dblp.uni-trier.dewww.uni-trier.de

Padhraic Smyth Vis

List of publications from the DBLP Bibliography Server - FAQ
Coauthor Index - Ask others: ACM DL/Guide - CiteSeerX - CSB - MetaPress - Google - Bing - Yahoo
Home Page

*2008
108EEChaitanya Chemudugunta, Padhraic Smyth, Mark Steyvers: Combining concept hierarchies and statistical topic models. CIKM 2008: 1469-1470
107EEChaitanya Chemudugunta, America Holloway, Padhraic Smyth, Mark Steyvers: Modeling Documents by Combining Semantic Concepts with Unsupervised Statistical Learning. International Semantic Web Conference 2008: 229-244
106EEIan Porteous, David Newman, Alexander T. Ihler, Arthur Asuncion, Padhraic Smyth, Max Welling: Fast collapsed gibbs sampling for latent dirichlet allocation. KDD 2008: 569-577
105EEArthur Asuncion, Padhraic Smyth, Max Welling: Asynchronous Distributed Learning of Topic Models. NIPS 2008: 81-88
104EEChaitanya Chemudugunta, Padhraic Smyth, Mark Steyvers: Text Modeling using Unsupervised Topic Models and Concept Hierarchies CoRR abs/0808.0973: (2008)
2007
103EESergey Kirshner, Padhraic Smyth: Infinite mixtures of trees. ICML 2007: 417-423
102EEDavid Newman, Kat Hagedorn, Chaitanya Chemudugunta, Padhraic Smyth: Subject metadata enrichment using statistical topic models. JCDL 2007: 366-375
101EEDavid Newman, Arthur Asuncion, Padhraic Smyth, Max Welling: Distributed Inference for Latent Dirichlet Allocation. NIPS 2007
100EEJames Bennett, Charles Elkan, Bing Liu, Padhraic Smyth, Domonkos Tikk: KDD Cup and workshop 2007. SIGKDD Explorations 9(2): 51-52 (2007)
99EEAlexander T. Ihler, Jon Hutchins, Padhraic Smyth: Learning to detect events with Markov-modulated poisson processes. TKDD 1(3): (2007)
2006
98EEPadhraic Smyth: Data-Driven Discovery Using Probabilistic Hidden Variable Models. ALT 2006: 28
97EEPadhraic Smyth: Data-Driven Discovery Using Probabilistic Hidden Variable Models. Discovery Science 2006: 13
96EEDavid Newman, Chaitanya Chemudugunta, Padhraic Smyth, Mark Steyvers: Analyzing Entities and Topics in News Articles Using Statistical Topic Models. ISI 2006: 93-104
95EEAlexander T. Ihler, Jon Hutchins, Padhraic Smyth: Adaptive event detection with time-varying poisson processes. KDD 2006: 207-216
94EEDavid Newman, Chaitanya Chemudugunta, Padhraic Smyth: Statistical entity-topic models. KDD 2006: 680-686
93EESeyoung Kim, Padhraic Smyth, Hal Stern: A Nonparametric Bayesian Approach to Detecting Spatial Activation Patterns in fMRI Data. MICCAI (2) 2006: 217-224
92EEChaitanya Chemudugunta, Padhraic Smyth, Mark Steyvers: Modeling General and Specific Aspects of Documents with a Probabilistic Topic Model. NIPS 2006: 241-248
91EEAlexander T. Ihler, Padhraic Smyth: Learning Time-Intensity Profiles of Human Activity using Non-Parametric Bayesian Models. NIPS 2006: 625-632
90EESeyoung Kim, Padhraic Smyth: Hierarchical Dirichlet Processes with Random Effects. NIPS 2006: 697-704
89EEIan Porteous, Alex Ihter, Padhraic Smyth, Max Welling: Gibbs Sampling for (Coupled) Infinite Mixture Models in the Stick Breaking Representation. UAI 2006
88EESeyoung Kim, Padhraic Smyth: Segmental Hidden Markov Models with Random Effects for Waveform Modeling. Journal of Machine Learning Research 7: 945-969 (2006)
2005
87EESeyoung Kim, Padhraic Smyth, Hal Stern, Jessica Turner: Parametric Response Surface Models for Analysis of Multi-site fMRI Data. MICCAI 2005: 352-359
86 Scott White, Padhraic Smyth: A Spectral Clustering Approach To Finding Communities in Graph. SDM 2005
85EEJoshua O'Madadhain, Jon Hutchins, Padhraic Smyth: Prediction and ranking algorithms for event-based network data. SIGKDD Explorations 7(2): 23-30 (2005)
2004
84EEMark Steyvers, Padhraic Smyth, Michal Rosen-Zvi, Thomas L. Griffiths: Probabilistic author-topic models for information discovery. KDD 2004: 306-315
83EEScott Gaffney, Padhraic Smyth: Joint Probabilistic Curve Clustering and Alignment. NIPS 2004
82EESeyoung Kim, Padhraic Smyth, Stefan Luther: Modeling Waveform Shapes with Random E ects Segmental Hidden Markov Models. UAI 2004: 309-316
81EESergey Kirshner, Padhraic Smyth, Andrew Robertson: Conditional Chow-Liu Tree Structures for Modeling Discrete-Valued Vector Time Series. UAI 2004: 317-314
80EEMichal Rosen-Zvi, Thomas L. Griffiths, Mark Steyvers, Padhraic Smyth: The Author-Topic Model for Authors and Documents. UAI 2004: 487-494
2003
79 Pierre Baldi, Paolo Frasconi, Padhraic Smyth: Modeling the Internet and the Web: Probabilistic Method and Algorithms John Wiley 2003
78 Sergey Kirshner, Sridevi Parise, Padhraic Smyth: Unsupervised Learning with Permuted Data. ICML 2003: 345-352
77EEScott White, Padhraic Smyth: Algorithms for estimating relative importance in networks. KDD 2003: 266-275
76EEDarya Chudova, Scott Gaffney, Eric Mjolsness, Padhraic Smyth: Translation-invariant mixture models for curve clustering. KDD 2003: 79-88
75EEDarya Chudova, Christopher Hart, Eric Mjolsness, Padhraic Smyth: Gene Expression Clustering with Functional Mixture Models. NIPS 2003
74EEDmitry Pavlov, Padhraic Smyth: Approximate Query Answering by Model Averaging. SDM 2003
73 Darya Chudova, Scott Gaffney, Padhraic Smyth: Probabilistic Models For Joint Clustering And Time-Warping Of Multidimensional Curves. UAI 2003: 134-141
72EEDarya Chudova, Padhraic Smyth: Analysis of Pattern Discovery in Sequences Using a Bayes Error Framework. Data Min. Knowl. Discov. 7(3): 273-299 (2003)
71EEIgor V. Cadez, David Heckerman, Christopher Meek, Padhraic Smyth, Steven White: Model-Based Clustering and Visualization of Navigation Patterns on a Web Site. Data Min. Knowl. Discov. 7(4): 399-424 (2003)
70EEDmitry Pavlov, Heikki Mannila, Padhraic Smyth: Beyond Independence: Probabilistic Models for Query Approximation on Binary Transaction Data. IEEE Trans. Knowl. Data Eng. 15(6): 1409-1421 (2003)
2002
69EEPadhraic Smyth: Learning with Mixture Models: Concepts and Applications. ECML 2002: 529-
68EESergey Kirshner, Igor V. Cadez, Padhraic Smyth, Chandrika Kamath, Erick Cantú-Paz: Probabilistic Model-Based Detection of Bent-Double Radio Galaxies. ICPR (2) 2002: 499-502
67EEDarya Chudova, Padhraic Smyth: Pattern discovery in sequences under a Markov assumption. KDD 2002: 153-162
66EESergey Kirshner, Igor V. Cadez, Padhraic Smyth, Chandrika Kamath: Learning to Classify Galaxy Shapes Using the EM Algorithm. NIPS 2002: 1497-1504
65EEPadhraic Smyth: Learning with Mixture Models: Concepts and Applications. PKDD 2002: 512
64EEPadhraic Smyth, Daryl Pregibon, Christos Faloutsos: Data-driven evolution of data mining algorithms. Commun. ACM 45(8): 33-37 (2002)
63EEChidanand Apté, Bing Liu, Edwin P. D. Pednault, Padhraic Smyth: Business applications of data mining. Commun. ACM 45(8): 49-53 (2002)
62 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)
2001
61EEPadhraic Smyth: Breaking out of the Black-Box: Research Challenges in Data Mining. DMKD 2001
60EEDmitry Pavlov, Padhraic Smyth: Probabilistic query models for transaction data. KDD 2001: 164-173
59EEIgor V. Cadez, Padhraic Smyth, Heikki Mannila: Probabilistic modeling of transaction data with applications to profiling, visualization, and prediction. KDD 2001: 37-46
58EEIgor V. Cadez, Padhraic Smyth: Bayesian Predictive Profiles With Applications to Retail Transaction Data. NIPS 2001: 1353-1360
57 Xianping Ge, David Eppstein, Padhraic Smyth: The distribution of loop lengths in graphical models for turbo decoding. IEEE Transactions on Information Theory 47(6): 2549-2553 (2001)
2000
56EEHeikki Mannila, Padhraic Smyth: Approximate Query Answering with Frequent Sets and Maximum Entropy. ICDE 2000: 309
55EEIgor V. Cadez, Scott Gaffney, Padhraic Smyth: A general probabilistic framework for clustering individuals and objects. KDD 2000: 140-149
54EEIgor 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
53EEDmitry Pavlov, Darya Chudova, Padhraic Smyth: Towards scalable support vector machines using squashing. KDD 2000: 295-299
52EEXianping Ge, Padhraic Smyth: Deformable Markov model templates for time-series pattern matching. KDD 2000: 81-90
51 Igor V. Cadez, Padhraic Smyth: Model Complexity, Goodness of Fit and Diminishing Returns. NIPS 2000: 388-394
50EEDmitry Pavlov, Heikki Mannila, Padhraic Smyth: Probabilistic Models for Query Approximation with Large Sparse Binary Data Sets. UAI 2000: 465-472
49EEStephen 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)
1999
48 Igor V. Cadez, Christine E. McLaren, Padhraic Smyth, Geoffrey J. McLachlan: Hierarchical Models for Screening of Iron Deficiency Anemia. ICML 1999: 77-86
47EEHeikki Mannila, Dmitry Pavlov, Padhraic Smyth: Prediction with Local Patterns using Cross-Entropy. KDD 1999: 357-361
46EEScott Gaffney, Padhraic Smyth: Trajectory Clustering with Mixtures of Regression Models. KDD 1999: 63-72
45EEXianping Ge, Wanda Pratt, Padhraic Smyth: Discovering Chinese Words from Unsegmented Text (poster abstract). SIGIR 1999: 271-272
44EEXianping Ge, David Eppstein, Padhraic Smyth: The Distribution of Cycle Lengths in Graphical Models for Iterative Decoding CoRR cs.DM/9907002: (1999)
43 Padhraic Smyth, David Wolpert: Linearly Combining Density Estimators via Stacking. Machine Learning 36(1-2): 59-83 (1999)
1998
42 Gautam Das, King-Ip Lin, Heikki Mannila, Gopal Renganathan, Padhraic Smyth: Rule Discovery from Time Series. KDD 1998: 16-22
41 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)
1997
40 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
39 Eamonn J. Keogh, Padhraic Smyth: A Probabilistic Approach to Fast Pattern Matching in Time Series Databases. KDD 1997: 24-30
38 Padhraic Smyth, David Wolpert: Anytime Exploratory Data Analysis for Massive Data Sets. KDD 1997: 54-60
37 Padhraic Smyth, Michael Ghil, Kayo Ide, Joseph Roden, Andrew Fraser: Detecting Atmospheric Regimes Using Cross-Validated Clustering. KDD 1997: 61-66
36 Padhraic Smyth, David Wolpert: Stacked Density Estimation. NIPS 1997
35 Clark Glymour, David Madigan, Daryl Pregibon, Padhraic Smyth: Statistical Themes and Lessons for Data Mining. Data Min. Knowl. Discov. 1(1): 11-28 (1997)
34 Pat Langley, Gregory M. Provan, Padhraic Smyth: Learning with Probabilistic Representations. Machine Learning 29(2-3): 91-101 (1997)
33EEPadhraic Smyth, David Heckerman, Michael I. Jordan: Probabilistic Independence Networks for Hidden Markov Probability Models. Neural Computation 9(2): 227-269 (1997)
32EEPadhraic Smyth: Belief networks, hidden Markov models, and Markov random fields: A unifying view. Pattern Recognition Letters 18(11-13): 1261-1268 (1997)
1996
31 Usama M. Fayyad, Gregory Piatetsky-Shapiro, Padhraic Smyth, Ramasamy Uthurusamy: Advances in Knowledge Discovery and Data Mining. AAAI/MIT Press 1996
30 Padhraic Smyth: Clustering Using Monte Carlo Cross-Validation. KDD 1996: 126-133
29 Usama M. Fayyad, Gregory Piatetsky-Shapiro, Padhraic Smyth: Knowledge Discovery and Data Mining: Towards a Unifying Framework. KDD 1996: 82-88
28EEPadhraic Smyth: Clustering Sequences with Hidden Markov Models. NIPS 1996: 648-654
27 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
26 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
25 Usama M. Fayyad, Gregory Piatetsky-Shapiro, Padhraic Smyth: From Data Mining to Knowledge Discovery in Databases. AI Magazine 17(3): 37-54 (1996)
24EEUsama M. Fayyad, Gregory Piatetsky-Shapiro, Padhraic Smyth: The KDD Process for Extracting Useful Knowledge from Volumes of Data. Commun. ACM 39(11): 27-34 (1996)
23EEClark Glymour, David Madigan, Daryl Pregibon, Padhraic Smyth: Statistical Inference and Data Mining. Commun. ACM 39(11): 35-41 (1996)
22EEPadhraic Smyth: Bounds on the mean classification error rate of multiple experts. Pattern Recognition Letters 17(12): 1253-1257 (1996)
1995
21 Padhraic Smyth, Alexander Gray, Usama M. Fayyad: Retrofitting Decision Tree Classifiers Using Kernel Density Estimation. ICML 1995: 506-514
20 Usama M. Fayyad, Padhraic Smyth, Nicholas Weir, S. George Djorgovski: Automated Analysis and Exploration of Image Databases: Results, Progress, and Challenges. J. Intell. Inf. Syst. 4(1): 7-25 (1995)
1994
19 Usama M. Fayyad, Padhraic Smyth: The Automated Analysis, Cataloging, and Searching of Digital Image Libraries: A Machine Learning Approach. DL 1994: 225-249
18 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
17 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
16EEPadhraic Smyth, Usama M. Fayyad, Michael C. Burl, Pietro Perona, Pierre Baldi: Inferring Ground Truth from Subjective Labelling of Venus Images. NIPS 1994: 1085-1092
15 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)
14EEPadhraic Smyth: Hidden Markov models for fault detection in dynamic system. Pattern Recognition 27(1): 149-164 (1994)
1993
13EEPadhraic Smyth: Probabilistic Anomaly Detection in Dynamic Systems. NIPS 1993: 825-832
12 John W. Miller, Rodney M. Goodman, Padhraic Smyth: On loss functions which minimize to conditional expected values and posterior proba- bilities. IEEE Transactions on Information Theory 39(4): 1404- (1993)
11EEZheng Zeng, Rodney M. Goodman, Padhraic Smyth: Learning Finite State Machines With Self-Clustering Recurrent Networks. Neural Computation 5(6): 976-990 (1993)
1992
10 Padhraic Smyth, Jeff Mellstrom: Detecting Novel Classes with Applications to Fault Diagnosis. ML 1992: 416-425
9EEPadhraic Smyth, Rodney M. Goodman: An Information Theoretic Approach to Rule Induction from Databases. IEEE Trans. Knowl. Data Eng. 4(4): 301-316 (1992)
1991
8EEPadhraic Smyth, Jeff Mellstrom: Fault Diagnosis of Antenna Pointing Systems Using Hybrid Neural Network and Signal Processing Models. NIPS 1991: 667-674
7 Padhraic Smyth, Rodney M. Goodman: Rule Induction Using Information Theory. Knowledge Discovery in Databases 1991: 159-176
1990
6 Padhraic Smyth, Rodney M. Goodman, Charles M. Higgins: A Hybrid Rule-Based/Bayesian Classifier. ECAI 1990: 610-615
5EEPadhraic Smyth: On Stochastic Complexity and Admissible Models for Neural Network Classifiers. NIPS 1990: 818-824
1989
4 Rodney M. Goodman, Padhraic Smyth: The Induction of Probabilistic Rule Sets - The Itrule Algorithm. ML 1989: 129-132
1988
3 Rodney M. Goodman, Padhraic Smyth: Information-Theoretic Rule Induction. ECAI 1988: 357-362
2EERodney M. Goodman, John W. Miller, Padhraic Smyth: An Information Theoretic Approach to Rule-Based Connectionist Expert Systems. NIPS 1988: 256-263
1 Rodney M. Goodman, Padhraic Smyth: Decision tree design from a communication theory standpoint. IEEE Transactions on Information Theory 34(5): 979-994 (1988)

Coauthor Index

1Chidanand Apté [63]
2Lars Asker [41]
3Arthur Asuncion [101] [105] [106]
4Jayne Aubele [41]
5Pierre Baldi [16] [79]
6Stephen D. Bay [49]
7James Bennett [100]
8Michael C. Burl [16] [17] [18] [26] [41]
9Igor V. Cadez [48] [51] [54] [55] [58] [59] [62] [66] [68] [71]
10Erick Cantú-Paz [68]
11Chaitanya Chemudugunta [92] [94] [96] [102] [104] [107] [108]
12Darya Chudova [53] [67] [72] [73] [75] [76]
13Larry Crumpler [41]
14Gautam Das [42]
15S. George Djorgovski [20]
16Charles Elkan [100]
17David Eppstein [44] [57]
18Christos Faloutsos [64]
19Usama M. Fayyad [16] [17] [18] [19] [20] [21] [24] [25] [26] [27] [29] [31] [41]
20Paolo Frasconi [79]
21Andrew Fraser [37]
22Scott Gaffney [46] [55] [73] [76] [83]
23Xianping Ge [44] [45] [52] [57]
24Michael Ghil [37]
25Clark Glymour [23] [35]
26Rodney M. Goodman [1] [2] [3] [4] [6] [7] [9] [11] [12]
27Alexander Gray [21]
28Thomas L. Griffiths [80] [84]
29Kat Hagedorn [102]
30Christopher Hart [75]
31David Heckerman [33] [54] [71]
32Charles M. Higgins [6]
33America Holloway [107]
34Jon Hutchins [85] [95] [99]
35Kayo Ide [37]
36Alexander T. Ihler [91] [95] [99] [106]
37Alex Ihter [89]
38Michael I. Jordan [33]
39Chandrika Kamath [66] [68]
40Eamonn J. Keogh [39]
41Dennis F. Kibler [49]
42Seyoung Kim [82] [87] [88] [90] [93]
43Sergey Kirshner [66] [68] [78] [81] [103]
44Pat Langley [34]
45King-Ip Lin [42]
46Bing Liu [63] [100]
47Stefan Luther [82]
48David Madigan [23] [35]
49Subramani Mani [40]
50Heikki Mannila [42] [47] [50] [56] [59] [70]
51Christopher J. Matheus [15]
52Geoffrey J. McLachlan [48] [62]
53Christine E. McLaren [48] [62]
54Christopher Meek [54] [71]
55Jeff Mellstrom [8] [10]
56John W. Miller [2] [12]
57Eric Mjolsness [75] [76]
58David Newman [94] [96] [101] [102] [106]
59Joshua O'Madadhain [85]
60Sridevi Parise [78]
61Dmitry Pavlov [47] [50] [53] [60] [70] [74]
62Michael J. Pazzani [40] [49]
63Edwin P. D. Pednault [63]
64Pietro Perona [16] [17] [18] [26] [41]
65Gregory Piatetsky-Shapiro [15] [24] [25] [27] [29] [31]
66Ian Porteous [89] [106]
67Wanda Pratt [45]
68Daryl Pregibon [23] [35] [64]
69Gregory M. Provan [34]
70Gopal Renganathan [42]
71Andrew Robertson [81]
72Joseph Roden [37]
73Michal Rosen-Zvi [80] [84]
74William Rodman Shankle [40]
75Hal Stern [87] [93]
76Mark Steyvers [80] [84] [92] [96] [104] [107] [108]
77Domonkos Tikk [100]
78Jessica Turner [87]
79Ramasamy Uthurusamy [15] [31]
80Nicholas Weir [20]
81Max Welling [89] [101] [105] [106]
82Scott White [77] [86]
83Steven White [54] [71]
84David Wolpert (David H. Wolpert) [36] [38] [43]
85Zheng Zeng [11]

Colors in the list of coauthors

Copyright © Tue Nov 3 08:52:44 2009 by Michael Ley (ley@uni-trier.de)