Vladimir Pavlovic

Zarko Stanisavljevic, Vladimir Pavlovic, Bosko Nikolic, Jovan Djordjevic: SDLDS - System for Digital Logic Design and Simulation. IEEE Trans. Education 56(2): 235-245 (2013)

Ognjen Rudovic, Maja Pantic, Vladimir Pavlovic: Heteroscedastic Conditional Ordinal Random Fields for Pain Intensity Estimation from Facial Images. CoRR abs/1301.5063 (2013)

Vladimir Pavlovic, Brendan J. Frey, Thomas S. Huang: Variational Learning in Mixed-State Dynamic Graphical Models. CoRR abs/1301.6731 (2013)

Shahriar Shariat, Vladimir Pavlovic: Improved sequence classification using adaptive segmental sequence alignment. Journal of Machine Learning Research - Proceedings Track 25: 379-394 (2012)

Dejan Ilic, Vladimir Pavlovic, Vladimir Rakocevic: Extensions of the Zamfirescu theorem to partial metric spaces. Mathematical and Computer Modelling 55(3-4): 801-809 (2012)

Wang Yan, Xiaoye Han, Vladimir Pavlovic: Structured Learning for Multiple Object Tracking. BMVC 2012: 1-12

Ognjen Rudovic, Vladimir Pavlovic, Maja Pantic: Multi-output Laplacian dynamic ordinal regression for facial expression recognition and intensity estimation. CVPR 2012: 2634-2641

Mihalis A. Nicolaou, Vladimir Pavlovic, Maja Pantic: Dynamic Probabilistic CCA for Analysis of Affective Behaviour. ECCV (7) 2012: 98-111

Ognjen Rudovic, Vladimir Pavlovic, Maja Pantic: Kernel Conditional Ordinal Random Fields for Temporal Segmentation of Facial Action Units. ECCV Workshops (2) 2012: 260-269

Chathra Hendahewa, Vladimir Pavlovic: Analysis of Causality in Stock Market Data. ICMLA (1) 2012: 288-293

Jongpil Kim, Vladimir Pavlovic: Attribute rating for classification of visual objects. ICPR 2012: 1611-1614

Saehoon Yi, Vladimir Pavlovic: Sparse Granger causality graphs for human action classification. ICPR 2012: 3374-3377

Pavel P. Kuksa, Vladimir Pavlovic: Efficient evaluation of large sequence kernels. KDD 2012: 759-767

Sejong Yoon, Vladimir Pavlovic: Distributed Probabilistic Learning for Camera Networks with Missing Data. NIPS 2012: 2933-2941

Pavel P. Kuksa, Imdadullah Khan, Vladimir Pavlovic: Generalized Similarity Kernels for Efficient Sequence Classification. SDM 2012: 873-882

Dejan Ilic, Vladimir Pavlovic, Vladimir Rakocevic: Some new extensions of Banach's contraction principle to partial metric space. Appl. Math. Lett. 24(8): 1326-1330 (2011)

Minyoung Kim, Vladimir Pavlovic: Sequence classification via large margin hidden Markov models. Data Min. Knowl. Discov. 23(2): 322-344 (2011)

Minyoung Kim, Vladimir Pavlovic: Central Subspace Dimensionality Reduction Using Covariance Operators. IEEE Trans. Pattern Anal. Mach. Intell. 33(4): 657-670 (2011)

Antonina Mitrofanova, Vladimir Pavlovic, Bud Mishra: Prediction of Protein Functions with Gene Ontology and Interspecies Protein Homology Data. IEEE/ACM Trans. Comput. Biology Bioinform. 8(3): 775-784 (2011)

Shahriar Shariat, Vladimir Pavlovic: Isotonic CCA for sequence alignment and activity recognition. ICCV 2011: 2572-2578

Andre Cohen, Vladimir Pavlovic: An efficient IP approach to constrained multiple face tracking and recognition. ICCV Workshops 2011: 852-859

Rui Huang, Nong Sang, Vladimir Pavlovic, Dimitris N. Metaxas: A Belief Propagation algorithm for bias field estimation and image segmentation. ICIP 2011: 37-40

Toufiq Parag, Vladimir Pavlovic, Ahmed M. Elgammal: Learning Hypergraph Labeling for Feature Matching. CoRR abs/1107.2553 (2011)

Dragana S. Cvetkovic-Ilic, Vladimir Pavlovic: A comment on some recent results concerning the reverse order law for {1, 3, 4}-inverses. Applied Mathematics and Computation 217(1): 105-109 (2010)

Pavel P. Kuksa, Vladimir Pavlovic: Efficient motif finding algorithms for large-alphabet inputs. BMC Bioinformatics 11(S-8): S1 (2010)

Ameesh Makadia, Vladimir Pavlovic, Sanjiv Kumar: Baselines for Image Annotation. International Journal of Computer Vision 90(1): 88-105 (2010)

Minyoung Kim, Vladimir Pavlovic: Structured Output Ordinal Regression for Dynamic Facial Emotion Intensity Prediction. ECCV (3) 2010: 649-662

Andre Cohen, Vladimir Pavlovic: Reinforcement Learning for Robust and Efficient Real-World Tracking. ICPR 2010: 2989-2992

Pavel P. Kuksa, Vladimir Pavlovic: Spatial Representation for Efficient Sequence Classification. ICPR 2010: 3320-3323

Minyoung Kim, Vladimir Pavlovic: Hidden Conditional Ordinal Random Fields for Sequence Classification. ECML/PKDD (2) 2010: 51-65

Pavel P. Kuksa, Yanjun Qi, Bing Bai, Ronan Collobert, Jason Weston, Vladimir Pavlovic, Xia Ning: Semi-supervised Abstraction-Augmented String Kernel for Multi-level Bio-Relation Extraction. ECML/PKDD (2) 2010: 128-144

Pavel P. Kuksa, Vladimir Pavlovic: Efficient alignment-free DNA barcode analytics. BMC Bioinformatics 10(S-14): 9 (2009)

Pavel P. Kuksa, Pai-Hsi Huang, Vladimir Pavlovic: Efficient use of unlabeled data for protein sequence classification: a comparative study. BMC Bioinformatics 10(S-4) (2009)

Minyoung Kim, Vladimir Pavlovic: Covariance Operator Based Dimensionality Reduction with Extension to Semi-Supervised Settings. Journal of Machine Learning Research - Proceedings Track 5: 280-287 (2009)

Minyoung Kim, Vladimir Pavlovic: Discriminative Learning for Dynamic State Prediction. IEEE Trans. Pattern Anal. Mach. Intell. 31(10): 1847-1861 (2009)

Pavel P. Kuksa, Vladimir Pavlovic: Fast Motif Selection for Biological Sequences. BIBM 2009: 79-82

Pai-Hsi Huang, Vladimir Pavlovic: Protein homology detection with biologically inspired features and interpretable statistical models. IJDMB 2(2): 157-175 (2008)

Yushi Jing, Vladimir Pavlovic, James M. Rehg: Boosted Bayesian network classifiers. Machine Learning 73(2): 155-184 (2008)

Pavel P. Kuksa, Pai-Hsi Huang, Vladimir Pavlovic: On the Role of Local Matching for Efficient Semi-supervised Protein Sequence Classification. BIBM 2008: 217-222

Antonina Mitrofanova, Vladimir Pavlovic, Bud Mishra: Integrative Protein Function Transfer Using Factor Graphs and Heterogeneous Data Sources. BIBM 2008: 314-318

Kooksang Moon, Vladimir Pavlovic: 3D Human Motion Tracking Using Dynamic Probabilistic Latent Semantic Analysis. CRV 2008: 155-162

Minyoung Kim, Sanjiv Kumar, Vladimir Pavlovic, Henry A. Rowley: Face tracking and recognition with visual constraints in real-world videos. CVPR 2008

Minyoung Kim, Vladimir Pavlovic: Dimensionality reduction using covariance operator inverse regression. CVPR 2008

Ameesh Makadia, Vladimir Pavlovic, Sanjiv Kumar: A New Baseline for Image Annotation. ECCV (3) 2008: 316-329

Pavel P. Kuksa, Pai-Hsi Huang, Vladimir Pavlovic: Fast protein homology and fold detection with sparse spatial sample kernels. ICPR 2008: 1-4

Pavel P. Kuksa, Pai-Hsi Huang, Vladimir Pavlovic: Scalable Algorithms for String Kernels with Inexact Matching. NIPS 2008: 881-888

Mathias Kölsch, Vladimir Pavlovic, Branislav Kisacanin, Thomas S. Huang: Special issue on vision for human-computer interaction. Computer Vision and Image Understanding 108(1-2): 1-3 (2007)

Christian Vogler, Siome Goldenstein, Jorge Stolfi, Vladimir Pavlovic, Dimitris N. Metaxas: Outlier rejection in high-dimensional deformable models. Image Vision Comput. 25(3): 274-284 (2007)

Minyoung Kim, Vladimir Pavlovic: Discriminative Learning of Dynamical Systems for Motion Tracking. CVPR 2007

Rui Huang, Vladimir Pavlovic, Dimitris N. Metaxas: Embedded Profile Hidden Markov Models for Shape Analysis. ICCV 2007: 1-8

Minyoung Kim, Vladimir Pavlovic: Conditional State Space Models for Discriminative Motion Estimation. ICCV 2007: 1-8

Minyoung Kim, Vladimir Pavlovic: A recursive method for discriminative mixture learning. ICML 2007: 409-416

Rui Huang, Vladimir Pavlovic, Dimitris N. Metaxas: Shape Analysis Using Curvature-Based Descriptors and Profile Hidden Markov Models. ISBI 2007: 1220-1223

Pavel P. Kuksa, Vladimir Pavlovic: Fast Kernel Methods for SVM Sequence Classifiers. WABI 2007: 228-239

Rui Huang, Vladimir Pavlovic, Dimitris N. Metaxas: A Graphical Model Framework for Image Segmentation. Applied Graph Theory in Computer Vision and Pattern Recognition 2007: 43-63

Steven Carroll, Vladimir Pavlovic: Protein classification using probabilistic chain graphs and the Gene Ontology structure. Bioinformatics 22(15): 1871-1878 (2006)

Kooksang Moon, Vladimir Pavlovic: Impact of Dynamics on Subspace Embedding and Tracking of Sequences. CVPR (1) 2006: 198-205

Minyoung Kim, Vladimir Pavlovic: Discriminative Learning of Mixture of Bayesian Network Classifiers for Sequence Classification. CVPR (1) 2006: 268-275

Pai-Hsi Huang, Vladimir Pavlovic: Sparse Logistic Classifiers for Interpretable Protien Homology Detection. ICDM Workshops 2006: 99-103

Rui Huang, Vladimir Pavlovic, Dimitris N. Metaxas: A Profile Hidden Markov Model Framework for Modeling and Analysis of Shape. ICIP 2006: 2121-2124

Rui Huang, Vladimir Pavlovic, Dimitris N. Metaxas: A tightly coupled region-shape framework for 3D medical image segmentation. ISBI 2006: 426-429

Thomas S. Huang, Nicu Sebe, Michael S. Lew, Vladimir Pavlovic, Mathias Kölsch, Aphrodite Galata, Branislav Kisacanin (Eds.): Computer Vision in Human-Computer Interaction, ECCV 2006 Workshop on HCI, Graz, Austria, May 13, 2006, Proceedings. Lecture Notes in Computer Science 3979, Springer 2006, isbn 3-540-34202-8

Rui Huang, Vladimir Pavlovic, Dimitris N. Metaxas: A Hybrid Framework for Image Segmentation Using Probabilistic Integration of Heterogeneous Constraints. CVBIA 2005: 82-92

Yushi Jing, Vladimir Pavlovic, James M. Rehg: Efficient discriminative learning of Bayesian network classifier via boosted augmented naive Bayes. ICML 2005: 369-376

Rui Huang, Vladimir Pavlovic, Dimitris N. Metaxas: A Graphical Model Framework for Coupling MRFs and Deformable Models. CVPR (2) 2004: 739-746

Vladimir Pavlovic: Model-Based Motion Clustering Using Boosted Mixture Modeling. CVPR (1) 2004: 811-818

Rui Huang, Dimitris N. Metaxas, Vladimir Pavlovic: A Hybrid Face Recognition Method using Markov Random Fields. ICPR (3) 2004: 157-160

Yang Su, T. M. Murali, Vladimir Pavlovic, Michael Schaffer, Simon Kasif: RankGene: identification of diagnostic genes based on expression data. Bioinformatics 19(12): 1578-1579 (2003)

James M. Rehg, Vladimir Pavlovic, Thomas S. Huang, William T. Freeman: Guest Editors' Introduction to the Special Section on Graphical Models in Computer Vision. IEEE Trans. Pattern Anal. Mach. Intell. 25(7): 785-786 (2003)

Jonathan Alon, Stan Sclaroff, George Kollios, Vladimir Pavlovic: Discovering Clusters in Motion Time-Series Data. CVPR (1) 2003: 375-381

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

Ashutosh Garg, Vladimir Pavlovic, Thomas S. Huang: Bayesian Networks as Ensemble of Classifiers. ICPR (2) 2002: 779-784

Tanzeem Choudhury, James M. Rehg, Vladimir Pavlovic, Alex Pentland: Boosting and Structure Learning in Dynamic Bayesian Networks for Audio-Visual Speaker Detection. ICPR (3) 2002: 789-

Rajeev Sharma, Michael Zeller, Vladimir Pavlovic, Thomas S. Huang, Zion Lo, Stephen M. Chu, Yunxin Zhao, James C. Phillips, Klaus Schulten: Speech/Gesture Interface to a Visual-Computing Environment. IEEE Computer Graphics and Applications 20(2): 29-37 (2000)

Vladimir Pavlovic, James M. Rehg: Impact of Dynamic Model Learning on Classification of Human Motion. CVPR 2000: 1788-1795

Vladimir Pavlovic, James M. Rehg, Ashutosh Garg, Thomas S. Huang: Multimodal Speaker Detection Using Error Feedback Dynamic Bayesian Networks. CVPR 2000: 2034-

Ashutosh Garg, Vladimir Pavlovic, James M. Rehg: Audio-Visual Speaker Detection Using Dynamic Bayesian Networks. FG 2000: 384-390

Vladimir Pavlovic, James M. Rehg, Tat-Jen Cham: A Dynamic Bayesian Network Approach to Tracking Using Learned Switching Dynamic Models. HSCC 2000: 366-380

Vladimir Pavlovic, Ashutosh Garg, James M. Rehg: Multimodal Speaker Detection Using Input/Output Dynamic Bayesian Networks. ICMI 2000: 308-316

Vladimir Pavlovic, James M. Rehg, John MacCormick: Learning Switching Linear Models of Human Motion. NIPS 2000: 981-987

Vladimir Pavlovic, Brendan J. Frey, Thomas S. Huang: Time-Series Classification Using Mixed-State Dynamic Bayesian Networks. CVPR 1999: 2609-

Vladimir Pavlovic, James M. Rehg, Tat-Jen Cham, Kevin P. Murphy: A Dynamic Bayesian Network Approach to Figure Tracking using Learned Dynamic Models. ICCV 1999: 94-101

Vladimir Pavlovic, Brendan J. Frey, Thomas S. Huang: Variational Learning in Mixed-State Dynamic Graphical Models. UAI 1999: 522-530

Vladimir Pavlovic: Multimodal Tracking and Classification of Audio-Visual Features. ICIP (1) 1998: 343-347

Vladimir Pavlovic, Rajeev Sharma, Thomas S. Huang: Visual Interpretation of Hand Gestures for Human-Computer Interaction: A Review. IEEE Trans. Pattern Anal. Mach. Intell. 19(7): 677-695 (1997)

Michael Zeller, James C. Phillips, A. Dalke, W. Humphrey, Klaus Schulten, Thomas S. Huang, Vladimir Pavlovic, Yunxin Zhao, Zion Lo, Stephen M. Chu, Rajeev Sharma: A Visual Computing Environment for Very Large Scale Biomolecular Modeling. ASAP 1997: 3-

Vladimir Pavlovic, G. A. Berry, Thomas S. Huang: Integration of Audio/Visual Information for Use in Human-Computer Intelligent Interaction. ICIP (1) 1997: 121-124

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

Pierre Moulin, Kannan Ramchandran, Vladimir Pavlovic: Transform image coding based on joint adaptation of filter banks and tree structures. ICIP (2) 1996: 369-372