| |
 |      |
                                            |
Note: Links lead to the DBLP on the Web. Padhraic Smyth 43 Igor V. Cadez , Padhraic Smyth, Geoffrey J. McLachlan , Christine E. McLaren : Maximum Likelihood Estimation of Mixture Densities for Binned and Truncated Multivariate Data. Machine Learning 47 (1): 7-34 (2002) 42 Dmitry Pavlov , Padhraic Smyth: Probabilistic query models for transaction data. KDD 2001 : 164-173 41 Igor V. Cadez , Padhraic Smyth, Heikki Mannila : Probabilistic modeling of transaction data with applications to profiling, visualization, and prediction. KDD 2001 : 37-46 40 Heikki Mannila , Padhraic Smyth: Approximate Query Answering with Frequent Sets and Maximum Entropy. ICDE 2000 : 309 39 Igor V. Cadez , Scott Gaffney , Padhraic Smyth: A general probabilistic framework for clustering individuals and objects. KDD 2000 : 140-149 38 Igor V. Cadez , David Heckerman , Christopher Meek , Padhraic Smyth, Steven White : Visualization of navigation patterns on a Web site using model-based clustering. KDD 2000 : 280-284 37 Dmitry Pavlov , Darya Chudova , Padhraic Smyth: Towards scalable support vector machines using squashing. KDD 2000 : 295-299 36 Xianping Ge , Padhraic Smyth: Deformable Markov model templates for time-series pattern matching. KDD 2000 : 81-90 35 Igor V. Cadez , Padhraic Smyth: Model Complexity, Goodness of Fit and Diminishing Returns. NIPS 2000 : 388-394 34 Stephen D. Bay , Dennis F. Kibler , Michael J. Pazzani , Padhraic Smyth: The UCI KDD Archive of Large Data Sets for Data Mining Research and Experimentation. SIGKDD Explorations 2 (2): 81-85 (2000) 33 Heikki Mannila , Dmitry Pavlov , Padhraic Smyth: Prediction with Local Patterns using Cross-Entropy. KDD 1999 : 357-361 32 Scott Gaffney , Padhraic Smyth: Trajectory Clustering with Mixtures of Regression Models. KDD 1999 : 63-72 31 Xianping Ge , Wanda Pratt , Padhraic Smyth: Discovering Chinese Words from Unsegmented Text (poster abstract). SIGIR 1999 : 271-272 30 Padhraic Smyth, David Wolpert : Linearly Combining Density Estimators via Stacking. Machine Learning 36 (1-2): 59-83 (1999) 29 Gautam Das , King-Ip Lin , Heikki Mannila , Gopal Renganathan , Padhraic Smyth: Rule Discovery from Time Series. KDD 1998 : 16-22 28 Michael C. Burl , Lars Asker , Padhraic Smyth, Usama M. Fayyad , Pietro Perona , Larry Crumpler , Jayne Aubele : Learning to Recognize Volcanoes on Venus. Machine Learning 30 (2-3): 165-194 (1998) 27 William Rodman Shankle , Subramani Mani , Michael J. Pazzani , Padhraic Smyth: Detecting Very Early Stages of Dementia from Normal Aging with Machine Learning Methods. AIME 1997 : 73-85 26 Eamonn J. Keogh , Padhraic Smyth: A Probabilistic Approach to Fast Pattern Matching in Time Series Databases. KDD 1997 : 24-30 25 Padhraic Smyth, David Wolpert : Anytime Exploratory Data Analysis for Massive Data Sets. KDD 1997 : 54-60 24 Padhraic Smyth, Michael Ghil , Kayo Ide , Joe Roden , Andrew Fraser : Detecting Atmospheric Regimes Using Cross-Validated Clustering. KDD 1997 : 61-66 23 Clark Glymour , David Madigan , Daryl Pregibon , Padhraic Smyth: Statistical Themes and Lessons for Data Mining. Data Mining and Knowledge Discovery 1 (1): 11-28 (1997) 22 Pat Langley , Gregory M. Provan , Padhraic Smyth: Learning with Probabilistic Representations. Machine Learning 29 (2-3): 91-101 (1997) 21 Padhraic Smyth, David Heckerman , Michael I. Jordan : Probabilistic Independence Networks for Hidden Markov Probability Models. Neural Computation 9 (2): 227-269 (1997) 20 Usama M. Fayyad , Gregory Piatetsky-Shapiro , Padhraic Smyth, Ramasamy Uthurusamy : Advances in Knowledge Discovery and Data Mining. AAAI/MIT Press 1996 19 Usama M. Fayyad , Gregory Piatetsky-Shapiro , Padhraic Smyth: From Data Mining to Knowledge Discovery: An Overview. Advances in Knowledge Discovery and Data Mining 1996 : 1-34 18 Padhraic Smyth, Usama M. Fayyad , Michael C. Burl , Pietro Perona : Modeling Subjective Uncertainty in Image Annotation. Advances in Knowledge Discovery and Data Mining 1996 : 517-539 17 Padhraic Smyth: Clustering Using Monte Carlo Cross-Validation. KDD 1996 : 126-133 16 Usama M. Fayyad , Gregory Piatetsky-Shapiro , Padhraic Smyth: Knowledge Discovery and Data Mining: Towards a Unifying Framework. KDD 1996 : 82-88 15 Usama M. Fayyad , Gregory Piatetsky-Shapiro , Padhraic Smyth: From Data Mining to Knowledge Discovery in Databases. AI Magazine 17 (3): 37-54 (1996) 14 Usama M. Fayyad , Gregory Piatetsky-Shapiro , Padhraic Smyth: The KDD Process for Extracting Useful Knowledge from Volumes of Data. CACM 39 (11): 27-34 (1996) 13 Clark Glymour , David Madigan , Daryl Pregibon , Padhraic Smyth: Statistical Inference and Data Mining. CACM 39 (11): 35-41 (1996) 12 Padhraic Smyth, Alexander Gray , Usama M. Fayyad : Retrofitting Decision Tree Classifiers Using Kernel Density Estimation. ICML 1995 : 506-514 11 Usama M. Fayyad , Padhraic Smyth, Nicholas Weir , S. George Djorgovski : Automated Analysis and Exploration of Image Databases: Results, Progress, and Challenges. JIIS 4 (1): 7-25 (1995) 10 Usama M. Fayyad , Padhraic Smyth: The Automated Analysis, Cataloging, and Searching of Digital Image Libraries: A Machine Learning Approach. DL 1994 : 225-249 9 Michael C. Burl , Usama M. Fayyad , Pietro Perona , Padhraic Smyth: Automated Analysis of Radar Imagery of Venus: Handling Lack of Ground Truth. ICIP (3) 1994 : 236-240 8 Padhraic Smyth, Michael C. Burl , Usama M. Fayyad , Pietro Perona : Knowledge Discovery in Large Image Databases: Dealing with Uncertainties in Ground Truth. KDD Workshop 1994 : 109-120 7 Gregory Piatetsky-Shapiro , Christopher J. Matheus , Padhraic Smyth, Ramasamy Uthurusamy : KDD-93: Progress and Challenges in Knowledge Discovery in Databases. AI Magazine 15 (3): 77-82 (1994) 6 Padhraic Smyth, Rodney M. Goodman : An Information Theoretic Approach to Rule Induction from Databases. TKDE 4 (4): 301-316 (1992) 5 Padhraic Smyth, Rodney M. Goodman : Rule Induction Using Information Theory. Knowledge Discovery in Databases 1991 : 159-176 4 Padhraic Smyth, Rodney M. Goodman , C. Higgins : A Hybrid Rule-Based/Bayesian Classifier. ECAI 1990 : 610-615 3 Padhraic Smyth: On Stochastic Complexity and Admissible Models for Neural Network Classifiers. NIPS 1990 : 818-824 2 Rodney M. Goodman , Padhraic Smyth: Information-Theoretic Rule Induction. ECAI 1988 : 357-362 1 Rodney M. Goodman , John W. Miller , Padhraic Smyth: An Information Theoretic Approach to Rule-Based Connectionist Expert Systems. NIPS 1988 : 256-263  DiSC'02 © 2003 Association for Computing Machinery |
