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Daby M. Sow
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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
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
Human-centered explainability for life sciences, healthcare, and medical informatics. Patterns 3(5): 100493 (2022) - [c41]Bekir Oguzhan Turkkan
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
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
Phenotypical ontology driven framework for multi-task learning. CHIL 2021: 183-192 - [c36]Rui Li, Stephanie M. Hu
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
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
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
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
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
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
eXITs: An Ensemble Approach for Imputing Missing EHR Data. ICHI 2019: 1-3 - [c30]Sanjoy Dey, Ping Zhang
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
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
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
A System for Mining Temporal Physiological Data Streams for Advanced Prognostic Decision Support. ICDM 2010: 1061-1066 - [c19]Jimeng Sun
Localized Supervised Metric Learning on Temporal Physiological Data. ICPR 2010: 4149-4152 - [c18]Marion Blount, Carolyn McGregor
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
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
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
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
Century: Automated Aspects of Patient Care. RTCSA 2007: 504-509 - 2006
- [j3]Daby M. Sow, John S. Davis II, Maria Ebling, Archan Misra
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 20:33 CEST by the dblp team
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