Kevin P. Murphy

Google Publications

Previous Publications

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    A Stick-Breaking Likelihood for Categorical Data Analysis with Latent Gaussian Models

    Mohammad Emtiyaz Khan, Shakir Mohamed, Benjamin M. Marlin, Kevin P. Murphy

    Journal of Machine Learning Research - Proceedings Track, vol. 22 (2012), pp. 610-618

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    Bayesian structure learning using dynamic programming and MCMC

    Daniel Eaton, Kevin P. Murphy

    CoRR, vol. abs/1206.5247 (2012)

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    Group Sparse Priors for Covariance Estimation

    Benjamin M. Marlin, Mark W. Schmidt, Kevin P. Murphy

    CoRR, vol. abs/1205.2626 (2012)

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    Identifying players in broadcast sports videos using conditional random fields

    Wei-Lwun Lu, Jo-Anne Ting, Kevin P. Murphy, James J. Little

    CVPR (2011), pp. 3249-3256

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    Multiscale Conditional Random Fields for Semi-supervised Labeling and Classification

    David K. Duvenaud, Benjamin M. Marlin, Kevin P. Murphy

    CRV (2011), pp. 371-378

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    Piecewise Bounds for Estimating Bernoulli-Logistic Latent Gaussian Models

    Benjamin M. Marlin, Mohammad Emtiyaz Khan, Kevin P. Murphy

    ICML (2011), pp. 633-640

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    Causal learning without DAGs

    David K. Duvenaud, Daniel Eaton, Kevin P. Murphy, Mark W. Schmidt

    Journal of Machine Learning Research - Proceedings Track, vol. 6 (2010), pp. 177-190

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    Convex Structure Learning in Log-Linear Models: Beyond Pairwise Potentials

    Mark W. Schmidt, Kevin P. Murphy

    Journal of Machine Learning Research - Proceedings Track, vol. 9 (2010), pp. 709-716

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    Review of "Probabilistic graphical models" by Koller and Friedman

    Kevin P. Murphy

    Artif. Intell., vol. 174 (2010), pp. 145-146

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    SNVMix: predicting single nucleotide variants from next-generation sequencing of tumors

    Rodrigo Goya, Mark G. F. Sun, Ryan D. Morin, Gillian Leung, Gavin Ha, Kimberley C. Wiegand, Janine Senz, Anamaria Crisan, Marco A. Marra, Martin Hirst, David G. Huntsman, Kevin P. Murphy, Sam Aparicio, Sohrab P. Shah

    Bioinformatics, vol. 26 (2010), pp. 730-736

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    Time-Bounded Sequential Parameter Optimization

    Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown, Kevin P. Murphy

    LION (2010), pp. 281-298

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    Using the forest to see the trees: exploiting context for visual object detection and localization

    Antonio Torralba, Kevin P. Murphy, William T. Freeman

    Commun. ACM, vol. 53 (2010), pp. 107-114

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    Variational bounds for mixed-data factor analysis

    Mohammad Emtiyaz Khan, Benjamin M. Marlin, Guillaume Bouchard, Kevin P. Murphy

    NIPS (2010), pp. 1108-1116

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    A Hybrid Conditional Random Field for Estimating the Underlying Ground Surface From Airborne LiDAR Data

    Wei-Lwun Lu, Kevin P. Murphy, James J. Little, Alla Sheffer, Hongbo Fu

    IEEE T. Geoscience and Remote Sensing, vol. 47 (2009), pp. 2913-2922

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    Accelerating Bayesian Structural Inference for Non-Decomposable Gaussian Graphical Models

    Baback Moghaddam, Benjamin M. Marlin, Mohammad Emtiyaz Khan, Kevin P. Murphy

    NIPS (2009), pp. 1285-1293

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    An experimental investigation of model-based parameter optimisation: SPO and beyond

    Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown, Kevin P. Murphy

    GECCO (2009), pp. 271-278

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    Group Sparse Priors for Covariance Estimation

    Benjamin M. Marlin, Mark W. Schmidt, Kevin P. Murphy

    UAI (2009), pp. 383-392

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    Model-based clustering of array CGH data

    Sohrab P. Shah, K-John Cheung Jr., Nathalie A. Johnson, Guillaume Alain, Randy D. Gascoyne, Douglas E. Horsman, Raymond T. Ng, Kevin P. Murphy

    Bioinformatics, vol. 25 (2009)

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    Modeling Discrete Interventional Data using Directed Cyclic Graphical Models

    Mark W. Schmidt, Kevin P. Murphy

    UAI (2009), pp. 487-495

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    Optimizing Costly Functions with Simple Constraints: A Limited-Memory Projected Quasi-Newton Algorithm

    Mark W. Schmidt, Ewout van den Berg, Michael P. Friedlander, Kevin P. Murphy

    Journal of Machine Learning Research - Proceedings Track, vol. 5 (2009), pp. 456-463

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    Sparse Gaussian graphical models with unknown block structure

    Benjamin M. Marlin, Kevin P. Murphy

    ICML (2009), pp. 89

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    LabelMe: A Database and Web-Based Tool for Image Annotation

    Bryan C. Russell, Antonio Torralba, Kevin P. Murphy, William T. Freeman

    International Journal of Computer Vision, vol. 77 (2008), pp. 157-173

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    Structure learning in random fields for heart motion abnormality detection

    Mark W. Schmidt, Kevin P. Murphy, Glenn Fung, Rómer Rosales

    CVPR (2008)

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    A non-myopic approach to visual search

    Julia Vogel, Kevin P. Murphy

    CRV (2007), pp. 227-234

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    Bayesian structure learning using dynamic programming and MCMC

    Daniel Eaton, Kevin P. Murphy

    UAI (2007), pp. 101-108

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    Efficient parameter estimation for RNA secondary structure prediction

    Mirela Andronescu, Anne Condon, Holger H. Hoos, David H. Mathews, Kevin P. Murphy

    ISMB/ECCB (Supplement of Bioinformatics) (2007), pp. 19-28

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    Exact Bayesian structure learning from uncertain interventions

    Daniel Eaton, Kevin P. Murphy

    Journal of Machine Learning Research - Proceedings Track, vol. 2 (2007), pp. 107-114

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    Figure-ground segmentation using a hierarchical conditional random field

    Jordan Reynolds, Kevin P. Murphy

    CRV (2007), pp. 175-182

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    Learning Graphical Model Structure Using L1-Regularization Paths

    Mark W. Schmidt, Alexandru Niculescu-Mizil, Kevin P. Murphy

    AAAI (2007), pp. 1278-1283

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    Modeling changing dependency structure in multivariate time series

    Xiang Xuan, Kevin P. Murphy

    ICML (2007), pp. 1055-1062

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    Modeling recurrent DNA copy number alterations in array CGH data

    Sohrab P. Shah, Wan L. Lam, Raymond T. Ng, Kevin P. Murphy

    ISMB/ECCB (Supplement of Bioinformatics) (2007), pp. 450-458

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    Sharing Visual Features for Multiclass and Multiview Object Detection

    Antonio Torralba, Kevin P. Murphy, William T. Freeman

    IEEE Trans. Pattern Anal. Mach. Intell., vol. 29 (2007), pp. 854-869

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    Accelerated training of conditional random fields with stochastic gradient methods

    S. V. N. Vishwanathan, Nicol N. Schraudolph, Mark W. Schmidt, Kevin P. Murphy

    ICML (2006), pp. 969-976

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    Integrating copy number polymorphisms into array CGH analysis using a robust HMM

    Sohrab P. Shah, Xiang Xuan, Ronald J. deLeeuw, Mehrnoush Khojasteh, Wan L. Lam, Raymond T. Ng, Kevin P. Murphy

    ISMB (Supplement of Bioinformatics) (2006), pp. 431-439

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    Object Detection and Localization Using Local and Global Features

    Kevin P. Murphy, Antonio Torralba, Daniel Eaton, William T. Freeman

    Toward Category-Level Object Recognition (2006), pp. 382-400

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    Shared Features for Multiclass Object Detection

    Antonio Torralba, Kevin P. Murphy, William T. Freeman

    Toward Category-Level Object Recognition (2006), pp. 345-361

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    Contextual Models for Object Detection Using Boosted Random Fields

    Antonio Torralba, Kevin P. Murphy, William T. Freeman

    NIPS (2004)

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    Representing Hierarchical POMDPs as DBNs for Multi-scale Robot Localization

    Georgios Theocharous, Kevin P. Murphy, Leslie Pack Kaelbling

    ICRA (2004), pp. 1045-1051

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    Sharing Features: Efficient Boosting Procedures for Multiclass Object Detection

    Antonio Torralba, Kevin P. Murphy, William T. Freeman

    CVPR (2) (2004), pp. 762-769

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    Context-based vision system for place and object recognition

    Antonio Torralba, Kevin P. Murphy, William T. Freeman, Mark A. Rubin

    ICCV (2003), pp. 273-280

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    Graphical Model For Recognizing Scenes and Objects

    Kevin P. Murphy, Antonio Torralba, William T. Freeman

    NIPS (2003)

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    A coupled HMM for audio-visual speech recognition

    Ara V. Nefian, Luhong Liang, Xiaobo Pi, Xiaoxiang Liu, Crusoe Mao, Kevin P. Murphy

    ICASSP (2002), pp. 2013-2016

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    Dynamic Bayesian Networks for Audio-Visual Speech Recognition

    Ara V. Nefian, Luhong Liang, Xiaobo Pi, Xiaoxing Liu, Kevin P. Murphy

    EURASIP J. Adv. Sig. Proc., vol. 2002 (2002), pp. 1274-1288

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    Linear-time inference in Hierarchical HMMs

    Kevin P. Murphy, Mark A. Paskin

    NIPS (2001), pp. 833-840

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    The Factored Frontier Algorithm for Approximate Inference in DBNs

    Kevin P. Murphy, Yair Weiss

    UAI (2001), pp. 378-385

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    Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks

    Arnaud Doucet, Nando de Freitas, Kevin P. Murphy, Stuart J. Russell

    UAI (2000), pp. 176-183

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    A Dynamic Bayesian Network Approach to Figure Tracking using Learned Dynamic Models

    Vladimir Pavlovic, James M. Rehg, Tat-Jen Cham, Kevin P. Murphy

    ICCV (1999), pp. 94-101

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    A Variational Approximation for Bayesian Networks with Discrete and Continuous Latent Variables

    Kevin P. Murphy

    UAI (1999), pp. 457-466

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    Bayesian Map Learning in Dynamic Environments

    Kevin P. Murphy

    NIPS (1999), pp. 1015-1021

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    Loopy Belief Propagation for Approximate Inference: An Empirical Study

    Kevin P. Murphy, Yair Weiss, Michael I. Jordan

    UAI (1999), pp. 467-475

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    Vision-Based Speaker Detection Using Bayesian Networks

    James M. Rehg, Kevin P. Murphy, Paul W. Fieguth

    CVPR (1999), pp. 2110-2116

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    Learning the Structure of Dynamic Probabilistic Networks

    Nir Friedman, Kevin P. Murphy, Stuart J. Russell

    UAI (1998), pp. 139-147

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    Space-Efficient Inference in Dynamic Probabilistic Networks

    John Binder, Kevin P. Murphy, Stuart J. Russell

    IJCAI (1997), pp. 1292-1296

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    Automata-Theoretic Models of Mutation and Alignment

    David B. Searls, Kevin P. Murphy

    ISMB (1995), pp. 341-349