Michael J. Pazzani

137 papers A* 29A 10B 13C 1Misc 2Journal 48Unranked 33

Year	Rank	Type	Title / Venue / Authors
2023	J	`jnl`	Feature Interpretation Using Generative Adversarial Networks (FIGAN): A Framework for Visualizing a CNN's Learned Features. IEEE Access Kyle Hasenstab, Justin Huynh, Samira Masoudi, Guilherme M. Cunha, Michael J. Pazzani, Albert Hsiao
2022	J	`jnl`	Deep Learning Radiographic Assessment of Pulmonary Edema: Optimizing Clinical Performance, Training With Serum Biomarkers. IEEE Access Justin Huynh, Samira Masoudi, Abraham Noorbakhsh, Amin Mahmoodi, Seth Kligerman, Andrew Yen, Kathleen Jacobs, Lewis Hahn, Kyle Hasenstab, Michael J. Pazzani, Albert Hsiao
2022	—	`conf`	Deep Learning Radiographic Assessment of Pulmonary Edema: Training with Serum Biomarkers. MIDL Justin Huynh, Samira Masoudi, Abraham Noorbakhsh, Kyle Hasenstab, Michael J. Pazzani, Albert Hsiao
2022	A*	`conf`	Expert-Informed, User-Centric Explanations for Machine Learning. AAAI Michael J. Pazzani, Severine Soltani, Robert Kaufman, Samson Qian, Albert Hsiao
2022	J	`jnl`	Explaining Image Classifiers Using Contrastive Counterfactuals in Generative Latent Spaces. CoRR Kamran Alipour, Aditya Lahiri, Ehsan Adeli, Babak Salimi, Michael J. Pazzani
2022	B	`conf`	User-Centric Enhancements to Explainable AI Algorithms for Image Classification. CogSci Severine Soltani, Robert Kaufman, Michael J. Pazzani
2021	J	`jnl`	A Comprehensive Explanation Framework for Biomedical Time Series Classification. IEEE J. Biomed. Health Informatics Praharsh Ivaturi, Matteo Gadaleta, Amitabh C. Pandey, Michael J. Pazzani, Steven R. Steinhubl, Giorgio Quer
2020	A	`conf`	CDeepEx: Contrastive Deep Explanations. ECAI Amir Feghahati, Christian R. Shelton, Michael J. Pazzani, Kevin Tang
2020	J	`jnl`	Ghost Imputation: Accurately Reconstructing Missing Data of the Off Period. IEEE Trans. Knowl. Data Eng. Reza Rawassizadeh, Hamidreza Keshavarz, Michael J. Pazzani
2019	J	`jnl`	Indexing Multivariate Mobile Data through Spatio-Temporal Event Detection and Clustering. Sensors Reza Rawassizadeh, Chelsea Dobbins, Mohammad Akbari, Michael J. Pazzani
2019	J	`jnl`	Manifestation of virtual assistants and robots into daily life: vision and challenges. CCF Trans. Pervasive Comput. Interact. Reza Rawassizadeh, Taylan K. Sen, Sunny Jung Kim, Christian Meurisch, Hamidreza Keshavarz, Max Mühlhäuser, Michael J. Pazzani
2018	—	`conf`	Explaining Contrasting Categories. IUI Workshops Michael J. Pazzani, Amir Feghahati, Christian R. Shelton, Aaron R. Seitz
2017	—	`conf`	A natural language query interface for searching personal information on smartwatches. PerCom Workshops Reza Rawassizadeh, Chelsea Dobbins, Manouchehr Nourizadeh, Zahra Ghamchili, Michael J. Pazzani
2016	J	`jnl`	A Natural Language Query Interface for Searching Personal Information on Smartwatches. CoRR Reza Rawassizadeh, Chelsea Dobbins, Manouchehr Nourizadeh, Zahra Ghamchili, Michael J. Pazzani
2016	J	`jnl`	Scalable Daily Human Behavioral Pattern Mining from Multivariate Temporal Data. IEEE Trans. Knowl. Data Eng. Reza Rawassizadeh, Elaheh Momeni, Chelsea Dobbins, Joobin Gharibshah, Michael J. Pazzani
2015	J	`jnl`	Energy-Efficient Integration of Continuous Context Sensing and Prediction into Smartwatches. Sensors Reza Rawassizadeh, Martin Tomitsch, Manouchehr Nourizadeh, Elaheh Momeni, Aaron Peery, Liudmila Ulanova, Michael J. Pazzani
2011	A*	`conf`	Active learning using on-line algorithms. KDD Chris Mesterharm, Michael J. Pazzani
2011	A	`ed.`	Proceedings of the 16th International Conference on Intelligent User Interfaces, IUI 2011, Palo Alto, CA, USA, February 13-16, 2011 IUI Pearl Pu, Michael J. Pazzani, Elisabeth André, Doug Riecken
2010	A*	`conf`	An energy-efficient mobile recommender system. KDD Yong Ge, Hui Xiong, Alexander Tuzhilin, Keli Xiao, Marco Gruteser, Michael J. Pazzani
2007	—	`conf`	Adaptive News Access. The Adaptive Web Daniel Billsus, Michael J. Pazzani
2007	—	`conf`	Content-Based Recommendation Systems. The Adaptive Web Michael J. Pazzani, Daniel Billsus
2006	—	`conf`	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 Michael J. Pazzani
2006	A*	`conf`	Mining for proposal reviewers: lessons learned at the national science foundation. KDD Seth Hettich, Michael J. Pazzani
2005	J	`jnl`	The Lowell database research self-assessment. Commun. ACM 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
2004	B	`conf`	Machine Learning for Personalized Wireless Portals. ICTAI Michael J. Pazzani
2003	—	`conf`	Adaptive Interfaces for Ubiquitous Web Access. User Modeling Michael J. Pazzani
2003	J	`jnl`	The Lowell Database Research Self Assessment CoRR 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
2002	J	`jnl`	Adaptive Web Site Agents. Auton. Agents Multi Agent Syst. Michael J. Pazzani, Daniel Billsus
2002	J	`jnl`	Adaptive interfaces for ubiquitous web access. Commun. ACM Daniel Billsus, Clifford Brunk, Craig Evans, Brian Gladish, Michael J. Pazzani
2002	B	`conf`	Commercial Applications of Machine Learning for Personalized Wireless Portals. PRICAI Michael J. Pazzani
2002	A	`conf`	Iterative Deepening Dynamic Time Warping for Time Series. SDM Selina Chu, Eamonn J. Keogh, David M. Hart, Michael J. Pazzani
2002	J	`jnl`	Learning the Structure of Augmented Bayesian Classifiers. Int. J. Artif. Intell. Tools Eamonn J. Keogh, Michael J. Pazzani
2002	J	`jnl`	Locally adaptive dimensionality reduction for indexing large time series databases. ACM Trans. Database Syst. Kaushik Chakrabarti, Eamonn J. Keogh, Sharad Mehrotra, Michael J. Pazzani
2001	A*	`conf`	An Online Algorithm for Segmenting Time Series. ICDM Eamonn J. Keogh, Selina Chu, David M. Hart, Michael J. Pazzani
2001	A	`conf`	Derivative Dynamic Time Warping. SDM Eamonn J. Keogh, Michael J. Pazzani
2001	J	`jnl`	Detecting Group Differences: Mining Contrast Sets. Data Min. Knowl. Discov. Stephen D. Bay, Michael J. Pazzani
2001	J	`jnl`	Dimensionality Reduction for Fast Similarity Search in Large Time Series Databases. Knowl. Inf. Syst. Eamonn J. Keogh, Kaushik Chakrabarti, Michael J. Pazzani, Sharad Mehrotra
2001	A*	`conf`	Ensemble-index: a new approach to indexing large databases. KDD Eamonn J. Keogh, Selina Chu, Michael J. Pazzani
2001	A*	`conf`	Improving mobile internet usability. WWW George Buchanan, Sarah Farrant, Matt Jones, Harold W. Thimbleby, Gary Marsden, Michael J. Pazzani
2001	—	`conf`	Locally Adaptive Dimensionality Reduction for Indexing Large Time Series Databases. SIGMOD Conference Eamonn J. Keogh, Kaushik Chakrabarti, Sharad Mehrotra, Michael J. Pazzani
2001	J	`jnl`	Machine Learning for User Modeling. User Model. User Adapt. Interact. Geoffrey I. Webb, Michael J. Pazzani, Daniel Billsus
2000	B	`conf`	A Simple Dimensionality Reduction Technique for Fast Similarity Search in Large Time Series Databases. PAKDD Eamonn J. Keogh, Michael J. Pazzani
2000	A	`conf`	A learning agent for wireless news access. IUI Daniel Billsus, Michael J. Pazzani, James Chen
2000	A*	`conf`	Characterizing Model Erros and Differences. ICML Stephen D. Bay, Michael J. Pazzani
2000	B	`conf`	Collaborative Filtering with the Simple Bayesian Classifier. PRICAI Koji Miyahara, Michael J. Pazzani
2000	J	`jnl`	Knowledge discovery from data? IEEE Intell. Syst. Michael J. Pazzani
2000	J	`jnl`	Learning with Globally Predictive Tests. New Gener. Comput. Michael J. Pazzani
2000	A	`conf`	Representation of electronic mail filtering profiles: a user study. IUI Michael J. Pazzani
2000	A*	`conf`	Scaling up dynamic time warping for datamining applications. KDD Eamonn J. Keogh, Michael J. Pazzani
2000	J	`jnl`	The UCI KDD Archive of Large Data Sets for Data Mining Research and Experimentation. SIGKDD Explor. Stephen D. Bay, Dennis F. Kibler, Michael J. Pazzani, Padhraic Smyth
2000	J	`jnl`	User Modeling for Adaptive News Access. User Model. User Adapt. Interact. Daniel Billsus, Michael J. Pazzani
1999	J	`jnl`	A Framework for Collaborative, Content-Based and Demographic Filtering. Artif. Intell. Rev. Michael J. Pazzani
1999	—	`conf`	A Personal News Agent That Talks, Learns and Explains. Agents Daniel Billsus, Michael J. Pazzani
1999	J	`jnl`	A Principal Components Approach to Combining Regression Estimates. Mach. Learn. Christopher J. Merz, Michael J. Pazzani
1999	—	`conf`	Adaptive Web Site Agents. Agents Michael J. Pazzani, Daniel Billsus
1999	B	`conf`	An Indexing Scheme for Fast Similarity Search in Large Time Series Databases. SSDBM Eamonn J. Keogh, Michael J. Pazzani
1999	J	`jnl`	Combinatorial Optimization in Rapidly Mutating Drug-Resistant Viruses. J. Comb. Optim. Richard H. Lathrop, Michael J. Pazzani
1999	A*	`conf`	Detecting Change in Categorical Data: Mining Contrast Sets. KDD Stephen D. Bay, Michael J. Pazzani
1999	J	`jnl`	Knowledge-Based Avoidance of Drug-Resistant HIV Mutants. AI Mag. Richard H. Lathrop, Nicholas R. Steffen, Miriam P. Raphael, Sophia Deeds-Rubin, Michael J. Pazzani, Paul J. Cimoch, Darryl M. See, Jeremiah G. Tilles
1999	A	`conf`	Learning augmented Bayesian classifiers: A comparison of distribution-based and classification-based approaches. AISTATS Eamonn J. Keogh, Michael J. Pazzani
1999	—	`conf`	Refinement of Neuro-psychological Tests for Dementia Screening in a Cross Cultural Population Using Machine Learning. AIMDM Subramani Mani, Malcolm B. Dick, Michael J. Pazzani, Evelyn L. Teng, Daniel Kempler, I. Maribell Taussig
1999	A*	`conf`	Relevance Feedback Retrieval of Time Series Data. SIGIR Eamonn J. Keogh, Michael J. Pazzani
1999	—	`conf`	Scaling up Dynamic Time Warping to Massive Dataset. PKDD Eamonn J. Keogh, Michael J. Pazzani
1999	J	`jnl`	Two-Stage Machine Learning model for guideline development. Artif. Intell. Medicine Subramani Mani, William Rodman Shankle, Malcolm B. Dick, Michael J. Pazzani
1999	J	`jnl`	Workshop on Recommender Systems: Algorithms and Evaluation. SIGIR Forum Ian Soboroff, Charles K. Nicholas, Michael J. Pazzani
1998	—	`conf`	Adjusted Probability Naive Bayesian Induction. Australian Joint Conference on Artificial Intelligence Geoffrey I. Webb, Michael J. Pazzani
1998	A*	`conf`	An Enhanced Representation of Time Series Which Allows Fast and Accurate Classification, Clustering and Relevance Feedback. KDD Eamonn J. Keogh, Michael J. Pazzani
1998	Misc	`conf`	Guideline generation from data by induction of decision tables using a Bayesian network framework. AMIA Subramani Mani, Michael J. Pazzani
1998	—	`conf`	Knowledge-Based Avoidance of Drug-Resistant HIV Mutants. AAAI/IAAI Richard H. Lathrop, Nicholas R. Steffen, Miriam P. Raphael, Sophia Deeds-Rubin, Michael J. Pazzani, Paul J. Cimoch, Darryl M. See, Jeremiah G. Tilles
1998	A*	`conf`	Learning Collaborative Information Filters. ICML Daniel Billsus, Michael J. Pazzani
1998	B	`conf`	Learning with Globally Predictive Tests. Discovery Science Michael J. Pazzani
1998	—	`conf`	Simple Models for Estimating Dementia Severity Using Machine Learning. MedInfo William Rodman Shankle, Subramani Mani, Malcolm B. Dick, Michael J. Pazzani
1997	A*	`conf`	Beyond Concise and Colorful: Learning Intelligible Rules. KDD Michael J. Pazzani, Subramani Mani, William Rodman Shankle
1997	A	`conf`	Combining Neural Network Regression Estimates Using Principal Components. AISTATS Christopher J. Merz, Michael J. Pazzani
1997	B	`conf`	Detecting Very Early Stages of Dementia from Normal Aging with Machine Learning Methods. AIME William Rodman Shankle, Subramani Mani, Michael J. Pazzani, Padhraic Smyth
1997	Misc	`conf`	Differential Diagnosis of Dementia: A Knowledge Discovery and Data Mining (KDD) Approach. AMIA Subramani Mani, William Rodman Shankle, Michael J. Pazzani, Padhraic Smyth, Malcolm B. Dick
1997	B	`conf`	Knowledge Discovery from a Breast Cancer Database. AIME Subramani Mani, Michael J. Pazzani, John West
1997	J	`jnl`	Learning Probabilistic User Profiles: Applications for Finding Interesting Web Sites, Notifying Users of Relevant Changes to Web Pages, and Locating Grant Opportunities. AI Mag. Mark S. Ackerman, Daniel Billsus, Scott Gaffney, Seth Hettich, Gordon Khoo, Dong Joon Kim, Raymond Klefstad, Charles Lowe, Alexius Ludeman, Jack Muramatsu, Kazuo Omori, Michael J. Pazzani, Douglas Semler, Brian Starr, Paul Yap
1997	J	`jnl`	Learning and Revising User Profiles: The Identification of Interesting Web Sites. Mach. Learn. Michael J. Pazzani, Daniel Billsus
1997	J	`jnl`	On the Optimality of the Simple Bayesian Classifier under Zero-One Loss. Mach. Learn. Pedro M. Domingos, Michael J. Pazzani
1997	—	`conf`	The Do-I-Care Agent: Effective Social Discovery and Filtering on the Web. RIAO Mark S. Ackerman, Brian Starr, Michael J. Pazzani
1996	A*	`conf`	Beyond Independence: Conditions for the Optimality of the Simple Bayesian Classifier. ICML Pedro M. Domingos, Michael J. Pazzani
1996	—	`conf`	Combining Neural Network Regression Estimates with Regularized Linear Weights. NIPS Christopher J. Merz, Michael J. Pazzani
1996	—	`conf`	Do-I-Care: a collaborative Web agent. CHI Conference Companion Brian Starr, Mark S. Ackerman, Michael J. Pazzani
1996	J	`jnl`	Error Reduction through Learning Multiple Descriptions. Mach. Learn. Kamal M. Ali, Michael J. Pazzani
1996	J	`jnl`	Review of "Inductive Logic Programming: Techniques and Applications" by Nada Lavrac, Saso Dzeroski. Mach. Learn. Michael J. Pazzani
1996	—	`conf`	Simple Bayesian Classifiers Do Not Assume Independence. AAAI/IAAI, Vol. 2 Pedro M. Domingos, Michael J. Pazzani
1996	—	`conf`	Syskill & Webert: Identifying Interesting Web Sites. AAAI/IAAI, Vol. 1 Michael J. Pazzani, Jack Muramatsu, Daniel Billsus
1996	J	`jnl`	Tuning Numeric Parameters to Troubleshoot a Telephone-Network Loop. IEEE Expert Christopher J. Merz, Michael J. Pazzani, Andrea Pohoreckyj Danyluk
1995	A*	`conf`	A Lexical Based Semantic Bias for Theory Revision. ICML Clifford Brunk, Michael J. Pazzani
1995	—	`conf`	Acquiring and updating hierarchical knowledge for machine translation based on a clustering technique. Learning for Natural Language Processing Takefumi Yamazaki, Michael J. Pazzani, Christopher J. Merz
1995	A*	`conf`	An Iterative Improvement Approach for the Discretization of Numeric Attributes in Bayesian Classifiers. KDD Michael J. Pazzani
1995	A	`conf`	Classification Using Bayes Averaging of Multiple, Relational Rule-based Models. AISTATS Kamal M. Ali, Michael J. Pazzani
1995	J	`jnl`	Hydra-mm: Learning Multiple Descriptions to Improve Classification Accuracy. Int. J. Artif. Intell. Tools Kamal M. Ali, Michael J. Pazzani
1995	A*	`conf`	Learning Hierarchies from Ambiguous Natural Language Data. ICML Takefumi Yamazaki, Michael J. Pazzani, Christopher J. Merz
1995	B	`conf`	Learning from hotlists and coldlists: towards a WWW information filtering and seeking agent. ICTAI Michael J. Pazzani, Larry Nguyen, Stefanus Mantik
1995	A	`conf`	Searching for Dependencies in Bayesian Classifiers. AISTATS Michael J. Pazzani
1994	C	`conf`	Avoiding Non-Termination when Learning Logical Programs: A Case Study with FOIL and FOCL. LOPSTR Giovanni Semeraro, Floriana Esposito, Donato Malerba, Clifford Brunk, Michael J. Pazzani
1994	J	`jnl`	Exploring the Decision Forest: An Empirical Investigation of Occam's Razor in Decision Tree Induction. CoRR Patrick M. Murphy, Michael J. Pazzani
1994	J	`jnl`	Exploring the Decision Forest: An Empirical Investigation of Occam's Razor in Decision Tree Induction. J. Artif. Intell. Res. Patrick M. Murphy, Michael J. Pazzani
1994	J	`jnl`	Guest Editor's Introduction. Mach. Learn. Michael J. Pazzani
1994	B	`conf`	On Learning Multiple Descriptions of a Concept. ICTAI Kamal M. Ali, Clifford Brunk, Michael J. Pazzani
1994	B	`conf`	Parameter Tuning for the MAX Expert System. ICTAI Christopher J. Merz, Michael J. Pazzani
1994	A*	`conf`	Reducing Misclassification Costs. ICML Michael J. Pazzani, Christopher J. Merz, Patrick M. Murphy, Kamal M. Ali, Timothy Hume, Clifford Brunk
1994	A*	`conf`	Revision of Production System Rule-Bases. ICML Patrick M. Murphy, Michael J. Pazzani
1993	A*	`conf`	A Methodology for Evaluating Theory Revision Systems: Results with Audrey II. IJCAI James Wogulis, Michael J. Pazzani
1993	J	`jnl`	A Reply to Cohen's Book Review of Creating a Memory of Causal Relationships. Mach. Learn. Michael J. Pazzani
1993	A*	`conf`	Finding Accurate Frontiers: A Knowledge-Intensive Approach to Relational Learning. AAAI Michael J. Pazzani, Clifford Brunk
1993	A*	`conf`	HYDRA: A Noise-tolerant Relational Concept Learning Algorithm. IJCAI Kamal M. Ali, Michael J. Pazzani
1993	J	`jnl`	Learning Causal Patterns: Making a Transition from Data-Driven to Theory-Driven Learning. Mach. Learn. Michael J. Pazzani
1992	J	`jnl`	A Framework for Average Case Analysis of Conjunctive Learning Algorithms. Mach. Learn. Michael J. Pazzani, Wendy Sarrett
1992	—	`conf`	Average Case Analysis of Learning kappa-CNF Concepts. ML Daniel S. Hirschberg, Michael J. Pazzani
1992	J	`jnl`	The Utility of Knowledge in Inductive Learning. Mach. Learn. Michael J. Pazzani, Dennis F. Kibler
1991	J	`jnl`	A Computational Theory of Learning Causal Relationships. Cogn. Sci. Michael J. Pazzani
1991	—	`conf`	A Knowledge-intensive Approach to Learning Relational Concepts. ML Michael J. Pazzani, Clifford Brunk, Glenn Silverstein
1991	—	`conf`	An Investigation of Noise-Tolerant Relational Concept Learning Algorithms. ML Clifford Brunk, Michael J. Pazzani
1991	—	`conf`	Constructive Induction of M-of-N Terms. ML Patrick M. Murphy, Michael J. Pazzani
1991	J	`jnl`	Detecting and correcting errors in rule-based expert systems: an integration of empirical and explanation-based learning. Knowl. Acquis. Michael J. Pazzani, Clifford Brunk
1991	—	`conf`	Relational Clichés: Constraining Induction During Relational Learning. ML Glenn Silverstein, Michael J. Pazzani
1990	—	`conf`	Average Case Analysis of Conjunctive Learning Algorithms. ML Michael J. Pazzani, Wendy Sarrett
1990	—	`book`	Creating a memory of causal relationships - an integration of empirical and explanation-based learning methods. Michael J. Pazzani
1989	A*	`conf`	Detecting and Correcting Errors of Omission After Explanation-Based Learning. IJCAI Michael J. Pazzani
1989	—	`conf`	Explanation-Based Learning with Week Domain Theories. ML Michael J. Pazzani
1989	—	`conf`	One-Sided Algorithms for Integrating Empirical and Explanation-Based Learning. ML Wendy Sarrett, Michael J. Pazzani
1988	—	`conf`	Integrated Learning with Incorrect and Incomplete Theories. ML Michael J. Pazzani
1988	—	`conf`	Integrating Explanation-Based and Empirical Learning Methods in OCCAM. EWSL Michael J. Pazzani
1987	A*	`conf`	A Comparison of Concept Identification in Human Learning and Network Learning with the Generalized Delta Rule. IJCAI Michael J. Pazzani, Michael G. Dyer
1987	—	`conf`	Creating High Level Knowledge Structures from Simple Elements. Knowledge Representation and Organization in Machine Learning Michael J. Pazzani
1987	J	`jnl`	Explanation-Based Learning for Knowledge-Based Systems. Int. J. Man Mach. Stud. Michael J. Pazzani
1987	J	`jnl`	Failure-Driven Learning of Fault Diagnosis Heuristics. IEEE Trans. Syst. Man Cybern. Michael J. Pazzani
1987	A*	`conf`	Using Prior Learning to Facilitate the Learning of New Causal Theories. IJCAI Michael J. Pazzani, Michael G. Dyer, Margot Flowers
1986	A*	`conf`	Refining the Knowledge Base of a Diagnostic Expert System: An Application of Failure-Driven Learning. AAAI Michael J. Pazzani
1986	A*	`conf`	The Role of Prior Causal Theories in Generalization. AAAI Michael J. Pazzani, Michael G. Dyer, Margot Flowers
1984	B	`conf`	Conceptual Analysis of Garden-Path Sentences. COLING Michael J. Pazzani
1984	J	`jnl`	Word-Meaning Selection in Multiprocess Language Understanding Programs. IEEE Trans. Pattern Anal. Mach. Intell. Richard E. Cullingford, Michael J. Pazzani
1983	A*	`conf`	Interactive Script Instantiation. AAAI Michael J. Pazzani
1983	—	`conf`	Knowledge Based Question Answering. ANLP Michael J. Pazzani, Carl Engelman