morales, Dhruv Srikanth, Jack H. Good, Keith Dufendach, Artur Dubrawski:
Bifurcation Identification for Ultrasound-driven Robotic Cannulation. CoRR abs/2409.06817 (2024) - [i50]Willa Potosnak, Cristian Challu, Mononito Goswami, Michal Wilinski, Nina Zukowska, Artur Dubrawski:
Implicit Reasoning in Deep Time Series Forecasting. CoRR abs/2409.10840 (2024) - [i49]Michal Wilinski, Mononito Goswami, Nina Zukowska, Willa Potosnak, Artur Dubrawski:
Unveiling and Manipulating Concepts in Time Series Foundation Models. CoRR abs/2409.12915 (2024) - [i48]Nina Zukowska, Mononito Goswami, Michal Wilinski, Willa Potosnak, Artur Dubrawski:
Towards Long-Context Time Series Foundation Models. CoRR abs/2409.13530 (2024) - 2023
- [j17]Piotr S. Maciag, Robert Bembenik, Artur Dubrawski:
Discovery of crime event sequences with constricted spatio-temporal sequential patterns. J. Big Data 10(1): 98 (2023) - [j16]Jack H. Good, Nicholas Gisolfi, James Kyle Miller, Artur Dubrawski:
Verification of Fuzzy Decision Trees. IEEE Trans. Software Eng. 49(5): 3277-3288 (2023) - [c75]Cristian Challu, Kin G. Olivares, Boris N. Oreshkin, Federico Garza Ramírez, Max Mergenthaler Canseco, Artur Dubrawski:
NHITS: Neural Hierarchical Interpolation for Time Series Forecasting. AAAI 2023: 6989-6997 - [c74]Prakruthi Pradeep, Benedikt Boecking, Nicholas Gisolfi, Jacob R. Kintz, Torin K. Clark, Artur Dubrawski:
Ordinal Programmatic Weak Supervision and Crowdsourcing for Estimating Cognitive States (Student Abstract). AAAI 2023: 16304-16305 - [c73]Benedikt Boecking, Nicholas Carl Roberts, Willie Neiswanger, Stefano Ermon, Frederic Sala, Artur Dubrawski:
Generative Modeling Helps Weak Supervision (and Vice Versa). ICLR 2023 - [c72]Cecilia G. Morales, Jason Yao, Tejas Rane, Robert Edman, Howie Choset, Artur Dubrawski:
Reslicing Ultrasound Images for Data Augmentation and Vessel Reconstruction. ICRA 2023: 2710-2716 - [c71]Jack H. Good, Torin Kovach, Kyle Miller, Artur Dubrawski:
Feature Learning for Interpretable, Performant Decision Trees. NeurIPS 2023 - [c70]Mononito Goswami, Vedant Sanil, Arjun Choudhry, Arvind Srinivasan, Chalisa Udompanyawit, Artur Dubrawski:
AQuA: A Benchmarking Tool for Label Quality Assessment. NeurIPS 2023 - [i47]Cecilia G. Morales, Jason Yao, Tejas Rane, Robert Edman, Howie Choset, Artur Dubrawski:
Reslicing Ultrasound Images for Data Augmentation and Vessel Reconstruction. CoRR abs/2301.07286 (2023) - [i46]Chirag Nagpal, Vedant Sanil, Artur Dubrawski:
Recovering Sparse and Interpretable Subgroups with Heterogeneous Treatment Effects with Censored Time-to-Event Outcomes. CoRR abs/2302.12504 (2023) - [i45]Kin G. Olivares, David Luo, Cristian Challu, Stefania La Vattiata, Max Mergenthaler, Artur Dubrawski:
HINT: Hierarchical Mixture Networks For Coherent Probabilistic Forecasting. CoRR abs/2305.07089 (2023) - [i44]Mononito Goswami, Vedant Sanil, Arjun Choudhry, Arvind Srinivasan, Chalisa Udompanyawit, Artur Dubrawski:
AQuA: A Benchmarking Tool for Label Quality Assessment. CoRR abs/2306.09467 (2023) - [i43]Willa Potosnak, Cristian Challu, Kin G. Olivares, Artur Dubrawski:
Forecasting Response to Treatment with Deep Learning and Pharmacokinetic Priors. CoRR abs/2309.13135 (2023) - [i42]Raghavv Goel, Cecilia G. Morales, Manpreet Singh, Artur Dubrawski, John M. Galeotti, Howie Choset:
Motion Informed Needle Segmentation in Ultrasound Images. CoRR abs/2312.01239 (2023) - 2022
- [j15]Stephanie Helman, Martha Ann Terry, Tiffany Pellathy, Andrew Williams, Artur Dubrawski, Gilles Clermont, Michael R. Pinsky, Salah Al-Zaiti, Marilyn Hravnak:
Engaging clinicians early during the development of a graphical user display of an intelligent alerting system at the bedside. Int. J. Medical Informatics 159: 104643 (2022) - [j14]Xinyu Li, Michael R. Pinsky, Artur Dubrawski:
Automated Assessment of Cardiovascular Sufficiency Using Non-Invasive Physiological Data. Sensors 22(3): 1024 (2022) - [j13]Michael R. Pinsky, Artur Dubrawski, Gilles Clermont:
Intelligent Clinical Decision Support. Sensors 22(4): 1408 (2022) - [c69]Cecilia G. Morales, Nicholas Gisolfi, Robert Edman, James Kyle Miller, Artur Dubrawski:
Actionable Model-Centric Explanations (Student Abstract). AAAI 2022: 13019-13020 - [c68]Arnab Dey, Mononito Goswami, Joo Heung Yoon, Gilles Clermont, Michael R. Pinsky, Marilyn Hravnak, Artur Dubrawski:
Weakly Supervised Classification of Vital Sign Alerts as Real or Artifact. AMIA 2022 - [c67]Ifigeneia Apostolopoulou, Ian Char, Elan Rosenfeld, Artur Dubrawski:
Deep Attentive Variational Inference. ICLR 2022 - [c66]Chirag Nagpal, Mononito Goswami, Keith Dufendach, Artur Dubrawski:
Counterfactual Phenotyping with Censored Time-to-Events. KDD 2022: 3634-3644 - [c65]Chirag Nagpal, Willa Potosnak, Artur Dubrawski:
auton-survival: an Open-Source Package for Regression, Counterfactual Estimation, Evaluation and Phenotyping with Censored Time-to-Event Data. MLHC 2022: 585-608 - [c64]Chufan Gao, Mononito Goswami, Jieshi Chen, Artur Dubrawski:
Classifying Unstructured Clinical Notes via Automatic Weak Supervision. MLHC 2022: 673-690 - [i41]Mononito Goswami, Benedikt Boecking, Artur Dubrawski:
Weak Supervision for Affordable Modeling of Electrocardiogram Data. CoRR abs/2201.02936 (2022) - [i40]Cristian Challu, Kin G. Olivares, Boris N. Oreshkin, Federico Garza, Max Mergenthaler, Artur Dubrawski:
N-HiTS: Neural Hierarchical Interpolation for Time Series Forecasting. CoRR abs/2201.12886 (2022) - [i39]Chirag Nagpal, Mononito Goswami, Keith Dufendach, Artur Dubrawski:
Counterfactual Phenotyping with Censored Time-to-Events. CoRR abs/2202.11089 (2022) - [i38]Benedikt Boecking, Willie Neiswanger, Nicholas Carl Roberts, Stefano Ermon, Frederic Sala, Artur Dubrawski:
Generative Modeling Helps Weak Supervision (and Vice Versa). CoRR abs/2203.12023 (2022) - [i37]Benedikt Boecking, Vincent Jeanselme, Artur Dubrawski:
Constrained Clustering and Multiple Kernel Learning without Pairwise Constraint Relaxation. CoRR abs/2203.12546 (2022) - [i36]Chirag Nagpal, Willa Potosnak, Artur Dubrawski:
auton-survival: an Open-Source Package for Regression, Counterfactual Estimation, Evaluation and Phenotyping with Censored Time-to-Event Data. CoRR abs/2204.07276 (2022) - [i35]Maria De-Arteaga, Alexandra Chouldechova, Artur Dubrawski:
Doubting AI Predictions: Influence-Driven Second Opinion Recommendation. CoRR abs/2205.00072 (2022) - [i34]Arnab Dey, Mononito Goswami, Joo Heung Yoon, Gilles Clermont, Michael R. Pinsky, Marilyn Hravnak, Artur Dubrawski:
Weakly Supervised Classification of Vital Sign Alerts as Real or Artifact. CoRR abs/2206.09074 (2022) - [i33]Brian Kunzer, Mario Berges, Artur Dubrawski:
The Digital Twin Landscape at the Crossroads of Predictive Maintenance, Machine Learning and Physics Based Modeling. CoRR abs/2206.10462 (2022) - [i32]Chufan Gao, Mononito Goswami, Jieshi Chen, Artur Dubrawski:
Classifying Unstructured Clinical Notes via Automatic Weak Supervision. CoRR abs/2206.12088 (2022) - [i31]Kin G. Olivares, Federico Garza, David Luo, Cristian Challu, Max Mergenthaler, Artur Dubrawski:
HierarchicalForecast: A Reference Framework for Hierarchical Forecasting in Python. CoRR abs/2207.03517 (2022) - 2021
- [j12]Chirag Nagpal, Xinyu Li, Artur Dubrawski:
Deep Survival Machines: Fully Parametric Survival Regression and Representation Learning for Censored Data With Competing Risks. IEEE J. Biomed. Health Informatics 25(8): 3163-3175 (2021) - [c63]Sebastian Caldas, Jieshi Chen, Artur Dubrawski:
Using Machine Learning to Support Transfer of Best Practices in Healthcare. AMIA 2021 - [c62]Mononito Goswami, Benedikt Boecking, Artur Dubrawski:
Weak Supervision for Affordable Modeling of Electrocardiogram Data. AMIA 2021 - [c61]Lujie Karen Chen, Joseph D. Ramsey, Artur Dubrawski:
Affect, Support and Personal Factors: Multimodal Causal Models of One-on-one Coaching. EDM 2021 - [c60]Benedikt Boecking, Willie Neiswanger, Eric P. Xing, Artur Dubrawski:
Interactive Weak Supervision: Learning Useful Heuristics for Data Labeling. ICLR 2021 - [c59]Sebastian Caldas, Joo Heung Yoon, Michael R. Pinsky, Gilles Clermont, Artur Dubrawski:
Understanding Clinical Collaborations Through Federated Classifier Selection. MLHC 2021: 126-145 - [c58]Salva Rühling Cachay, Benedikt Boecking, Artur Dubrawski:
End-to-End Weak Supervision. NeurIPS 2021: 1845-1857 - [c57]Chirag Nagpal, Vincent Jeanselme, Artur Dubrawski:
Deep Parametric Time-to-Event Regression with Time-Varying Covariates. SPACA 2021: 184-193 - [i30]Maria De-Arteaga, Artur Dubrawski, Alexandra Chouldechova:
Leveraging Expert Consistency to Improve Algorithmic Decision Support. CoRR abs/2101.09648 (2021) - [i29]Kin G. Olivares, Cristian Challu, Grzegorz Marcjasz, Rafal Weron, Artur Dubrawski:
Neural basis expansion analysis with exogenous variables: Forecasting electricity prices with NBEATSx. CoRR abs/2104.05522 (2021) - [i28]Cristian Challu, Kin G. Olivares, Gus Welter, Artur Dubrawski:
DMIDAS: Deep Mixed Data Sampling Regression for Long Multi-Horizon Time Series Forecasting. CoRR abs/2106.05860 (2021) - [i27]Salva Rühling Cachay, Benedikt Boecking, Artur Dubrawski:
Dependency Structure Misspecification in Multi-Source Weak Supervision Models. CoRR abs/2106.10302 (2021) - [i26]Salva Rühling Cachay, Benedikt Boecking, Artur Dubrawski:
End-to-End Weak Supervision. CoRR abs/2107.02233 (2021) - [i25]Cecilia G. Morales, Nicholas Gisolfi, Robert Edman, James Kyle Miller, Artur Dubrawski:
Provably Robust Model-Centric Explanations for Critical Decision-Making. CoRR abs/2110.13937 (2021) - [i24]Piotr S. Maciag, Robert Bembenik, Artur Dubrawski:
Discovery of Crime Event Sequences with Constricted Spatio-Temporal Sequential Patterns. CoRR abs/2112.01863 (2021) - 2020
- [j11]Yichong Xu, Sivaraman Balakrishnan, Aarti Singh, Artur Dubrawski:
Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information. J. Mach. Learn. Res. 21: 162:1-162:54 (2020) - [c56]Mononito Goswami, Lujie Chen, Artur Dubrawski:
Discriminating Cognitive Disequilibrium and Flow in Problem Solving: A Semi-Supervised Approach Using Involuntary Dynamic Behavioral Signals. AAAI 2020: 420-427 - [c55]Mononito Goswami, Lujie Chen, Chufan Gao, Artur Dubrawski:
Modeling Involuntary Dynamic Behaviors to Support Intelligent Tutoring (Student Abstract). AAAI 2020: 13799-13800 - [c54]Sibi Venkatesan, James Kyle Miller, Artur Dubrawski:
Robust Multi-View Representation Learning (Student Abstract). AAAI 2020: 13939-13940 - [c53]Yichong Xu, Xi Chen, Aarti Singh, Artur Dubrawski:
Thresholding Bandit Problem with Both Duels and Pulls. AISTATS 2020: 2591-2600 - [c52]Chao Liu, Akash K. Maity, Artur W. Dubrawski, Ashutosh Sabharwal, Srinivasa G. Narasimhan:
High Resolution Diffuse Optical Tomography using Short Range Indirect Subsurface Imaging. ICCP 2020: 1-12 - [c51]Yichong Xu, Ruosong Wang, Lin F. Yang, Aarti Singh, Artur Dubrawski:
Preference-based Reinforcement Learning with Finite-Time Guarantees. NeurIPS 2020 - [c50]Yichong Xu, Aparna Joshi, Aarti Singh, Artur Dubrawski:
Zeroth Order Non-convex optimization with Dueling-Choice Bandits. UAI 2020: 899-908 - [i23]Chirag Nagpal, Xinyu Li, Artur Dubrawski:
Deep Survival Machines: Fully Parametric Survival Regression and Representation Learning for Censored Data with Competing Risks. CoRR abs/2003.01176 (2020) - [i22]Kyle Miller, Artur Dubrawski:
System-Level Predictive Maintenance: Review of Research Literature and Gap Analysis. CoRR abs/2005.05239 (2020) - [i21]Yichong Xu, Ruosong Wang, Lin F. Yang, Aarti Singh, Artur Dubrawski:
Preference-based Reinforcement Learning with Finite-Time Guarantees. CoRR abs/2006.08910 (2020) - [i20]Ifigeneia Apostolopoulou, Elan Rosenfeld, Artur Dubrawski:
Self-Reflective Variational Autoencoder. CoRR abs/2007.05166 (2020) - [i19]Benedikt Boecking, Willie Neiswanger, Eric Poe Xing, Artur Dubrawski:
Interactive Weak Supervision: Learning Useful Heuristics for Data Labeling. CoRR abs/2012.06046 (2020)
2010 – 2019
- 2019
- [j10]James Kyle Miller, Jieshi Chen, Alexander Sundermann, Jane W. Marsh, Melissa I. Saul, Kathleen A. Shutt, Marissa Pacey, Mustapha M. Mustapha, Lee H. Harrison, Artur Dubrawski:
Statistical outbreak detection by joining medical records and pathogen similarity. J. Biomed. Informatics 91 (2019) - [c49]Matt Barnes, Artur Dubrawski:
On the Interaction Effects Between Prediction and Clustering. AISTATS 2019: 118-126 - [c48]Lujie Chen, Eva Gjekmarkaj, Artur Dubrawski:
Parent as a Companion for Solving Challenging Math Problems: Insights from Multi-modal Observational Data. EDM 2019 - [c47]David Bethge, Jieshi Chen, Oliver Grothe, Jonathan Elmer, Artur Dubrawski:
Prognostication of Neurological Recovery by Analyzing Structural Breaks in EEG Data. ICDM Workshops 2019: 933-940 - [c46]Chirag Nagpal, Xinyu Li, Michael R. Pinsky, Artur Dubrawski:
Dynamically Personalized Detection of Hemorrhage. MLHC 2019: 109-123 - [c45]Ifigeneia Apostolopoulou, Scott W. Linderman, Kyle Miller, Artur Dubrawski:
Mutually Regressive Point Processes. NeurIPS 2019: 5116-5127 - [i18]Chirag Nagpal, Rohan Sangave, Amit Chahar, Parth Shah, Artur Dubrawski, Bhiksha Raj:
Nonlinear Semi-Parametric Models for Survival Analysis. CoRR abs/1905.05865 (2019) - [i17]Yichong Xu, Xi Chen, Aarti Singh, Artur Dubrawski:
Thresholding Bandit Problem with Both Duels and Pulls. CoRR abs/1910.06368 (2019) - [i16]Yuexin Wu, Yichong Xu, Aarti Singh, Yiming Yang, Artur Dubrawski:
Active Learning for Graph Neural Networks via Node Feature Propagation. CoRR abs/1910.07567 (2019) - [i15]Yichong Xu, Aparna Joshi, Aarti Singh, Artur Dubrawski:
Zeroth Order Non-convex optimization with Dueling-Choice Bandits. CoRR abs/1911.00980 (2019) - [i14]Chufan Gao, Fabian Falck, Mononito Goswami, Anthony Wertz, Michael R. Pinsky, Artur Dubrawski:
Detecting Patterns of Physiological Response to Hemodynamic Stress via Unsupervised Deep Learning. CoRR abs/1911.05121 (2019) - [i13]Benedikt Boecking, Artur Dubrawski:
Pairwise Feedback for Data Programming. CoRR abs/1912.07685 (2019) - 2018
- [j9]Maria De-Arteaga, William Herlands, Daniel B. Neill, Artur Dubrawski:
Machine Learning for the Developing World. ACM Trans. Manag. Inf. Syst. 9(2): 9:1-9:14 (2018) - [c44]Nick Gisolfi, Artur Dubrawski:
Revealing Actionable Simplicity in Data. AAAI Spring Symposia 2018 - [c43]Yichong Xu, Sivaraman Balakrishnan, Aarti Singh, Artur Dubrawski:
Interactive Linear Regression with Pairwise Comparisons. ACSSC 2018: 636-640 - [c42]Chao Liu, Srinivasa G. Narasimhan, Artur W. Dubrawski:
Near-light photometric stereo using circularly placed point light sources. ICCP 2018: 1-10 - [c41]Yichong Xu, Hariank Muthakana, Sivaraman Balakrishnan, Aarti Singh, Artur Dubrawski:
Nonparametric Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information. ICML 2018: 5469-5478 - [c40]Reihaneh Rabbany, David Bayani, Artur Dubrawski:
Active Search of Connections for Case Building and Combating Human Trafficking. KDD 2018: 2120-2129 - [c39]Lujie Chen, Artur Dubrawski:
Accelerated apprenticeship: teaching data science problem solving skills at scale. L@S 2018: 39:1-39:4 - [c38]Dhivya Eswaran, Reihaneh Rabbany, Artur W. Dubrawski, Christos Faloutsos:
Social-Affiliation Networks: Patterns and the SOAR Model. ECML/PKDD (2) 2018: 105-121 - [i12]Igor Gitman, Jieshi Chen, Eric Lei, Artur Dubrawski:
Novel Prediction Techniques Based on Clusterwise Linear Regression. CoRR abs/1804.10742 (2018) - [i11]Yichong Xu, Hariank Muthakana, Sivaraman Balakrishnan, Aarti Singh, Artur Dubrawski:
Nonparametric Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information. CoRR abs/1806.03286 (2018) - [i10]Maria De-Arteaga, Artur Dubrawski, Alexandra Chouldechova:
Learning under selective labels in the presence of expert consistency. CoRR abs/1807.00905 (2018) - [i9]Matt Barnes, Artur Dubrawski:
Dependency Leakage: Analysis and Scalable Estimators. CoRR abs/1807.06713 (2018) - [i8]Kin Gutierrez, Jin Li, Cristian Challu, Artur Dubrawski:
Double Adaptive Stochastic Gradient Optimization. CoRR abs/1811.02525 (2018) - 2017
- [j8]Mathieu Guillame-Bert, Artur Dubrawski, Donghan Wang, Marilyn Hravnak, Gilles Clermont, Michael R. Pinsky:
Learning temporal rules to forecast instability in continuously monitored patients. J. Am. Medical Informatics Assoc. 24(1): 47-53 (2017) - [j7]Mathieu Guillame-Bert, Artur Dubrawski:
Classification of Time Sequences using Graphs of Temporal Constraints. J. Mach. Learn. Res. 18: 121:1-121:34 (2017) - [c37]Chirag Nagpal, Kyle Miller, Benedikt Boecking, Artur Dubrawski:
An Entity Resolution Approach to Isolate Instances of Human Trafficking Online. NUT@EMNLP 2017: 77-84 - [c36]Xuan Wang, Lujie Chen, Marilyn Hravnak, Gilles Clermont, Michael R. Pinsky, Artur Dubrawski:
Utility of Anti-hypertension Prescription Orders in Predicting Future Hypertensive Instability Events. AMIA 2017 - [c35]Chao Liu, Srinivasa G. Narasimhan, Artur W. Dubrawski:
Matting and Depth Recovery of Thin Structures Using a Focal Stack. CVPR 2017: 4782-4790 - [c34]Chirag Nagpal, Kyle Miller, Tiffany Pellathy, Marilyn Hravnak, Gilles Clermont, Michael R. Pinsky, Artur Dubrawski:
Semi-Supervised Prediction of Comorbid Rare Conditions Using Medical Claims Data. ICDM Workshops 2017: 478-485 - [c33]Sibi Venkatesan, James Kyle Miller, Jeff Schneider, Artur Dubrawski:
Scaling Active Search using Linear Similarity Functions. IJCAI 2017: 2878-2884 - [c32]Lujie Chen, Artur Dubrawski:
Learning from learning curves: discovering interpretable learning trajectories. LAK 2017: 544-545 - [c31]Yichong Xu, Hongyang Zhang, Aarti Singh, Artur Dubrawski, Kyle Miller:
Noise-Tolerant Interactive Learning Using Pairwise Comparisons. NIPS 2017: 2431-2440 - [c30]Reihaneh Rabbany, Dhivya Eswaran, Artur W. Dubrawski, Christos Faloutsos:
Beyond Assortativity: Proclivity Index for Attributed Networks (ProNe). PAKDD (1) 2017: 225-237 - [c29]Matt Barnes, Artur Dubrawski:
The Binomial Block Bootstrap Estimator for Evaluating Loss on Dependent Clusters. UAI 2017 - [i7]Sibi Venkatesan, James Kyle Miller, Jeff Schneider, Artur Dubrawski:
Scaling Active Search using Linear Similarity Functions. CoRR abs/1705.00334 (2017) - [i6]Eric Lei, Kyle Miller, Artur Dubrawski:
Learning Mixtures of Multi-Output Regression Models by Correlation Clustering for Multi-View Data. CoRR abs/1709.05602 (2017) - 2016
- [j6]Prateek Tandon, Peter Huggins, Robert A. MacLachlan, Artur Dubrawski, Karl Nelson, Simon Labov:
Detection of radioactive sources in urban scenes using Bayesian Aggregation of data from mobile spectrometers. Inf. Syst. 57: 195-206 (2016) - [c28]Lujie Chen, Gilles Clermont, Marilyn Hravnak, Michael R. Pinsky, Artur Dubrawski:
A Framework for Visual Tracking of Risk and its Drivers in Monitoring Patients Susceptible for Cardiorespiratory Instability. AMIA 2016 - [c27]Lujie Chen, Xin Li, Zhuyun Xia, Zhanmei Song, Louis-Philippe Morency, Artur Dubrawski:
Riding an emotional roller-coaster: A multimodal study of young child's math problem solving activities. EDM 2016: 38-45 - [c26]Donghan Wang, Madalina Fiterau, Artur Dubrawski:
VIPR: An Interactive Tool for Meaningful Visualization of High-Dimensional Data. IJCAI 2016: 4274-4275 - [c25]Reuben M. Aronson, Ankit Bhatia, Zhenzhong Jia, Mathieu Guillame-Bert, David A. Bourne, Artur Dubrawski, Matthew T. Mason:
Data-Driven Classification of Screwdriving Operations. ISER 2016: 244-253 - [i5]Mathieu Guillame-Bert, Artur Dubrawski:
Batched Lazy Decision Trees. CoRR abs/1603.02578 (2016) - [i4]Prateek Tandon, Peter Huggins, Artur Dubrawski, Simon Labov, Karl Nelson:
Suppressing Background Radiation Using Poisson Principal Component Analysis. CoRR abs/1605.08455 (2016) - 2015
- [c24]Matt Barnes, Nick Gisolfi, Madalina Fiterau, Artur Dubrawski:
Leveraging Common Structure to Improve Prediction across Related Datasets. AAAI 2015: 4144-4145 - [c23]Madalina Fiterau, Artur Dubrawski:
Active Learning for Informative Projection Retrieval. AAAI 2015: 4158-4159 - [c22]Nick Gisolfi, Madalina Fiterau, Artur Dubrawski:
Finding Meaningful Gaps to Guide Data Acquisition for a Radiation Adjudication System. AAAI 2015: 4164-4165 - [c21]Lujie Chen, Artur Dubrawski, Marilyn Hravnak, Gilles Clermont, Michael R. Pinsky:
Modelling Risk of Cardio-Respiratory Instability as a Heterogeneous Process. AMIA 2015 - [c20]Chao Liu, Hernando Gomez, Srinivasa G. Narasimhan, Artur Dubrawski, Michael R. Pinsky, Brian Zuckerbraun:
Real-time visual analysis of microvascular blood flow for critical care. CVPR 2015: 2217-2225 - [i3]Matt Barnes, Kyle Miller, Artur Dubrawski:
Performance Bounds for Pairwise Entity Resolution. CoRR abs/1509.03302 (2015) - [i2]Chirag Nagpal, Kyle Miller, Benedikt Boecking, Artur Dubrawski:
An Entity Resolution approach to isolate instances of Human Trafficking online. CoRR abs/1509.06659 (2015) - [i1]Maria De-Arteaga, Artur Dubrawski, Peter Huggins:
Canonical Autocorrelation Analysis. CoRR abs/1511.06419 (2015) - 2013
- [c19]Madalina Fiterau, Artur Dubrawski:
Informative Projection Recovery for Classification, Clustering and Regression. ICMLA (1) 2013: 15-20 - 2012
- [c18]Madalina Fiterau, Artur Dubrawski:
Projection Retrieval for Classification. NIPS 2012: 3032-3040 - 2011
- [j5]Nuwan Waidyanatha, Artur Dubrawski, M. Ganesan, Gordon A. Gow:
Affordable System for Rapid Detection and Mitigation of Emerging Diseases. Int. J. E Health Medical Commun. 2(1): 73-90 (2011) - 2010
- [j4]Artur Dubrawski, John Östlund, Lujie Chen, Andrew W. Moore:
Computationally efficient scoring of activity using demographics and connectivity of entities. Inf. Technol. Manag. 11(2): 77-89 (2010) - [c17]Julian Ramos, Sajid M. Siddiqi, Artur Dubrawski, Geoffrey J. Gordon, Abhishek Sharma:
Automatic state discovery for unstructured audio scene classification. ICASSP 2010: 2154-2157 - [c16]Nuwan Waidyanatha, Chamindu Sampath, Artur Dubrawski, Maheshkumar Sabhnani, Lujie Chen, M. Ganesan, Pushpa Mary Vincy:
T-Cube Web Interface as a Tool for Detecting Disease Outbreaks in Real-Time: A Pilot in India and Sri Lanka. RIVF 2010: 1-4 - [c15]Yi Zhang, Jeff G. Schneider, Artur Dubrawski:
Learning Compressible Models. SDM 2010: 872-881
2000 – 2009
- 2009
- [c14]Artur Dubrawski, Purnamrita Sarkar, Lujie Chen:
Trade-offs between Agility and Reliability of Predictions in Dynamic Social Networks Used to Model Risk of Microbial Contamination of Food. ASONAM 2009: 125-130 - [c13]Artur Dubrawski, Maheshkumar Sabhnani, Michael Knight, Michael Baysek, Daniel B. Neill, Saswati Ray, Anna Michalska, Nuwan Waidyanatha:
T-Cube Web Interface in support of real-time bio-surveillance program. ICTD 2009: 495 - 2008
- [c12]Josep Roure, Artur Dubrawski, Jeff G. Schneider:
Learning Detectors of Events in Multivariate Time Series. AMIA 2008 - [c11]Purnamrita Sarkar, Lujie Chen, Artur Dubrawski:
Dynamic Network Model for Predicting Occurrences of Salmonella at Food Facilities. BioSecure 2008: 56-63 - [c10]Yi Zhang, Jeff G. Schneider, Artur Dubrawski:
Learning the Semantic Correlation: An Alternative Way to Gain from Unlabeled Text. NIPS 2008: 1945-1952 - 2007
- [c9]Artur Dubrawski, Michael Baysek, Shannon Mikus, Charles McDaniel, Bradley Mowry, Laurel Moyer, John Östlund, Norman K. Sondheimer, Timothy Stewart:
Applying Outbreak Detection Algorithms to Prognostics. AAAI Fall Symposium: Artificial Intelligence for Prognostics 2007: 36-43 - [c8]Josep Roure, Artur Dubrawski, Jeff G. Schneider:
A Study into Detection of Bio-Events in Multiple Streams of Surveillance Data. BioSurveillance 2007: 124-133 - 2006
- [c7]Artur Dubrawski, Kimberly Elenberg, Andrew W. Moore, Maheshkumar Sabhnani:
Monitoring Food Safety by Detecting Patterns in Consumer Complaints. AAAI 2006: 1782-1788
1990 – 1999
- 1998
- [c6]Artur Dubrawski, Barbara Siemiatkowska:
A Method for Tracking Pose of a Mobile Robot Equipped with a Scanning Laser Range Finder. ICRA 1998: 2518-2523 - [c5]Barbara Siemiatkowska, Artur Dubrawski:
Cellular Neural Networks for Navigation of a Mobile Robot. Rough Sets and Current Trends in Computing 1998: 147-154 - 1997
- [j3]Artur Dubrawski:
Stochastic validation for automated tuning of neural network's hyper-parameters. Robotics Auton. Syst. 21(1): 83-93 (1997) - [c4]Artur Dubrawski, Jeff Schneider:
Memory Based Stochastic Optimization for Validation and Tuning of Function Approximators. AISTATS 1997: 165-172 - [c3]Artur Dubrawski:
Tuning neural networks with stochastic optimization. IROS 1997: 614-620 - 1995
- [j2]Janusz W. Racz, Artur Dubrawski:
Artificial neural network for mobile robot topological localization. Robotics Auton. Syst. 16(1): 73-80 (1995) - 1994
- [j1]Artur Dubrawski, James L. Crowley:
Learning locomotion reflexes: A self-supervised neural system for a mobile robot. Robotics Auton. Syst. 12(3-4): 133-142 (1994) - [c2]Artur Dubrawski, James L. Crowley:
Self-Supervised Neural System for Reactive Navigation. ICRA 1994: 2076-2082 - [c1]Artur Dubrawski, Patrick Reignier:
Learning to categorize perceptual space of a mobile robot using fuzzy-ART neural network. IROS 1994: 1272-1277
Coauthor Index
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