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Publication search results
found 141 matches
- 2024
- Hong Nguyen, Hoang Nguyen, Melinda Chang, Hieu Pham, Shrikanth Narayanan, Michael Pazzani:
ConPro: Learning Severity Representation for Medical Images using Contrastive Learning and Preference Optimization. CoRR abs/2404.18831 (2024) - 2023
- Kyle Hasenstab, Justin Huynh, Samira Masoudi, Guilherme M. Cunha, Michael J. Pazzani, Albert Hsiao:
Feature Interpretation Using Generative Adversarial Networks (FIGAN): A Framework for Visualizing a CNN's Learned Features. IEEE Access 11: 5144-5160 (2023) - Hong Nguyen, Cuong V. Nguyen, Shrikanth Narayanan, Benjamin Y. Xu, Michael Pazzani:
Explainable Severity ranking via pairwise n-hidden comparison: a case study of glaucoma. CoRR abs/2312.02541 (2023) - 2022
- Justin Huynh, Samira Masoudi, Abraham Noorbakhsh, Amin Mahmoodi, Seth Kligerman, Andrew Yen, Kathleen Jacobs, Lewis Hahn, Kyle Hasenstab, Michael J. Pazzani, Albert Hsiao:
Deep Learning Radiographic Assessment of Pulmonary Edema: Optimizing Clinical Performance, Training With Serum Biomarkers. IEEE Access 10: 48577-48588 (2022) - Michael J. Pazzani, Severine Soltani, Robert A. Kaufman, Samson Qian, Albert Hsiao:
Expert-Informed, User-Centric Explanations for Machine Learning. AAAI 2022: 12280-12286 - Severine Soltani, Robert A. Kaufman, Michael J. Pazzani:
User-Centric Enhancements to Explainable AI Algorithms for Image Classification. CogSci 2022 - Justin Huynh, Samira Masoudi, Abraham Noorbakhsh, Kyle Hasenstab, Michael J. Pazzani, Albert Hsiao:
Deep Learning Radiographic Assessment of Pulmonary Edema: Training with Serum Biomarkers. MIDL 2022: 590-604 - Kamran Alipour, Aditya Lahiri, Ehsan Adeli, Babak Salimi, Michael J. Pazzani:
Explaining Image Classifiers Using Contrastive Counterfactuals in Generative Latent Spaces. CoRR abs/2206.05257 (2022) - 2021
- Praharsh Ivaturi, Matteo Gadaleta, Amitabh C. Pandey, Michael J. Pazzani, Steven R. Steinhubl, Giorgio Quer:
A Comprehensive Explanation Framework for Biomedical Time Series Classification. IEEE J. Biomed. Health Informatics 25(7): 2398-2408 (2021) - 2020
- Reza Rawassizadeh, Hamidreza Keshavarz, Michael J. Pazzani:
Ghost Imputation: Accurately Reconstructing Missing Data of the Off Period. IEEE Trans. Knowl. Data Eng. 32(11): 2185-2197 (2020) - Amir Feghahati, Christian R. Shelton, Michael J. Pazzani, Kevin Tang:
CDeepEx: Contrastive Deep Explanations. ECAI 2020: 1143-1151 - 2019
- Reza Rawassizadeh, Taylan K. Sen, Sunny Jung Kim, Christian Meurisch, Hamidreza Keshavarz, Max Mühlhäuser, Michael J. Pazzani:
Manifestation of virtual assistants and robots into daily life: vision and challenges. CCF Trans. Pervasive Comput. Interact. 1(3): 163-174 (2019) - Reza Rawassizadeh, Chelsea Dobbins, Mohammad Akbari, Michael J. Pazzani:
Indexing Multivariate Mobile Data through Spatio-Temporal Event Detection and Clustering. Sensors 19(3): 448 (2019) - 2018
- Michael J. Pazzani, Amir Feghahati, Christian R. Shelton, Aaron R. Seitz:
Explaining Contrasting Categories. IUI Workshops 2018 - 2017
- Reza Rawassizadeh, Chelsea Dobbins, Manouchehr Nourizadeh, Zahra Ghamchili, Michael J. Pazzani:
A natural language query interface for searching personal information on smartwatches. PerCom Workshops 2017: 679-684 - 2016
- Reza Rawassizadeh, Elaheh Momeni, Chelsea Dobbins, Joobin Gharibshah, Michael J. Pazzani:
Scalable Daily Human Behavioral Pattern Mining from Multivariate Temporal Data. IEEE Trans. Knowl. Data Eng. 28(11): 3098-3112 (2016) - Reza Rawassizadeh, Chelsea Dobbins, Manouchehr Nourizadeh, Zahra Ghamchili, Michael J. Pazzani:
A Natural Language Query Interface for Searching Personal Information on Smartwatches. CoRR abs/1611.07139 (2016) - 2015
- Reza Rawassizadeh, Martin Tomitsch, Manouchehr Nourizadeh, Elaheh Momeni, Aaron Peery, Liudmila Ulanova, Michael J. Pazzani:
Energy-Efficient Integration of Continuous Context Sensing and Prediction into Smartwatches. Sensors 15(9): 22616-22645 (2015) - 2011
- Chris Mesterharm, Michael J. Pazzani:
Active learning using on-line algorithms. KDD 2011: 850-858 - Pearl Pu, Michael J. Pazzani, Elisabeth André, Doug Riecken:
Proceedings of the 16th International Conference on Intelligent User Interfaces, IUI 2011, Palo Alto, CA, USA, February 13-16, 2011. ACM 2011, ISBN 978-1-4503-0419-1 [contents] - Chris Mesterharm, Michael J. Pazzani:
Farm Ads. UCI Machine Learning Repository, 2011 - 2010
- Yong Ge, Hui Xiong, Alexander Tuzhilin, Keli Xiao, Marco Gruteser, Michael J. Pazzani:
An energy-efficient mobile recommender system. KDD 2010: 899-908 - 2007
- Daniel Billsus, Michael J. Pazzani:
Adaptive News Access. The Adaptive Web 2007: 550-570 - Michael J. Pazzani, Daniel Billsus:
Content-Based Recommendation Systems. The Adaptive Web 2007: 325-341 - 2006
- Michael J. Pazzani:
Adaptive Info - Personalizing the Wireless Web: Machine Learning 275 and Business 101. AAAI Spring Symposium: What Went Wrong and Why: Lessons from AI Research and Applications 2006: 12 - Seth Hettich, Michael J. Pazzani:
Mining for proposal reviewers: lessons learned at the national science foundation. KDD 2006: 862-871 - 2005
- Serge Abiteboul, Rakesh Agrawal, Philip A. Bernstein, Michael J. Carey, Stefano Ceri, W. Bruce Croft, David J. DeWitt, Michael J. Franklin, Hector Garcia-Molina, Dieter Gawlick, Jim Gray, Laura M. Haas, Alon Y. Halevy, Joseph M. Hellerstein, Yannis E. Ioannidis, Martin L. Kersten, Michael J. Pazzani, Michael Lesk, David Maier, Jeffrey F. Naughton, Hans-Jörg Schek, Timos K. Sellis, Avi Silberschatz, Michael Stonebraker, Richard T. Snodgrass, Jeffrey D. Ullman, Gerhard Weikum, Jennifer Widom, Stanley B. Zdonik:
The Lowell database research self-assessment. Commun. ACM 48(5): 111-118 (2005) - 2004
- Michael J. Pazzani:
Machine Learning for Personalized Wireless Portals. ICTAI 2004: 3 - 2003
- Michael J. Pazzani:
Adaptive Interfaces for Ubiquitous Web Access. User Modeling 2003: 1 - Michael J. Pazzani, Amnon Meyers:
NSF Research Award Abstracts 1990-2003. UCI Machine Learning Repository, 2003
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