Posters 1A Statistical Methods and Learning - 8:30-10:00 Foothills/Atrium/Pikes Peak
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| A Direct Formulation for Totally-corrective Multi-class Boosting |
Chunhua Shen (NICTA); Zhihui Hao (Beijing Institute of Technology); |
| A Probabilistic Representation for Efficient Large Scale Visual Recognition Tasks |
Subhabrata Bhattacharya (UCF); Rahul Sukthankar;Rong Jin (Michigan State University); Mubarak Shah (UCF); |
| A Scalable Dual Approach to Semidefinite Metric Learning |
Chunhua Shen (NICTA); Junae Kim (Australian National University); Lei Wang (Australian National University); |
| AdaBoost on Low-Rank PSD Matrices for Metric Learning with Applications in Computer Aided Diagnosis |
Jinbo Bi (University of Connecticut); Dijia Wu;Le Lu (Siemens ); Meizhu Liu;Yimo Tao;Matthias Wolf; |
| Bayesian Deblurring with Integrated Noise Estimation |
Uwe Schmidt (TU Darmstadt); Kevin Schelten (TU Darmstadt); Stefan Roth; |
| Comparing Data-Dependent and Data-Independent Embeddings for Classification and Ranking of Internet Images |
Yunchao Gong (UNC Chapel Hill); Svetlana Lazebnik (University of North Carolina at Chapel Hill); |
| Connecting Non-Quadratic Variational Models and MRFs |
Kevin Schelten (TU Darmstadt); Stefan Roth; |
| Dynamic Batch Mode Active Learning |
Shayok Chakraborty (Arizona State University); Vineeth Balasubramanian (Arizona State University); Sethuraman Panchanathan (Arizona State University); |
| Natural Image Denoising: Optimality and Inherent Bounds |
Anat Levin (Weizmann Institute of Science); Boaz Nadler (Weizmann Inst of Science); |
| From Region Similarity to Category Discovery |
Carolina Galleguillos (U.C San Diego); Brian McFee (U.C San Diego); Serge Belongie (UCSD); Gert Lanckriet (U.C San Diego); |
| Gated Classifiers: Boosting under High Intra-Class Variation |
Oscar Danielsson (KTH); Babak Rasolzadeh (KTH); Stefan Carlsson (KTH); |
| Generalized Gaussian Process Models |
Antoni Chan (City University of Hong Kong); Daxiang Dong (Hong Kong University of Science and Technology); |
| Generalized Projection Based M-Estimator: Theory and Applications |
Sushil Mittal (Rutgers University); Saket Anand (Rutgers University); Peter Meer (Rutgers University); |
| Geometric $\ell_p$-norm Feature Pooling for Image Classification |
Jiashi Feng (NUS); Bingbing Ni;Qi Tian (University of Texas at San Antonio); Shuicheng Yan; |
| Graph Embedding Discriminant Analysis on Grassmannian Manifolds for Improved Image Set Matching |
Mehrtash Harandi (NICTA); Sareh Shirazi (National ICT Australia (NICTA)); Conrad Sanderson (National ICT Australia (NICTA)); Brian Lovell; |
| Hybrid Generative-Discriminative Classification using Posterior Divergence |
Xiong Li (Shanghai Jiao Tong University); Tai Sing Lee (Department of Computer Science, Carnegie Mellon University); Yuncai Liu (Department of Automation, Shanghai Jiao Tong University); |
| Learning Better Image Representations Using `Flobject Analysis' |
Inmar Givoni (University of Toronto); Patrick Li (University of Toronto); Brendan Frey (University of Toronto); |
| Learning invariance through imitation |
Graham Taylor;Ian Spiro (New York University); Rob Fergus;Christoph Bregler (NYU); |
| Learning Message-Passing Inference Machines for Structured Prediction |
Stephane Ross (Carnegie Mellon University); Daniel Munoz (Carnegie Mellon University); J. Andrew Bagnell (Carnegie Mellon University); |
| Learning Non-Local Range Markov Random Field for Image Restoration |
Jian Sun (Xi'an Jiaotong University); Marshall Tappen; |
| Learning Transformation Invariant Representations from weakly-related Videos |
Christian Leistner (icg tugraz); Martin Godec;Samuel Schulter;Manuel Werlberger;Amir Saffari;Horst Bischof; |
| Local Isomorphism to Solve the Pre-image Problem in Kernel Methods |
Dong Huang (Carnegie Mellon University); Yuandong Tian (Carnegie Mellon University); Fernando DelaTorre; |
| Max-margin Clustering: Detecting Margins from Projections of Points on Lines |
Raghuraman Gopalan (University of Maryland); Jagan Sankaranarayanan; |
| Mining Discriminative Co-occurrence Patterns for Visual Recognition |
Junsong Yuan (Nanyang Technological University); Ming Yang (NEC Laboratories America); Ying Wu (Northwestern University); |
| MKPM: a multiclass extension of the Kernel Projection Machine |
Sylvain Takerkart (CNRS); Liva Ralaivola (LIF); |
| Modeling the joint density of two images under a variety of transformations |
Joshua Susskind (University of Toronto); Roland Memisevic;Geoffrey Hinton (University of Toronto); Marc Pollefeys; |
| Multi-label Learning with Incomplete Class Assignments |
Serhat Bucak (Michigan State University); Rong Jin (Michigan State University); Anil Jain (Michigan State University); |
| Multi-layer Group Sparse Coding -- for Concurrent Image Classification and Annotation |
Shenghua Gao (Nanyang Technological Univ.); Liang-Tien Chia (Nanyang Technological University); Ivor W. Tsang; |
| Multifactor Analysis Based on Factor-Dependent Geometry |
Sung Won Park (Carnegie Mellon University); |
| Multiscale Geometric and Spectral Analysis of Plane Arrangements |
Guangliang Chen (Duke University); Mauro Maggioni; |
| Non-negative Matrix Factorization as a Feature Selection Tool for Maximum Margin Classifiers |
Mithun Gupta (GE); Jing Xiao (Epson R&D); |
| Nonnegative Sparse Coding for Discriminative Semi-supervised Learning |
Ran He (Institute of Automation Chines); Wei-Shi Zheng (Queen Mary University of London); |
| On Deep Generative Models with Applications to Recognition |
Marc'Aurelio Ranzato;Joshua Susskind (University of Toronto); Volodymyr Mnih (University of Toronto); Geoffrey Hinton (University of Toronto); |
| Online Group-Structured Dictionary Learning |
Zoltan Szabo (Eotvos Lorand University); Barnabas Poczos (Carnegie Mellon University); Andras Lorincz (Eotvos Lorand University); |
| Particle Filter with State Permutations for Solving Image Jigsaw Puzzles |
Xingwei Yang (Temple University); Nagesh Adluru;LonginJan Latecki; |
| Recovery of Corrupted Low-Rank Matrices via Half-Quadratic based Nonconvex Minimization |
Ran He (Institute of Automation Chines); zhenan sun ( Institute of Automation Chinese Academy of Sciences); Tieniu Tan;Wei-Shi Zheng (Queen Mary University of London); |
| Robust and Efficient Regularized Boosting Using Total Bregman Divergence |
Meizhu Liu (University of Florida); Baba Vemuri; |
| Sparse Concept Coding for Visual Analysis |
Deng Cai;Xiaofei He; |
| Sparse Image Representation with Epitomes |
Louise Benoit (ENS); Julien Mairal;Francis Bach (INRIA); Jean Ponce; |
| Supervised Local Subspace Learning for Continuous Head Pose Estimation |
Dong Huang (Carnegie Mellon University); Markus Storer (Graz University of Technology ); Fernando DelaTorre;Horst Bischof; |
| TaylorBoost: First and Second-order Boosting Algorithms with Explicit Margin Control |
Mohammad Saberian (UC San Diego); Hamed Masnadi-Shirazi (UC San Diego); Nuno Vasconcelos; |
| Truncated Message Passing |
Justin Domke; |
| Visual textures as realizations of multivariate log-Gaussian Cox processes |
Huu-Giao Nguyen (Telecom Bretgane); Ronan Fablet (Institut Telecom / Telecom Bretagne); Jean-Marc Boucher (Institut Telecom / Telecom Bretagne); |