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2020 – today
- 2024
[c43]Xi Yang, Paulito Palmes, Saurabh Jha, Bekir O. Turkkan, Gerard Vanloo, Frank Bagehorn, Chandra Narayanaswami, Larisa Shwartz, Naoki Abe, Yu Deng, Daby M. Sow:
SAM: Subseries Augmentation-Based Meta-Learning for Generalizing AIOps Models in Multi-Cloud Migration. CLOUD 2024: 291-301- [c42]Xi Yang, Rohan R. Arora, Saurabh Jha, Chandra Narayanaswami, Cheuk Lam, Jerrold Leichter, Yu Deng, Daby M. Sow:
Optimizing IT FinOps and Sustainability through Unsupervised Workload Characterization. AAAI 2024: 22990-22996 - 2023
- [j11]Zijun Yao
, Bin Liu, Fei Wang, Daby Sow, Ying Li:
Ontology-aware Prescription Recommendation in Treatment Pathways Using Multi-evidence Healthcare Data. ACM Trans. Inf. Syst. 41(4): 99:1-99:29 (2023) - 2022
- [j10]Sanjoy Dey, Prithwish Chakraborty, Bum Chul Kwon, Amit Dhurandhar, Mohamed F. Ghalwash, Fernando J. Suarez Saiz, Kenney Ng, Daby Sow, Kush R. Varshney, Pablo Meyer:
Human-centered explainability for life sciences, healthcare, and medical informatics. Patterns 3(5): 100493 (2022) - [c41]Bekir Oguzhan Turkkan, Ting Dai, Adithya Raman, Tevfik Kosar, Changyou Chen, Muhammed Fatih Bulut, Jaroslaw Zola, Daby Sow:
GreenABR: energy-aware adaptive bitrate streaming with deep reinforcement learning. MMSys 2022: 150-163 - [i11]Constantin Adam, Muhammed Fatih Bulut, Daby Sow, Steven Ocepek, Chris Bedell, Lilian Ngweta:
Attack Techniques and Threat Identification for Vulnerabilities. CoRR abs/2206.11171 (2022) - [i10]Muhammed Fatih Bulut, Abdulhamid Adebayo, Daby Sow, Steve Ocepek:
Vulnerability Prioritization: An Offensive Security Approach. CoRR abs/2206.11182 (2022) - [i9]Abdulhamid Adebayo, Daby Sow, Muhammed Fatih Bulut:
Automated Compliance Blueprint Optimization with Artificial Intelligence. CoRR abs/2206.11187 (2022) - 2021
- [j9]Zefang Tang, Yiqin Yu, Kenney Ng, Daby Sow, Jianying Hu, Jing Mei:
Disease network delineates the disease progression profile of cardiovascular diseases. J. Biomed. Informatics 115: 103686 (2021) - [c40]Shruthi Chari, Prithwish Chakraborty, Oshani Seneviratne, Mohamed F. Ghalwash, Daniel M. Gruen, Daby Sow, Deborah L. McGuinness:
Towards Clinically Relevant Explanations for Type-2 Diabetes Risk Prediction with the Explanation Ontology. AMIA 2021 - [c39]Sanjoy Dey, Aritra Bose, Subrata Saha, Prithwish Chakraborty, Mohamed F. Ghalwash, Filippo Utro, Aldo Guzmán-Sáenz, Kenney Ng, Jianying Hu, Laxmi Parida, Daby Sow:
Impact of Clinical and Genomic Factors on COVID-19 Disease Severity. AMIA 2021 - [c38]Mohamed F. Ghalwash, Prithwish Chakraborty, Akira Koseki, Hiroki Yanagisawa, Toshiya Iwamori, Ray Tokumasu, Masaki Makino, Ryosuke Yanagiya, Atsushi Suzuki, Michiharu Kudo, Daby Sow:
A Comparative Time-to-Event Analysis Across Health Systems. AMIA 2021 - [c37]Mohamed F. Ghalwash, Zijun Yao, Prithwish Chakraborty, James V. Codella, Daby Sow:
Phenotypical ontology driven framework for multi-task learning. CHIL 2021: 183-192 - [c36]Rui Li, Stephanie M. Hu, Mingyu Lu, Yuria Utsumi, Prithwish Chakraborty, Daby M. Sow, Piyush Madan, Jun Li, Mohamed F. Ghalwash, Zach Shahn, Li-Wei H. Lehman:
G-Net: a Recurrent Network Approach to G-Computation for Counterfactual Prediction Under a Dynamic Treatment Regime. ML4H@NeurIPS 2021: 282-299 - [i8]Q. Vera Liao, Milena Pribic, Jaesik Han, Sarah Miller, Daby Sow:
Question-Driven Design Process for Explainable AI User Experiences. CoRR abs/2104.03483 (2021) - [i7]Prithwish Chakraborty, James V. Codella, Piyush Madan, Ying Li, Hu Huang, Yoonyoung Park, Chao Yan, Ziqi Zhang, Cheng Gao, Steve Nyemba, Xu Min, Sanjib Basak, Mohamed F. Ghalwash, Zach Shahn, Parthasarathy Suryanarayanan, Italo Buleje, Shannon Harrer, Sarah Miller, Amol Rajmane, Colin Walsh, Jonathan Wanderer, Gigi Y. Yuen-Reed, Kenney Ng, Daby Sow, Bradley A. Malin:
Blending Knowledge in Deep Recurrent Networks for Adverse Event Prediction at Hospital Discharge. CoRR abs/2104.04377 (2021) - 2020
- [c35]Sanjoy Dey, Ping Zhang, Mohamed F. Ghalwash, Chandramouli Maduri, Daby Sow, Zachary Shahn:
Finding Causal Mechanistic Drug-Drug Interactions from Observational Data. AMIA 2020 - [c34]Mingyu Lu, Zachary Shahn, Daby Sow, Finale Doshi-Velez, Li-Wei H. Lehman:
Is Deep Reinforcement Learning Ready for Practical Applications in Healthcare? A Sensitivity Analysis of Duel-DDQN for Hemodynamic Management in Sepsis Patients. AMIA 2020 - [c33]Mohamed F. Ghalwash, Daby Sow:
A Multi-Task Learning Approach to Personalized Progression Modeling. ICHI 2020: 1-9 - [c32]Prithwish Chakraborty, Bum Chul Kwon, Sanjoy Dey, Amit Dhurandhar, Daniel M. Gruen, Kenney Ng, Daby Sow, Kush R. Varshney:
Tutorial on Human-Centered Explainability for Healthcare. KDD 2020: 3547-3548 - [i6]Rui Li, Zach Shahn, Jun Li, Mingyu Lu, Prithwish Chakraborty, Daby Sow, Mohamed F. Ghalwash, Li-Wei H. Lehman:
G-Net: A Deep Learning Approach to G-computation for Counterfactual Outcome Prediction Under Dynamic Treatment Regimes. CoRR abs/2003.10551 (2020) - [i5]Mingyu Lu, Zachary Shahn, Daby Sow, Finale Doshi-Velez, Li-Wei H. Lehman:
Is Deep Reinforcement Learning Ready for Practical Applications in Healthcare? A Sensitivity Analysis of Duel-DDQN for Sepsis Treatment. CoRR abs/2005.04301 (2020) - [i4]Mohamed F. Ghalwash, Zijun Yao, Prithwish Chakraborty, James V. Codella, Daby Sow:
ODVICE: An Ontology-Driven Visual Analytic Tool for Interactive Cohort Extraction. CoRR abs/2005.06434 (2020) - [i3]Parthasarathy Suryanarayanan, Bhavani Iyer, Prithwish Chakraborty, Bibo Hao, Italo Buleje, Piyush Madan, James V. Codella, Antonio Foncubierta, Divya Pathak, Sarah Miller, Amol Rajmane, Shannon Harrer, Gigi Yuan-Reed, Daby Sow:
A Canonical Architecture For Predictive Analytics on Longitudinal Patient Records. CoRR abs/2007.12780 (2020) - [i2]Mohamed F. Ghalwash, Zijun Yao, Prithwish Chakraborty, James V. Codella, Daby Sow:
Phenotypical Ontology Driven Framework for Multi-Task Learning. CoRR abs/2009.02188 (2020)
2010 – 2019
- 2019
- [j8]Ching-Hua Chen, James A. Hendler, Sabbir M. Rashid, Oshani Seneviratne, Daby Sow, Biplav Srivastava:
Reflections on Successful Research in Artificial Intelligence: An Introduction. AI Mag. 40(4): 3-5 (2019) - [j7]Arvind Gupta, Biplav Srivastava, Daby Sow, Ching-Hua Chen, Oshani Seneviratne:
Reflections on the Ingredients for Success in AI Research: An Interview with Arvind Gupta. AI Mag. 40(4): 24-27 (2019) - [c31]James V. Codella, Hillol Sarker, Prithwish Chakraborty, Mohamed F. Ghalwash, Zijun Yao, Daby Sow:
eXITs: An Ensemble Approach for Imputing Missing EHR Data. ICHI 2019: 1-3 - [c30]Sanjoy Dey, Ping Zhang, Daby Sow, Kenney Ng:
PerDREP: Personalized Drug Effectiveness Prediction from Longitudinal Observational Data. KDD 2019: 1258-1268 - [i1]Prithwish Chakraborty, Fei Wang, Jianying Hu, Daby Sow:
Explicit-Blurred Memory Network for Analyzing Patient Electronic Health Records. CoRR abs/1911.06472 (2019) - 2018
- [c29]Sanjoy Dey, Ping Zhang, Mohamed F. Ghalwash, Zach Shahn, Daby Sow:
Estimating Causal Multi-Drug-Drug Interaction for Adverse Drug Reactions. AMIA 2018 - [c28]Oliver Ren, Alistair E. W. Johnson, Eric P. Lehman, Matthieu Komorowski, Jerome Aboab, Fengyi Tang, Zach Shahn, Daby Sow, Roger G. Mark, Li-Wei H. Lehman:
Predicting and Understanding Unexpected Respiratory Decompensation in Critical Care Using Sparse and Heterogeneous Clinical Data. ICHI 2018: 144-151 - 2015
- [c27]Jie Xu, Daby M. Sow, Deepak S. Turaga, Mihaela van der Schaar:
Online Transfer Learning for Differential Diagnosis Determination. AAAI Workshop: WWW and Public Health Intelligence 2015 - [c26]Alain Biem, Maria Butrico, Mark Feblowitz, Tim Klinger, Yuri Malitsky, Kenney Ng, Adam Perer, Chandra Reddy, Anton Riabov, Horst Samulowitz, Daby M. Sow, Gerald Tesauro, Deepak S. Turaga:
Towards Cognitive Automation of Data Science. AAAI 2015: 4268-4269 - [c25]Anton V. Riabov, Shirin Sohrabi, Daby M. Sow, Deepak S. Turaga, Octavian Udrea, Long H. Vu:
Planning-Based Reasoning for Automated Large-Scale Data Analysis. ICAPS 2015: 282-290 - [c24]Guo-Jun Qi, Charu C. Aggarwal, Deepak S. Turaga, Daby M. Sow, Phil Anno:
State-Driven Dynamic Sensor Selection and Prediction with State-Stacked Sparseness. KDD 2015: 945-954 - [p2]Daby M. Sow, Kiran K. Turaga, Deepak S. Turaga, J. Michael Schmidt:
Mining of Sensor Data in Healthcare: A Survey. Healthcare Data Analytics 2015: 91-125 - 2014
- [j6]Yu Zhang, Daby M. Sow, Deepak S. Turaga, Mihaela van der Schaar:
A fast online learning algorithm for distributed mining of BigData. SIGMETRICS Perform. Evaluation Rev. 41(4): 90-93 (2014) - [c23]Peter D. Kirchner, Matthias Böhm, Berthold Reinwald, Daby M. Sow, J. Michael Schmidt, Deepak S. Turaga, Alain Biem:
Large Scale Discriminative Metric Learning. IPDPS Workshops 2014: 1656-1663 - 2013
- [c22]Alina Beygelzimer, Anton Riabov, Daby M. Sow, Deepak S. Turaga, Octavian Udrea:
Big Data Exploration Via Automated Orchestration of Analytic Workflows. ICAC 2013: 153-158 - [c21]Carolyn McGregor, Andrew James, Mike Eklund, Daby M. Sow, Maria Ebling, Marion Blount:
Real-time Multidimensional Temporal Analysis of Complex High Volume Physiological Data Streams in the Neonatal Intensive Care Unit. MedInfo 2013: 362-366 - [p1]Daby M. Sow, Deepak S. Turaga, J. Michael Schmidt:
Mining of Sensor Data in Healthcare: A Survey. Managing and Mining Sensor Data 2013: 459-504 - 2012
- [j5]Daby M. Sow, Jimeng Sun, Alain Biem, Jianying Hu, Marion Blount, Shahram Ebadollahi:
Real-time analysis for short-term prognosis in intensive care. IBM J. Res. Dev. 56(5): 3 (2012) - 2010
- [c20]Jimeng Sun, Daby M. Sow, Jianying Hu, Shahram Ebadollahi:
A System for Mining Temporal Physiological Data Streams for Advanced Prognostic Decision Support. ICDM 2010: 1061-1066 - [c19]Jimeng Sun, Daby M. Sow, Jianying Hu, Shahram Ebadollahi:
Localized Supervised Metric Learning on Temporal Physiological Data. ICPR 2010: 4149-4152 - [c18]Marion Blount, Carolyn McGregor, Andrew James, Daby M. Sow, Rishikesan Kamaleswaran, Sascha Tuuha, Jennifer Percival, Nathan Percival:
On the integration of an artifact system and a real-time healthcare analytics system. IHI 2010: 647-655 - [c17]Daby M. Sow, Alain Biem, Marion Blount, Maria Ebling, Olivier Verscheure:
Body sensor data processing using stream computing. Multimedia Information Retrieval 2010: 449-458 - [c16]Wim De Pauw, Mihai Letia, Bugra Gedik, Henrique Andrade, Andy Frenkiel, Michael Pfeifer, Daby M. Sow:
Visual Debugging for Stream Processing Applications. RV 2010: 18-35
2000 – 2009
- 2009
- [j4]Mounir Mokhtari, Daby M. Sow:
Preface. Pervasive Mob. Comput. 5(3): 223-225 (2009) - 2008
- [c15]Deepak S. Turaga, Olivier Verscheure, Daby M. Sow, Lisa Amini:
Adaptative Signal Sampling and Sample Quantization for Resource-Constrained Stream Processing. BIOSIGNALS (2) 2008: 96-103 - [c14]Archan Misra, Marion Blount, Anastasios Kementsietsidis, Daby M. Sow, Min Wang:
Advances and Challenges for Scalable Provenance in Stream Processing Systems. IPAW 2008: 253-265 - [c13]Ya-Ti Peng, Daby M. Sow:
Data scaling in remote health monitoring systems. ISCAS 2008: 2042-2045 - 2007
- [c12]Eran Belinsky, Natalia Marmasse, Eyal Sonsino, Vladimir Soroka, Maria Ebling, William F. Jerome, Archan Misra, Daby M. Sow, Sune Jakobsson:
PASTA: Deriving Rich Presence for Converged Telecommunications Network Applications. COMSWARE 2007 - [c11]Daby M. Sow, Lipyeow Lim, Min Wang, Kyu Hyun Kim:
Persisting and querying biometric event streams with hybrid relational-XML DBMS. DEBS 2007: 189-197 - [c10]Min Wang, Marion Blount, John Davis, Archan Misra, Daby M. Sow:
A time-and-value centric provenance model and architecture for medical event streams. HealthNet 2007: 95-100 - [c9]Marion Blount, John S. Davis II, Maria Ebling, Ji Hyun Kim, Kyu Hyun Kim, KangYoon Lee, Archan Misra, SeHun Park, Daby M. Sow, Young Ju Tak, Min Wang, Karen Witting:
Century: Automated Aspects of Patient Care. RTCSA 2007: 504-509 - 2006
- [j3]Daby M. Sow, John S. Davis II, Maria Ebling, Archan Misra, Lawrence D. Bergman:
Uncovering the to-dos hidden in your in-box. IBM Syst. J. 45(4): 739-758 (2006) - [c8]John Davis, Daby M. Sow, Daniela Bourges-Waldegg, Changjie Guo, Christian Hoertnagl, Markus Stolze, Brian White Eagle, Ying Yin:
Supporting Mobile Business Workflow with Commune. WMCSA 2006: 10-18 - [c7]John Davis, Daby M. Sow, Daniela Bourges-Waldegg, Changjie Guo, Christian Hoertnagl, Markus Stolze, Brian White Eagle, Ying Yin:
Supporting Mobile Business Workflow with Commune. WMCSA 2006: 43 - 2005
- [c6]Daby M. Sow, Maria Ebling, Rene-Pierre Lehmann, John S. Davis II, Lawrence D. Bergman:
SCOUT Contextually Organizes User Tasks. ICEBE 2005: 94-101 - [c5]Joel W. Branch, John S. Davis II, Daby M. Sow, Chatschik Bisdikian:
Sentire: A Framework for Building Middleware for Sensor and Actuator Networks. PerCom Workshops 2005: 396-400 - 2003
- [j2]Daby M. Sow, Alexandros Eleftheriadis:
Complexity distortion theory. IEEE Trans. Inf. Theory 49(3): 604-608 (2003) - [c4]John S. Davis II, Daby M. Sow, Marion Blount, Maria Ebling:
Context Tailor: Towards a Programming Model for Context-Aware Computing. Middleware Workshops 2003: 68-75 - [c3]Daby M. Sow, David P. Olshefski, Mandis Beigi, Guruduth Banavar:
Prefetching Based on Web Usage Mining. Middleware 2003: 262-281 - 2002
- [j1]Hui Lei, Daby M. Sow, John S. Davis II, Guruduth Banavar, Maria Ebling:
The design and applications of a context service. ACM SIGMOBILE Mob. Comput. Commun. Rev. 6(4): 45-55 (2002) - 2001
- [c2]Chatschik Bisdikian, Jim Christensen, John S. Davis II, Maria Ebling, Guerney D. H. Hunt, William F. Jerome, Hui Lei, Stéphane H. Maes, Daby M. Sow:
Enabling location-based applications. Workshop Mobile Commerce 2001: 38-42
1990 – 1999
- 1997
- [c1]Daby M. Sow, Alexandros Eleftheriadis:
Algorithmic Representation of Visual Information. ICIP (2) 1997: 250-253
Coauthor Index
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last updated on 2024-10-21 21:33 CEST by the dblp team
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