Padhraic Smyth

268 papers A* 55A 39B 4C 2Misc 2Journal 111Unranked 49

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	A Generative Diffusion Model for Probabilistic Ensembles of Precipitation Maps Conditioned on Multisensor Satellite Observations. IEEE Trans. Geosci. Remote. Sens. Clément Guilloteau, Gavin Kerrigan, Kai Nelson, Giosue Migliorini, Padhraic Smyth, Runze Li, Efi Foufoula-Georgiou
2025	J	`jnl`	Bayesian Evaluation of Large Language Model Behavior. CoRR Rachel Longjohn, Shang Wu, Saatvik Kher, Catarina G. Belém, Padhraic Smyth
2025	A*	`conf`	Bayesian Inference for Correlated Human Experts and Classifiers. ICML Markelle Kelly, Alex James Boyd, Samuel Showalter, Mark Steyvers, Padhraic Smyth
2025	J	`jnl`	Bayesian Inference for Correlated Human Experts and Classifiers. CoRR Markelle Kelly, Alex Boyd, Samuel Showalter, Mark Steyvers, Padhraic Smyth
2025	J	`jnl`	Beyond Accuracy: Are Time Series Foundation Models Well-Calibrated? CoRR Coen Adler, Yuxin Chang, Felix Draxler, Samar Abdi, Padhraic Smyth
2025	A*	`conf`	ELBOing Stein: Variational Bayes with Stein Mixture Inference. ICLR Ola Rønning, Eric T. Nalisnick, Christophe Ley, Padhraic Smyth, Thomas Hamelryck
2025	J	`jnl`	Efficient Inference for Coupled Hidden Markov Models in Continuous Time and Discrete Space. CoRR Giosue Migliorini, Padhraic Smyth
2025	J	`jnl`	Improving Metacognition and Uncertainty Communication in Language Models. CoRR Mark Steyvers, Catarina G. Belém, Padhraic Smyth
2025	J	`jnl`	JANET: Joint Adaptive predictioN-region Estimation for Time-series. Mach. Learn. Eshant English, Eliot Wong-Toi, Matteo Fontana, Stephan Mandt, Padhraic Smyth, Christoph Lippert
2025	J	`jnl`	Semantic Probabilistic Control of Language Models. CoRR Kareem Ahmed, Catarina G. Belém, Padhraic Smyth, Sameer Singh
2025	J	`jnl`	Shifting norms in scholarly publications: trends in readability, objectivity, authorship, and AI use. CoRR Padraig Cunningham, Padhraic Smyth, Barry Smyth
2025	—	`conf`	Understanding Gender Bias in AI-Generated Product Descriptions. FAccT Markelle Kelly, Mohammad Tahaei, Padhraic Smyth, Lauren Wilcox
2025	J	`jnl`	Understanding Gender Bias in AI-Generated Product Descriptions. CoRR Markelle Kelly, Mohammad Tahaei, Padhraic Smyth, Lauren Wilcox
2025	J	`jnl`	What large language models know and what people think they know. Nat. Mac. Intell. Mark Steyvers, Heliodoro Tejeda Lemus, Aakriti Kumar, Catarina G. Belém, Sheer Karny, Xinyue Hu, Lukas William Mayer, Padhraic Smyth
2024	J	`jnl`	Anomaly Detection of Tabular Data Using LLMs. CoRR Aodong Li, Yunhan Zhao, Chen Qiu, Marius Kloft, Padhraic Smyth, Maja Rudolph, Stephan Mandt
2024	A	`conf`	Bayesian Online Learning for Consensus Prediction. AISTATS Samuel Showalter, Alex J. Boyd, Padhraic Smyth, Mark Steyvers
2024	A*	`conf`	Benchmark Data Repositories for Better Benchmarking. NeurIPS Rachel Longjohn, Markelle Kelly, Sameer Singh, Padhraic Smyth
2024	J	`jnl`	Benchmark Data Repositories for Better Benchmarking. CoRR Rachel Longjohn, Markelle Kelly, Sameer Singh, Padhraic Smyth
2024	J	`jnl`	Deep Linear Hawkes Processes. CoRR Yuxin Chang, Alex Boyd, Cao Xiao, Taha A. Kass-Hout, Parminder Bhatia, Padhraic Smyth, Andrew Warrington
2024	A*	`conf`	Dynamic Conditional Optimal Transport through Simulation-Free Flows. NeurIPS Gavin Kerrigan, Giosue Migliorini, Padhraic Smyth
2024	J	`jnl`	Dynamic Conditional Optimal Transport through Simulation-Free Flows. CoRR Gavin Kerrigan, Giosue Migliorini, Padhraic Smyth
2024	J	`jnl`	ELBOing Stein: Variational Bayes with Stein Mixture Inference. CoRR Ola Rønning, Eric T. Nalisnick, Christophe Ley, Padhraic Smyth, Thomas Hamelryck
2024	J	`jnl`	EventFlow: Forecasting Continuous-Time Event Data with Flow Matching. CoRR Gavin Kerrigan, Kai Nelson, Padhraic Smyth
2024	A	`conf`	Functional Flow Matching. AISTATS Gavin Kerrigan, Giosue Migliorini, Padhraic Smyth
2024	J	`jnl`	JANET: Joint Adaptive predictioN-region Estimation for Time-series. CoRR Eshant English, Eliot Wong-Toi, Matteo Fontana, Stephan Mandt, Padhraic Smyth, Christoph Lippert
2024	A*	`conf`	Perceptions of Linguistic Uncertainty by Language Models and Humans. EMNLP Catarina G. Belém, Markelle Kelly, Mark Steyvers, Sameer Singh, Padhraic Smyth
2024	J	`jnl`	Perceptions of Linguistic Uncertainty by Language Models and Humans. CoRR Catarina G. Belém, Markelle Kelly, Mark Steyvers, Sameer Singh, Padhraic Smyth
2024	A	`conf`	Probabilistic Modeling for Sequences of Sets in Continuous-Time. AISTATS Yuxin Chang, Alex J. Boyd, Padhraic Smyth
2024	J	`jnl`	The Calibration Gap between Model and Human Confidence in Large Language Models. CoRR Mark Steyvers, Heliodoro Tejeda Lemus, Aakriti Kumar, Catarina G. Belém, Sheer Karny, Xinyue Hu, Lukas William Mayer, Padhraic Smyth
2023	J	`jnl`	A cell-level discriminative neural network model for diagnosis of blood cancers. Bioinform. Edgar E. Robles, Ye Jin, Padhraic Smyth, Richard H. Scheuermann, Jack D. Bui, Huan-You Wang, Jean Oak, Yu Qian
2023	J	`jnl`	Bayesian Online Learning for Consensus Prediction. CoRR Samuel Showalter, Alex Boyd, Padhraic Smyth, Mark Steyvers
2023	—	`conf`	Capturing Humans' Mental Models of AI: An Item Response Theory Approach. FAccT Markelle Kelly, Aakriti Kumar, Padhraic Smyth, Mark Steyvers
2023	J	`jnl`	Capturing Humans' Mental Models of AI: An Item Response Theory Approach. CoRR Markelle Kelly, Aakriti Kumar, Padhraic Smyth, Mark Steyvers
2023	A*	`conf`	Deep Anomaly Detection under Labeling Budget Constraints. ICML Aodong Li, Chen Qiu, Marius Kloft, Padhraic Smyth, Stephan Mandt, Maja Rudolph
2023	J	`jnl`	Deep Anomaly Detection under Labeling Budget Constraints. CoRR Aodong Li, Chen Qiu, Padhraic Smyth, Marius Kloft, Stephan Mandt, Maja Rudolph
2023	A	`conf`	Diffusion Generative Models in Infinite Dimensions. AISTATS Gavin Kerrigan, Justin Ley, Padhraic Smyth
2023	J	`jnl`	Functional Flow Matching. CoRR Gavin Kerrigan, Giosue Migliorini, Padhraic Smyth
2023	A	`conf`	Inference for mark-censored temporal point processes. UAI Alex Boyd, Yuxin Chang, Stephan Mandt, Padhraic Smyth
2023	J	`jnl`	Probabilistic Modeling for Sequences of Sets in Continuous-Time. CoRR Yuxin Chang, Alex Boyd, Padhraic Smyth
2023	A	`conf`	Probabilistic Querying of Continuous-Time Event Sequences. AISTATS Alex Boyd, Yuxin Chang, Stephan Mandt, Padhraic Smyth
2023	A*	`conf`	Variable-Based Calibration for Machine Learning Classifiers. AAAI Markelle Kelly, Padhraic Smyth
2023	—	`conf`	When More is Less: Incorporating Additional Datasets Can Hurt Performance By Introducing Spurious Correlations. MLHC Hyungrok Do, Yuxin Chang, Yoon-Sang Cho, Padhraic Smyth, Judy Zhong
2023	A*	`conf`	Zero-Shot Anomaly Detection via Batch Normalization. NeurIPS Aodong Li, Chen Qiu, Marius Kloft, Padhraic Smyth, Maja Rudolph, Stephan Mandt
2023	J	`jnl`	Zero-Shot Anomaly Detection without Foundation Models. CoRR Aodong Li, Chen Qiu, Marius Kloft, Padhraic Smyth, Maja Rudolph, Stephan Mandt
2022	J	`jnl`	Automating data science. Commun. ACM Tijl De Bie, Luc De Raedt, José Hernández-Orallo, Holger H. Hoos, Padhraic Smyth, Christopher K. I. Williams
2022	J	`jnl`	Diffusion Generative Models in Infinite Dimensions. CoRR Gavin Kerrigan, Justin Ley, Padhraic Smyth
2022	A*	`conf`	Fair Generalized Linear Models with a Convex Penalty. ICML Hyungrok Do, Preston Putzel, Axel S. Martin, Padhraic Smyth, Judy Zhong
2022	J	`jnl`	Fair Generalized Linear Models with a Convex Penalty. CoRR Hyungrok Do, Preston Putzel, Axel S. Martin, Padhraic Smyth, Judy Zhong
2022	A*	`conf`	Predictive Querying for Autoregressive Neural Sequence Models. NeurIPS Alex Boyd, Samuel Showalter, Stephan Mandt, Padhraic Smyth
2022	J	`jnl`	Predictive Querying for Autoregressive Neural Sequence Models. CoRR Alex Boyd, Samuel Showalter, Stephan Mandt, Padhraic Smyth
2022	J	`jnl`	Probabilistic Querying of Continuous-Time Event Sequences. CoRR Alex Boyd, Yuxin Chang, Stephan Mandt, Padhraic Smyth
2022	J	`jnl`	Variable-Based Calibration for Machine Learning Classifiers. CoRR Markelle Kelly, Padhraic Smyth
2021	A*	`conf`	Active Bayesian Assessment of Black-Box Classifiers. AAAI Disi Ji, Robert L. Logan IV, Padhraic Smyth, Mark Steyvers
2021	J	`jnl`	Automating Data Science: Prospects and Challenges. CoRR Tijl De Bie, Luc De Raedt, José Hernández-Orallo, Holger H. Hoos, Padhraic Smyth, Christopher K. I. Williams
2021	A*	`conf`	Combining Human Predictions with Model Probabilities via Confusion Matrices and Calibration. NeurIPS Gavin Kerrigan, Padhraic Smyth, Mark Steyvers
2021	J	`jnl`	Combining Human Predictions with Model Probabilities via Confusion Matrices and Calibration. CoRR Gavin Kerrigan, Padhraic Smyth, Mark Steyvers
2021	A*	`conf`	Detecting and Adapting to Irregular Distribution Shifts in Bayesian Online Learning. NeurIPS Aodong Li, Alex Boyd, Padhraic Smyth, Stephan Mandt
2021	—	`conf`	Dynamic Survival Analysis for EHR Data with Personalized Parametric Distributions. MLHC Preston Putzel, Hyungrok Do, Alex Boyd, Hua Zhong, Padhraic Smyth
2021	—	`conf`	Dynamic Survival Analysis with Individualized Truncated Parametric Distributions. SPACA Preston Putzel, Padhraic Smyth, Jaehong Yu, Hua Zhong
2020	J	`jnl`	Active Bayesian Assessment for Black-Box Classifiers. CoRR Disi Ji, Robert L. Logan IV, Padhraic Smyth, Mark Steyvers
2020	A*	`conf`	Can I Trust My Fairness Metric? Assessing Fairness with Unlabeled Data and Bayesian Inference. NeurIPS Disi Ji, Padhraic Smyth, Mark Steyvers
2020	J	`jnl`	Can I Trust My Fairness Metric? Assessing Fairness with Unlabeled Data and Bayesian Inference. CoRR Disi Ji, Padhraic Smyth, Mark Steyvers
2020	J	`jnl`	Forecasting Daily Wildfire Activity Using Poisson Regression. IEEE Trans. Geosci. Remote. Sens. Casey A. Graff, Shane R. Coffield, Yang Chen, Efi Foufoula-Georgiou, James T. Randerson, Padhraic Smyth
2020	J	`jnl`	Statistical Methods for the Forensic Analysis of Geolocated Event Data. Digit. Investig. Christopher Galbraith, Padhraic Smyth, Hal S. Stern
2020	A*	`conf`	User-Dependent Neural Sequence Models for Continuous-Time Event Data. NeurIPS Alex Boyd, Robert Bamler, Stephan Mandt, Padhraic Smyth
2020	J	`jnl`	User-Dependent Neural Sequence Models for Continuous-Time Event Data. CoRR Alex Boyd, Robert Bamler, Stephan Mandt, Padhraic Smyth
2020	J	`jnl`	Variational Beam Search for Online Learning with Distribution Shifts. CoRR Aodong Li, Alex Boyd, Padhraic Smyth, Stephan Mandt
2019	J	`jnl`	Detecting conversation topics in primary care office visits from transcripts of patient-provider interactions. J. Am. Medical Informatics Assoc. Jihyun Park, Dimitrios Kotzias, Patty Kuo, Robert L. Logan IV, Kritzia Merced, Sameer Singh, Michael Tanana, Efi Karra Taniskidou, Jennifer Elston-Lafata, David C. Atkins, Ming Tai-Seale, Zac E. Imel, Padhraic Smyth
2019	A*	`conf`	Dropout as a Structured Shrinkage Prior. ICML Eric T. Nalisnick, José Miguel Hernández-Lobato, Padhraic Smyth
2019	J	`jnl`	Predicting Consumption Patterns with Repeated and Novel Events. IEEE Trans. Knowl. Data Eng. Dimitrios Kotzias, Moshe Lichman, Padhraic Smyth
2018	J	`jnl`	Automating Data Science (Dagstuhl Seminar 18401). Dagstuhl Reports Tijl De Bie, Luc De Raedt, Holger H. Hoos, Padhraic Smyth
2018	—	`conf`	Bayesian Trees for Automated Cytometry Data Analysis. MLHC Disi Ji, Eric T. Nalisnick, Yu Qian, Richard H. Scheuermann, Padhraic Smyth
2018	A	`conf`	Learning Priors for Invariance. AISTATS Eric T. Nalisnick, Padhraic Smyth
2018	A*	`conf`	Prediction of Sparse User-Item Consumption Rates with Zero-Inflated Poisson Regression. WWW Moshe Lichman, Padhraic Smyth
2018	B	`conf`	Understanding Student Procrastination via Mixture Models. EDM Jihyun Park, Renzhe Yu, Fernando Rodriguez, Rachel B. Baker, Padhraic Smyth, Mark Warschauer
2018	J	`jnl`	Unifying the Dropout Family Through Structured Shrinkage Priors. CoRR Eric T. Nalisnick, Padhraic Smyth
2017	J	`jnl`	Analyzing user-event data using score-based likelihood ratios with marked point processes. Digit. Investig. Christopher Galbraith, Padhraic Smyth
2017	J	`jnl`	Content Coding of Psychotherapy Transcripts Using Labeled Topic Models. IEEE J. Biomed. Health Informatics Garren Gaut, Mark Steyvers, Zac E. Imel, David C. Atkins, Padhraic Smyth
2017	A	`conf`	Detecting changes in student behavior from clickstream data. LAK Jihyun Park, Kameryn Denaro, Fernando Rodriguez, Padhraic Smyth, Mark Warschauer
2017	A	`conf`	Learning Approximately Objective Priors. UAI Eric T. Nalisnick, Padhraic Smyth
2017	J	`jnl`	Science and data science. Proc. Natl. Acad. Sci. USA David M. Blei, Padhraic Smyth
2017	—	`conf`	Stick-Breaking Variational Autoencoders. ICLR (Poster) Eric T. Nalisnick, Padhraic Smyth
2017	—	`conf`	Variational Reference Priors. ICLR (Workshop) Eric T. Nalisnick, Padhraic Smyth
2016	—	`conf`	Analyzing NIH Funding Patterns over Time with Statistical Text Analysis. AAAI Workshop: Scholarly Big Data Jihyun Park, Margaret Blume-Kohout, Ralf Krestel, Eric T. Nalisnick, Padhraic Smyth
2016	J	`jnl`	Bayesian Detection of Changepoints in Finite-State Markov Chains for Multiple Sequences. Technometrics Petter Arnesen, Tracy Holsclaw, Padhraic Smyth
2016	—	`conf`	Personalized location models with adaptive mixtures. SIGSPATIAL/GIS Moshe Lichman, Dimitrios Kotzias, Padhraic Smyth
2015	A*	`conf`	From Group to Individual Labels Using Deep Features. KDD Dimitrios Kotzias, Misha Denil, Nando de Freitas, Padhraic Smyth
2015	—	`conf`	Hot Swapping for Online Adaptation of Optimization Hyperparameters. ICLR (Workshop) Kevin Bache, Dennis DeCoste, Padhraic Smyth
2015	A	`conf`	Modeling Response Time in Digital Human Communication. ICWSM Nicholas Martin Navaroli, Padhraic Smyth
2015	—	`conf`	Recursive Neural Networks for Coding Therapist and Patient Behavior in Motivational Interviewing. CLPsych@HLT-NAACL Michael Tanana, Kevin Hallgren, Zac E. Imel, David C. Atkins, Padhraic Smyth, Vivek Srikumar
2014	A	`conf`	Annealing Paths for the Evaluation of Topic Models. UAI James R. Foulds, Padhraic Smyth
2014	A	`conf`	Approximate Slice Sampling for Bayesian Posterior Inference. AISTATS Christopher DuBois, Anoop Korattikara Balan, Max Welling, Padhraic Smyth
2014	J	`jnl`	Beyond MAP Estimation With the Track-Oriented Multiple Hypothesis Tracker. IEEE Trans. Signal Process. Andrew J. Frank, Padhraic Smyth, Alexander Ihler
2014	A*	`conf`	Modeling human location data with mixtures of kernel densities. KDD Moshe Lichman, Padhraic Smyth
2013	A*	`conf`	Modeling Scientific Impact with Topical Influence Regression. EMNLP James R. Foulds, Padhraic Smyth
2013	J	`jnl`	Modeling individual email patterns over time with latent variable models. Mach. Learn. Nicholas Navaroli, Christopher DuBois, Padhraic Smyth
2013	J	`jnl`	Probabilistic Models for Query Approximation with Large Sparse Binary Datasets CoRR Dmitry Pavlov, Heikki Mannila, Padhraic Smyth
2013	J	`jnl`	Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence (2013). CoRR Ann E. Nicholson, Padhraic Smyth
2013	A	`ed.`	Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, UAI 2013, Bellevue, WA, USA, August 11-15, 2013 UAI Ann E. Nicholson, Padhraic Smyth
2013	A	`conf`	Recommending patents based on latent topics. RecSys Ralf Krestel, Padhraic Smyth
2013	J	`jnl`	Stochastic Collapsed Variational Bayesian Inference for Latent Dirichlet Allocation CoRR James R. Foulds, Levi Boyles, Christopher DuBois, Padhraic Smyth, Max Welling
2013	A	`conf`	Stochastic blockmodeling of relational event dynamics. AISTATS Christopher DuBois, Carter T. Butts, Padhraic Smyth
2013	A*	`conf`	Stochastic collapsed variational Bayesian inference for latent Dirichlet allocation. KDD James R. Foulds, Levi Boyles, Christopher DuBois, Padhraic Smyth, Max Welling
2013	A*	`conf`	Text-based measures of document diversity. KDD Kevin Bache, David Newman, Padhraic Smyth
2013	A*	`conf`	Windows into Relational Events: Data Structures for Contiguous Subsequences of Edges. SODA Michael J. Bannister, Christopher DuBois, David Eppstein, Padhraic Smyth
2012	—	`conf`	A graphical model representation of the track-oriented multiple hypothesis tracker. SSP Andrew J. Frank, Padhraic Smyth, Alexander Ihler
2012	—	`conf`	Analyzing Text and Social Network Data with Probabilistic Models. ECML/PKDD (1) Padhraic Smyth
2012	J	`jnl`	Conditional Chow-Liu Tree Structures for Modeling Discrete-Valued Vector Time Series CoRR Sergey Kirshner, Padhraic Smyth, Andrew Robertson
2012	J	`jnl`	Gibbs Sampling for (Coupled) Infinite Mixture Models in the Stick Breaking Representation. CoRR Ian Porteous, Alexander T. Ihler, Padhraic Smyth, Max Welling
2012	J	`jnl`	Modeling Waveform Shapes with Random Eects Segmental Hidden Markov Models CoRR Seyoung Kim, Padhraic Smyth, Stefan Luther
2012	J	`jnl`	On Smoothing and Inference for Topic Models CoRR Arthur U. Asuncion, Max Welling, Padhraic Smyth, Yee Whye Teh
2012	—	`conf`	Predictive modeling of cardiovascular complications in incident hemodialysis patients. EMBC Jasmine Ion Titapiccolo, Manuela Ferrario, Carlo Barbieri, Daniele Marcelli, Flavio Mari, Emanuele Gatti, Sergio Cerutti, Padhraic Smyth, Maria G. Signorini
2012	J	`jnl`	Special issue on best of SIGKDD 2011. ACM Trans. Knowl. Discov. Data Joydeep Ghosh, Padhraic Smyth, Andrew Tomkins, Rich Caruana
2012	C	`conf`	Statistical Models for Exploring Individual Email Communication Behavior. ACML Nicholas Navaroli, Christopher DuBois, Padhraic Smyth
2012	J	`jnl`	Statistical topic models for multi-label document classification. Mach. Learn. Timothy N. Rubin, America Chambers, Padhraic Smyth, Mark Steyvers
2012	J	`jnl`	The Author-Topic Model for Authors and Documents CoRR Michal Rosen-Zvi, Thomas L. Griffiths, Mark Steyvers, Padhraic Smyth
2012	J	`jnl`	TopicNets: Visual Analysis of Large Text Corpora with Topic Modeling. ACM Trans. Intell. Syst. Technol. Brynjar Gretarsson, John O'Donovan, Svetlin Bostandjiev, Tobias Höllerer, Arthur U. Asuncion, David Newman, Padhraic Smyth
2012	J	`jnl`	Windows into Relational Events: Data Structures for Contiguous Subsequences of Edges CoRR Michael J. Bannister, Christopher DuBois, David Eppstein, Padhraic Smyth
2011	A	`conf`	A Dynamic Relational Infinite Feature Model for Longitudinal Social Networks. AISTATS James R. Foulds, Christopher DuBois, Arthur U. Asuncion, Carter T. Butts, Padhraic Smyth
2011	J	`jnl`	Combining Background Knowledge and Learned Topics. Top. Cogn. Sci. Mark Steyvers, Padhraic Smyth, Chaitanya Chemudugunta
2011	—	`conf`	Continuous-Time Regression Models for Longitudinal Networks. NIPS Duy Quang Vu, Arthur U. Asuncion, David R. Hunter, Padhraic Smyth
2011	A*	`conf`	Dynamic Egocentric Models for Citation Networks. ICML Duy Quang Vu, Arthur U. Asuncion, David R. Hunter, Padhraic Smyth
2011	A	`conf`	Latent Set Models for Two-Mode Network Data. ICWSM Christopher DuBois, James R. Foulds, Padhraic Smyth
2011	A	`conf`	Multi-Instance Mixture Models. SDM James R. Foulds, Padhraic Smyth
2011	A*	`ed.`	Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Diego, CA, USA, August 21-24, 2011 KDD Chid Apté, Joydeep Ghosh, Padhraic Smyth
2011	A	`conf`	Revisiting MAP Estimation, Message Passing and Perfect Graphs. AISTATS James R. Foulds, Nicholas Navaroli, Padhraic Smyth, Alexander Ihler
2011	J	`jnl`	Statistical Topic Models for Multi-Label Document Classification CoRR Timothy N. Rubin, America Chambers, Padhraic Smyth, Mark Steyvers
2010	J	`jnl`	A Bayesian Mixture Approach to Modeling Spatial Activation Patterns in Multisite fMRI Data. IEEE Trans. Medical Imaging Seyoung Kim, Padhraic Smyth, Hal S. Stern
2010	J	`jnl`	Estimating replicate time shifts using Gaussian process regression. Bioinform. Qiang Liu, Kevin K. Lin, Bogi Andersen, Padhraic Smyth, Alexander Ihler
2010	J	`jnl`	Learning author-topic models from text corpora. ACM Trans. Inf. Syst. Michal Rosen-Zvi, Chaitanya Chemudugunta, Thomas L. Griffiths, Padhraic Smyth, Mark Steyvers
2010	—	`conf`	Learning concept graphs from text with stick-breaking priors. NIPS America Chambers, Padhraic Smyth, Mark Steyvers
2010	A	`conf`	Learning with Blocks: Composite Likelihood and Contrastive Divergence. AISTATS Arthur U. Asuncion, Qiang Liu, Alexander Ihler, Padhraic Smyth
2010	A*	`conf`	Modeling relational events via latent classes. KDD Christopher DuBois, Padhraic Smyth
2010	A*	`conf`	Particle Filtered MCMC-MLE with Connections to Contrastive Divergence. ICML Arthur U. Asuncion, Qiang Liu, Alexander T. Ihler, Padhraic Smyth
2010	J	`jnl`	Technical perspective - Creativity helps influence prediction precision. Commun. ACM Padhraic Smyth, Charles Elkan
2009	J	`jnl`	Bayesian detection of non-sinusoidal periodic patterns in circadian expression data. Bioinform. Darya Chudova, Alexander Ihler, Kevin K. Lin, Bogi Andersen, Padhraic Smyth
2009	J	`jnl`	Distributed Algorithms for Topic Models. J. Mach. Learn. Res. David Newman, Arthur U. Asuncion, Padhraic Smyth, Max Welling
2009	A	`conf`	On Smoothing and Inference for Topic Models. UAI Arthur U. Asuncion, Max Welling, Padhraic Smyth, Yee Whye Teh
2009	—	`conf`	Particle-based Variational Inference for Continuous Systems. NIPS Alexander Ihler, Andrew J. Frank, Padhraic Smyth
2008	—	`conf`	Asynchronous Distributed Learning of Topic Models. NIPS Arthur U. Asuncion, Padhraic Smyth, Max Welling
2008	A	`conf`	Combining concept hierarchies and statistical topic models. CIKM Chaitanya Chemudugunta, Padhraic Smyth, Mark Steyvers
2008	A*	`conf`	Fast collapsed gibbs sampling for latent dirichlet allocation. KDD Ian Porteous, David Newman, Alexander Ihler, Arthur U. Asuncion, Padhraic Smyth, Max Welling
2008	Misc	`conf`	Modeling Documents by Combining Semantic Concepts with Unsupervised Statistical Learning. ISWC Chaitanya Chemudugunta, America Holloway, Padhraic Smyth, Mark Steyvers
2008	—	`conf`	Probabilistic Analysis of a Large-Scale Urban Traffic Sensor Data Set. KDD Workshop on Knowledge Discovery from Sensor Data Jon Hutchins, Alexander Ihler, Padhraic Smyth
2008	J	`jnl`	Text Modeling using Unsupervised Topic Models and Concept Hierarchies CoRR Chaitanya Chemudugunta, Padhraic Smyth, Mark Steyvers
2007	—	`conf`	Distributed Inference for Latent Dirichlet Allocation. NIPS David Newman, Arthur U. Asuncion, Padhraic Smyth, Max Welling
2007	A*	`conf`	Infinite mixtures of trees. ICML Sergey Kirshner, Padhraic Smyth
2007	J	`jnl`	KDD Cup and workshop 2007. SIGKDD Explor. James Bennett, Charles Elkan, Bing Liu, Padhraic Smyth, Domonkos Tikk
2007	J	`jnl`	Learning to detect events with Markov-modulated poisson processes. ACM Trans. Knowl. Discov. Data Alexander T. Ihler, Jon Hutchins, Padhraic Smyth
2007	—	`conf`	Subject metadata enrichment using statistical topic models. JCDL David Newman, Kat Hagedorn, Chaitanya Chemudugunta, Padhraic Smyth
2006	—	`conf`	A Nonparametric Bayesian Approach to Detecting Spatial Activation Patterns in fMRI Data. MICCAI (2) Seyoung Kim, Padhraic Smyth, Hal S. Stern
2006	A*	`conf`	Adaptive event detection with time-varying poisson processes. KDD Alexander Ihler, Jon Hutchins, Padhraic Smyth
2006	C	`conf`	Analyzing Entities and Topics in News Articles Using Statistical Topic Models. ISI David Newman, Chaitanya Chemudugunta, Padhraic Smyth, Mark Steyvers
2006	B	`conf`	Data-Driven Discovery Using Probabilistic Hidden Variable Models. ALT Padhraic Smyth
2006	B	`conf`	Data-Driven Discovery Using Probabilistic Hidden Variable Models. Discovery Science Padhraic Smyth
2006	A	`conf`	Gibbs Sampling for (Coupled) Infinite Mixture Models in the Stick Breaking Representation. UAI Ian Porteous, Alexander T. Ihler, Padhraic Smyth, Max Welling
2006	—	`conf`	Hierarchical Dirichlet Processes with Random Effects. NIPS Seyoung Kim, Padhraic Smyth
2006	J	`jnl`	Imaging phenotypes and genotypes in schizophrenia. Neuroinformatics Jessica A. Turner, Padhraic Smyth, Fabio Macciardi, James H. Fallon, James L. Kennedy, Steven G. Potkin
2006	—	`conf`	Learning Time-Intensity Profiles of Human Activity using Non-Parametric Bayesian Models. NIPS Alexander T. Ihler, Padhraic Smyth
2006	—	`conf`	Modeling General and Specific Aspects of Documents with a Probabilistic Topic Model. NIPS Chaitanya Chemudugunta, Padhraic Smyth, Mark Steyvers
2006	J	`jnl`	Segmental Hidden Markov Models with Random Effects for Waveform Modeling. J. Mach. Learn. Res. Seyoung Kim, Padhraic Smyth
2006	A*	`conf`	Statistical entity-topic models. KDD David Newman, Chaitanya Chemudugunta, Padhraic Smyth
2005	A	`conf`	A Spectral Clustering Approach To Finding Communities in Graph. SDM Scott White, Padhraic Smyth
2005	—	`conf`	EventRank: a framework for ranking time-varying networks. LinkKDD Joshua O'Madadhain, Padhraic Smyth
2005	A	`conf`	Parametric Response Surface Models for Analysis of Multi-site fMRI Data. MICCAI Seyoung Kim, Padhraic Smyth, Hal S. Stern, Jessica A. Turner
2005	J	`jnl`	Prediction and ranking algorithms for event-based network data. SIGKDD Explor. Joshua O'Madadhain, Jon Hutchins, Padhraic Smyth
2004	A	`conf`	Conditional Chow-Liu Tree Structures for Modeling Discrete-Valued Vector Time Series. UAI Sergey Kirshner, Padhraic Smyth, Andrew Robertson
2004	J	`jnl`	Identification of hair cycle-associated genes from time-course gene expression profile data by using replicate variance. Proc. Natl. Acad. Sci. USA Kevin K. Lin, Darya Chudova, G. Wesley Hatfield, Padhraic Smyth, Bogi Andersen
2004	—	`conf`	Joint Probabilistic Curve Clustering and Alignment. NIPS Scott Gaffney, Padhraic Smyth
2004	A	`conf`	Modeling Waveform Shapes with Random E ects Segmental Hidden Markov Models. UAI Seyoung Kim, Padhraic Smyth, Stefan Luther
2004	A*	`conf`	Probabilistic author-topic models for information discovery. KDD Mark Steyvers, Padhraic Smyth, Michal Rosen-Zvi, Thomas Griffiths
2004	A	`conf`	The Author-Topic Model for Authors and Documents. UAI Michal Rosen-Zvi, Thomas L. Griffiths, Mark Steyvers, Padhraic Smyth
2003	A*	`conf`	Algorithms for estimating relative importance in networks. KDD Scott White, Padhraic Smyth
2003	J	`jnl`	Analysis of Pattern Discovery in Sequences Using a Bayes Error Framework. Data Min. Knowl. Discov. Darya Chudova, Padhraic Smyth
2003	A	`conf`	Approximate Query Answering by Model Averaging. SDM Dmitry Pavlov, Padhraic Smyth
2003	J	`jnl`	Beyond Independence: Probabilistic Models for Query Approximation on Binary Transaction Data. IEEE Trans. Knowl. Data Eng. Dmitry Pavlov, Heikki Mannila, Padhraic Smyth
2003	A	`conf`	Clustering Markov States into Equivalence Classes using SVD and Heuristic Search Algorithms. AISTATS Xianping Ge, Sridevi Parise, Padhraic Smyth
2003	A	`conf`	Curve Clustering with Random Effects Regression Mixtures. AISTATS Scott Gaffney, Padhraic Smyth
2003	—	`conf`	Gene Expression Clustering with Functional Mixture Models. NIPS Darya Chudova, Christopher E. Hart, Eric Mjolsness, Padhraic Smyth
2003	J	`jnl`	Model-Based Clustering and Visualization of Navigation Patterns on a Web Site. Data Min. Knowl. Discov. Igor V. Cadez, David Heckerman, Christopher Meek, Padhraic Smyth, Steven White
2003	—	`book`	Modeling the Internet and the Web: Probabilistic Method and Algorithms Pierre Baldi, Paolo Frasconi, Padhraic Smyth
2003	A	`conf`	Probabilistic Models For Joint Clustering And Time-Warping Of Multidimensional Curves. UAI Darya Chudova, Scott Gaffney, Padhraic Smyth
2003	A*	`conf`	Translation-invariant mixture models for curve clustering. KDD Darya Chudova, Scott Gaffney, Eric Mjolsness, Padhraic Smyth
2003	A*	`conf`	Unsupervised Learning with Permuted Data. ICML Sergey Kirshner, Sridevi Parise, Padhraic Smyth
2002	J	`jnl`	Business applications of data mining. Commun. ACM Chidanand Apté, Bing Liu, Edwin P. D. Pednault, Padhraic Smyth
2002	J	`jnl`	Data-driven evolution of data mining algorithms. Commun. ACM Padhraic Smyth, Daryl Pregibon, Christos Faloutsos
2002	—	`conf`	Learning to Classify Galaxy Shapes Using the EM Algorithm. NIPS Sergey Kirshner, Igor V. Cadez, Padhraic Smyth, Chandrika Kamath
2002	—	`conf`	Learning with Mixture Models: Concepts and Applications. ECML Padhraic Smyth
2002	—	`conf`	Learning with Mixture Models: Concepts and Applications. PKDD Padhraic Smyth
2002	J	`jnl`	Maximum Likelihood Estimation of Mixture Densities for Binned and Truncated Multivariate Data. Mach. Learn. Igor V. Cadez, Padhraic Smyth, Geoffrey J. McLachlan, Christine E. McLaren
2002	A*	`conf`	Pattern discovery in sequences under a Markov assumption. KDD Darya Chudova, Padhraic Smyth
2002	—	`conf`	Probabilistic Model-Based Detection of Bent-Double Radio Galaxies. ICPR (2) Sergey Kirshner, Igor V. Cadez, Padhraic Smyth, Chandrika Kamath, Erick Cantú-Paz
2001	—	`conf`	Bayesian Predictive Profiles With Applications to Retail Transaction Data. NIPS Igor V. Cadez, Padhraic Smyth
2001	—	`conf`	Breaking out of the Black-Box: Research Challenges in Data Mining. DMKD Padhraic Smyth
2001	—	`book`	Principles of Data Mining David J. Hand, Heikki Mannila, Padhraic Smyth
2001	A*	`conf`	Probabilistic modeling of transaction data with applications to profiling, visualization, and prediction. KDD Igor V. Cadez, Padhraic Smyth, Heikki Mannila
2001	A*	`conf`	Probabilistic query models for transaction data. KDD Dmitry Pavlov, Padhraic Smyth
2001	J	`jnl`	The distribution of loop lengths in graphical models for turbo decoding. IEEE Trans. Inf. Theory Xianping Ge, David Eppstein, Padhraic Smyth
2000	A*	`conf`	A general probabilistic framework for clustering individuals and objects. KDD Igor V. Cadez, Scott Gaffney, Padhraic Smyth
2000	A*	`conf`	Approximate Query Answering with Frequent Sets and Maximum Entropy. ICDE Heikki Mannila, Padhraic Smyth
2000	A*	`conf`	Deformable Markov model templates for time-series pattern matching. KDD Xianping Ge, Padhraic Smyth
2000	—	`conf`	Model Complexity, Goodness of Fit and Diminishing Returns. NIPS Igor V. Cadez, Padhraic Smyth
2000	J	`jnl`	Model selection for probabilistic clustering using cross-validated likelihood. Stat. Comput. Padhraic Smyth
2000	A	`conf`	Probabilistic Models for Query Approximation with Large Sparse Binary Data Sets. UAI Dmitry Pavlov, Heikki Mannila, Padhraic Smyth
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	A*	`conf`	Towards scalable support vector machines using squashing. KDD Dmitry Pavlov, Darya Chudova, Padhraic Smyth
2000	A*	`conf`	Visualization of navigation patterns on a Web site using model-based clustering. KDD Igor V. Cadez, David Heckerman, Christopher Meek, Padhraic Smyth, Steven White
1999	A*	`conf`	Discovering Chinese Words from Unsegmented Text (poster abstract). SIGIR Xianping Ge, Wanda Pratt, Padhraic Smyth
1999	J	`jnl`	Discussion on the paper by Friedman and Fisher. Stat. Comput. Padhraic Smyth
1999	A*	`conf`	Hierarchical Models for Screening of Iron Deficiency Anemia. ICML Igor V. Cadez, Christine E. McLaren, Padhraic Smyth, Geoffrey J. McLachlan
1999	A	`conf`	Joint probabilistic clustering of multivariate and sequential data. AISTATS Padhraic Smyth
1999	J	`jnl`	Linearly Combining Density Estimators via Stacking. Mach. Learn. Padhraic Smyth, David H. Wolpert
1999	A*	`conf`	Prediction with Local Patterns using Cross-Entropy. KDD Heikki Mannila, Dmitry Pavlov, Padhraic Smyth
1999	J	`jnl`	The Distribution of Cycle Lengths in Graphical Models for Iterative Decoding CoRR Xianping Ge, David Eppstein, Padhraic Smyth
1999	A*	`conf`	Trajectory Clustering with Mixtures of Regression Models. KDD Scott Gaffney, Padhraic Smyth
1998	J	`jnl`	Learning to Recognize Volcanoes on Venus. Mach. Learn. Michael C. Burl, Lars Asker, Padhraic Smyth, Usama M. Fayyad, Pietro Perona, Larry Crumpler, Jayne Aubele
1998	A*	`conf`	Rule Discovery from Time Series. KDD Gautam Das, King-Ip Lin, Heikki Mannila, Gopal Renganathan, Padhraic Smyth
1997	A*	`conf`	A Probabilistic Approach to Fast Pattern Matching in Time Series Databases. KDD Eamonn J. Keogh, Padhraic Smyth
1997	A*	`conf`	Anytime Exploratory Data Analysis for Massive Data Sets. KDD Padhraic Smyth, David H. Wolpert
1997	J	`jnl`	Applying classification algorithms in practice. Stat. Comput. Carla E. Brodley, Padhraic Smyth
1997	J	`jnl`	Belief networks, hidden Markov models, and Markov random fields: A unifying view. Pattern Recognit. Lett. Padhraic Smyth
1997	A	`conf`	Cross-validated Likelihood for Model Selection in Unsupervised Learning. AISTATS Padhraic Smyth
1997	A*	`conf`	Detecting Atmospheric Regimes Using Cross-Validated Clustering. KDD Padhraic Smyth, Michael Ghil, Kayo Ide, Joseph Roden, Andrew Fraser
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	J	`jnl`	Learning with Probabilistic Representations. Mach. Learn. Pat Langley, Gregory M. Provan, Padhraic Smyth
1997	A	`conf`	Preface. AISTATS David Madigan, Padhraic Smyth
1997	J	`jnl`	Probabilistic Independence Networks for Hidden Markov Probability Models. Neural Comput. Padhraic Smyth, David Heckerman, Michael I. Jordan
1997	A	`ed.`	Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, AISTATS 1997, Fort Lauderdale, Florida, USA, January, 4-7, 1997 AISTATS David Madigan, Padhraic Smyth
1997	—	`conf`	Stacked Density Estimation. NIPS Padhraic Smyth, David H. Wolpert
1997	J	`jnl`	Statistical Themes and Lessons for Data Mining. Data Min. Knowl. Discov. Clark Glymour, David Madigan, Daryl Pregibon, Padhraic Smyth
1996	—	`book`	Advances in Knowledge Discovery and Data Mining. Usama M. Fayyad, Gregory Piatetsky-Shapiro, Padhraic Smyth, Ramasamy Uthurusamy
1996	J	`jnl`	Bounds on the mean classification error rate of multiple experts. Pattern Recognit. Lett. Padhraic Smyth
1996	—	`conf`	Clustering Sequences with Hidden Markov Models. NIPS Padhraic Smyth
1996	A*	`conf`	Clustering Using Monte Carlo Cross-Validation. KDD Padhraic Smyth
1996	J	`jnl`	From Data Mining to Knowledge Discovery in Databases. AI Mag. Usama M. Fayyad, Gregory Piatetsky-Shapiro, Padhraic Smyth
1996	—	`ch.`	From Data Mining to Knowledge Discovery: An Overview. Advances in Knowledge Discovery and Data Mining Usama M. Fayyad, Gregory Piatetsky-Shapiro, Padhraic Smyth
1996	A*	`conf`	Knowledge Discovery and Data Mining: Towards a Unifying Framework. KDD Usama M. Fayyad, Gregory Piatetsky-Shapiro, Padhraic Smyth
1996	—	`ch.`	Modeling Subjective Uncertainty in Image Annotation. Advances in Knowledge Discovery and Data Mining Padhraic Smyth, Usama M. Fayyad, Michael C. Burl, Pietro Perona
1996	J	`jnl`	Statistical Inference and Data Mining. Commun. ACM Clark Glymour, David Madigan, Daryl Pregibon, Padhraic Smyth
1996	J	`jnl`	The KDD Process for Extracting Useful Knowledge from Volumes of Data. Commun. ACM Usama M. Fayyad, Gregory Piatetsky-Shapiro, Padhraic Smyth
1995	J	`jnl`	Automated Analysis and Exploration of Image Databases: Results, Progress, and Challenges. J. Intell. Inf. Syst. Usama M. Fayyad, Padhraic Smyth, Nicholas Weir, S. George Djorgovski
1995	A*	`conf`	Retrofitting Decision Tree Classifiers Using Kernel Density Estimation. ICML Padhraic Smyth, Alexander G. Gray, Usama M. Fayyad
1994	—	`conf`	Automated Analysis of Radar Imagery of Venus: Handling Lack of Ground Truth. ICIP (3) Michael C. Burl, Usama M. Fayyad, Pietro Perona, Padhraic Smyth
1994	A*	`conf`	Automating the hunt for volcanoes on Venus. CVPR Michael C. Burl, Usama M. Fayyad, Pietro Perona, Padhraic Smyth
1994	J	`jnl`	Discrete recurrent neural networks for grammatical inference. IEEE Trans. Neural Networks Zheng Zeng, Rodney M. Goodman, Padhraic Smyth
1994	J	`jnl`	Hidden Markov models for fault detection in dynamic system. Pattern Recognit. Padhraic Smyth
1994	—	`conf`	Inferring Ground Truth from Subjective Labelling of Venus Images. NIPS Padhraic Smyth, Usama M. Fayyad, Michael C. Burl, Pietro Perona, Pierre Baldi
1994	J	`jnl`	KDD-93: Progress and Challenges in Knowledge Discovery in Databases. AI Mag. Gregory Piatetsky-Shapiro, Christopher J. Matheus, Padhraic Smyth, Ramasamy Uthurusamy
1994	—	`conf`	Knowledge Discovery in Large Image Databases: Dealing with Uncertainties in Ground Truth. KDD Workshop Padhraic Smyth, Michael C. Burl, Usama M. Fayyad, Pietro Perona
1994	J	`jnl`	Markov monitoring with unknown states. IEEE J. Sel. Areas Commun. Padhraic Smyth
1994	—	`conf`	The Automated Analysis, Cataloging, and Searching of Digital Image Libraries: A Machine Learning Approach. DL Usama M. Fayyad, Padhraic Smyth
1993	J	`jnl`	Learning Finite State Machines With Self-Clustering Recurrent Networks. Neural Comput. Zheng Zeng, Rodney M. Goodman, Padhraic Smyth
1993	J	`jnl`	On loss functions which minimize to conditional expected values and posterior proba- bilities. IEEE Trans. Inf. Theory John W. Miller, Rodney M. Goodman, Padhraic Smyth
1993	—	`conf`	Probabilistic Anomaly Detection in Dynamic Systems. NIPS Padhraic Smyth
1993	—	`conf`	Self-clustering recurrent networks. ICNN Zheng Zeng, Rodney M. Goodman, Padhraic Smyth
1992	J	`jnl`	An Information Theoretic Approach to Rule Induction from Databases. IEEE Trans. Knowl. Data Eng. Padhraic Smyth, Rodney M. Goodman
1992	—	`conf`	Detecting Novel Classes with Applications to Fault Diagnosis. ML Padhraic Smyth, Jeff Mellstrom
1992	J	`jnl`	Rule-Based Neural Networks for Classification and Probability Estimation. Neural Comput. Rodney M. Goodman, Charles M. Higgins, John W. Miller, Padhraic Smyth
1991	—	`conf`	Fault Diagnosis of Antenna Pointing Systems Using Hybrid Neural Network and Signal Processing Models. NIPS Padhraic Smyth, Jeff Mellstrom
1991	—	`ch.`	Rule Induction Using Information Theory. Knowledge Discovery in Databases Padhraic Smyth, Rodney M. Goodman
1990	A	`conf`	A Hybrid Rule-Based/Bayesian Classifier. ECAI Padhraic Smyth, Rodney M. Goodman, Charles M. Higgins
1990	J	`jnl`	Decision tree design using information theory. Knowl. Acquis. Rodney M. Goodman, Padhraic Smyth
1990	—	`conf`	On Stochastic Complexity and Admissible Models for Neural Network Classifiers. NIPS Padhraic Smyth
1989	—	`conf`	The Induction of Probabilistic Rule Sets - The Itrule Algorithm. ML Rodney M. Goodman, Padhraic Smyth
1988	—	`conf`	An Information Theoretic Approach to Rule-Based Connectionist Expert Systems. NIPS Rodney M. Goodman, John W. Miller, Padhraic Smyth
1988	J	`jnl`	Decision tree design from a communication theory standpoint. IEEE Trans. Inf. Theory Rodney M. Goodman, Padhraic Smyth
1988	A	`conf`	Information-Theoretic Rule Induction. ECAI Rodney M. Goodman, Padhraic Smyth