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