Vladimir Pavlovic - researchr alias

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2011

2010

Reinforcement Learning for Robust and Efficient Real-World TrackingAndre Cohen, Vladimir Pavlovic. icpr 2010: 2989-2992 [doi]

A comment on some recent results concerning the reverse order law for {1, 3, 4}-inversesDragana S. Cvetkovic-Ilic, Vladimir Pavlovic. amc, 217(1):105-109, 2010. [doi]

Structured Output Ordinal Regression for Dynamic Facial Emotion Intensity PredictionMinyoung Kim, Vladimir Pavlovic. eccv 2010: 649-662 [doi]

Hidden Conditional Ordinal Random Fields for Sequence ClassificationMinyoung Kim, Vladimir Pavlovic. pkdd 2010: 51-65 [doi]

Semi-supervised Abstraction-Augmented String Kernel for Multi-level Bio-Relation ExtractionPavel P. Kuksa, Yanjun Qi, Bing Bai, Ronan Collobert, Jason Weston, Vladimir Pavlovic, Xia Ning. pkdd 2010: 128-144 [doi]

Spatial Representation for Efficient Sequence ClassificationPavel P. Kuksa, Vladimir Pavlovic. icpr 2010: 3320-3323 [doi]

Baselines for Image AnnotationAmeesh Makadia, Vladimir Pavlovic, Sanjiv Kumar. ijcv, 90(1):88-105, 2010. [doi]

2009

2008

Protein homology detection with biologically inspired features and interpretable statistical modelsPai-Hsi Huang, Vladimir Pavlovic. ijdmb, 2(2):157-175, 2008. [doi]

Boosted Bayesian network classifiersYushi Jing, Vladimir Pavlovic, James M. Rehg. ml, 73(2):155-184, 2008. [doi]

Dimensionality reduction using covariance operator inverse regressionMinyoung Kim, Vladimir Pavlovic. cvpr 2008: [doi]

Face tracking and recognition with visual constraints in real-world videosMinyoung Kim, Sanjiv Kumar, Vladimir Pavlovic, Henry A. Rowley. cvpr 2008: [doi]

Scalable Algorithms for String Kernels with Inexact MatchingPavel P. Kuksa, Pai-Hsi Huang, Vladimir Pavlovic. nips 2009: 881-888 [doi]

Fast protein homology and fold detection with sparse spatial sample kernelsPavel P. Kuksa, Pai-Hsi Huang, Vladimir Pavlovic. icpr 2008: 1-4 [doi]

On the Role of Local Matching for Efficient Semi-supervised Protein Sequence ClassificationPavel P. Kuksa, Pai-Hsi Huang, Vladimir Pavlovic. bibm 2008: 217-222 [doi]

A New Baseline for Image AnnotationAmeesh Makadia, Vladimir Pavlovic, Sanjiv Kumar. eccv 2008: 316-329 [doi]

Integrative Protein Function Transfer Using Factor Graphs and Heterogeneous Data SourcesAntonina Mitrofanova, Vladimir Pavlovic, Bud Mishra. bibm 2008: 314-318 [doi]

3D Human Motion Tracking Using Dynamic Probabilistic Latent Semantic AnalysisKooksang Moon, Vladimir Pavlovic. crv 2008: 155-162 [doi]

2007

Embedded Profile Hidden Markov Models for Shape AnalysisRui Huang, Vladimir Pavlovic, Dimitris N. Metaxas. iccv 2007: 1-8 [doi]

Shape Analysis Using Curvature-Based Descriptors and Profile Hidden Markov ModelsRui Huang, Vladimir Pavlovic, Dimitris N. Metaxas. isbi 2007: 1220-1223 [doi]

A Graphical Model Framework for Image SegmentationRui Huang, Vladimir Pavlovic, Dimitris N. Metaxas. In Abraham Kandel, Horst Bunke, Mark Last, editors, Applied Graph Theory in Computer Vision and Pattern Recognition. Volume 52 of Studies in Computational Intelligence, pages 43-63, Springer, 2007. [doi]

Discriminative Learning of Dynamical Systems for Motion TrackingMinyoung Kim, Vladimir Pavlovic. cvpr 2007: [doi]

A recursive method for discriminative mixture learningMinyoung Kim, Vladimir Pavlovic. icml 2007: 409-416 [doi]

Conditional State Space Models for Discriminative Motion EstimationMinyoung Kim, Vladimir Pavlovic. iccv 2007: 1-8 [doi]

Fast Kernel Methods for SVM Sequence ClassifiersPavel P. Kuksa, Vladimir Pavlovic. wabi 2007: 228-239 [doi]

Special issue on vision for human-computer interactionMathias Kölsch, Vladimir Pavlovic, Branislav Kisacanin, Thomas S. Huang. cviu, 108(1-2):1-3, 2007. [doi]

Outlier rejection in high-dimensional deformable modelsChristian Vogler, Siome Goldenstein, Jorge Stolfi, Vladimir Pavlovic, Dimitris N. Metaxas. ivc, 25(3):274-284, 2007. [doi]

2006

Protein classification using probabilistic chain graphs and the Gene Ontology structureSteven Carroll, Vladimir Pavlovic. bioinformatics, 22(15):1871-1878, 2006. [doi]

Sparse Logistic Classifiers for Interpretable Protien Homology DetectionPai-Hsi Huang, Vladimir Pavlovic. icdm 2006: 99-103 [doi]

A tightly coupled region-shape framework for 3D medical image segmentationRui Huang, Vladimir Pavlovic, Dimitris N. Metaxas. isbi 2006: 426-429 [doi]

Computer Vision in Human-Computer Interaction, ECCV 2006 Workshop on HCI, Graz, Austria, May 13, 2006, ProceedingsThomas S. Huang, Nicu Sebe, Michael S. Lew, Vladimir Pavlovic, Mathias Kölsch, Aphrodite Galata, Branislav Kisacanin, editors, Volume 3979 of Lecture Notes in Computer Science, Springer, 2006.

A Profile Hidden Markov Model Framework for Modeling and Analysis of ShapeRui Huang, Vladimir Pavlovic, Dimitris N. Metaxas. icip 2006: 2121-2124 [doi]

Discriminative Learning of Mixture of Bayesian Network Classifiers for Sequence ClassificationMinyoung Kim, Vladimir Pavlovic. cvpr 2006: 268-275 [doi]

Impact of Dynamics on Subspace Embedding and Tracking of SequencesKooksang Moon, Vladimir Pavlovic. cvpr 2006: 198-205 [doi]

2005

A Hybrid Framework for Image Segmentation Using Probabilistic Integration of Heterogeneous ConstraintsRui Huang, Vladimir Pavlovic, Dimitris N. Metaxas. cvbia 2005: 82-92 [doi]

Efficient discriminative learning of Bayesian network classifier via boosted augmented naive BayesYushi Jing, Vladimir Pavlovic, James M. Rehg. icml 2005: 369-376 [doi]

2004

A Hybrid Face Recognition Method using Markov Random FieldsRui Huang, Dimitris N. Metaxas, Vladimir Pavlovic. icpr 2004: 157-160 [doi]

A Graphical Model Framework for Coupling MRFs and Deformable ModelsRui Huang, Vladimir Pavlovic, Dimitris N. Metaxas. cvpr 2004: 739-746 [doi]

Model-Based Motion Clustering Using Boosted Mixture ModelingVladimir Pavlovic. cvpr 2004: 811-818 [doi]

2003

2002

Boosting and Structure Learning in Dynamic Bayesian Networks for Audio-Visual Speaker DetectionTanzeem Choudhury, James M. Rehg, Vladimir Pavlovic, Alex Pentland. icpr 2002: 789 [doi]

Bayesian Networks as Ensemble of ClassifiersAshutosh Garg, Vladimir Pavlovic, Thomas S. Huang. icpr 2002: 779-784 [doi]

A Bayesian framework for combining gene predictionsVladimir Pavlovic, Ashutosh Garg, Simon Kasif. bioinformatics, 18(1):19-27, 2002.

2000

Audio-Visual Speaker Detection Using Dynamic Bayesian NetworksAshutosh Garg, Vladimir Pavlovic, James M. Rehg. fgr 2000: 384-390 [doi]

Learning Switching Linear Models of Human MotionVladimir Pavlovic, James M. Rehg, John MacCormick. nips 2001: 981-987

Multimodal Speaker Detection Using Input/Output Dynamic Bayesian NetworksVladimir Pavlovic, Ashutosh Garg, James M. Rehg. icmi 2000: 308-316 [doi]

Multimodal Speaker Detection Using Error Feedback Dynamic Bayesian NetworksVladimir Pavlovic, James M. Rehg, Ashutosh Garg, Thomas S. Huang. cvpr 2000: 2034 [doi]

Impact of Dynamic Model Learning on Classification of Human MotionVladimir Pavlovic, James M. Rehg. cvpr 2000: 1788-1795 [doi]

A Dynamic Bayesian Network Approach to Tracking Using Learned Switching Dynamic ModelsVladimir Pavlovic, James M. Rehg, Tat-Jen Cham. hybrid 2000: 366-380 [doi]

Speech/Gesture Interface to a Visual-Computing EnvironmentRajeev Sharma, Michael Zeller, Vladimir Pavlovic, Thomas S. Huang, Zion Lo, Stephen M. Chu, Yunxin Zhao, James C. Phillips, Klaus Schulten. cga, 20(2):29-37, 2000. [doi]

1999

Variational Learning in Mixed-State Dynamic Graphical ModelsVladimir Pavlovic, Brendan J. Frey, Thomas S. Huang. uai 1999: 522-530 [doi]

Time-Series Classification Using Mixed-State Dynamic Bayesian NetworksVladimir Pavlovic, Brendan J. Frey, Thomas S. Huang. cvpr 1999: 2609 [doi]

A Dynamic Bayesian Network Approach to Figure Tracking using Learned Dynamic ModelsVladimir Pavlovic, James M. Rehg, Tat-Jen Cham, Kevin P. Murphy. iccv 1999: 94-101 [doi]

1998

Multimodal Tracking and Classification of Audio-Visual FeaturesVladimir Pavlovic. icip 1998: 343-347

1997

1996

Invited Speech: Gestural Interface to a visual computing Environment for Molecular biologists Vladimir Pavlovic, Rajeev Sharma, Thomas S. Huang. fgr 1996: 30-37 [doi]