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);  |