POSTER SESSION A: Tuesday April 14, 19:30
| 162 | Connected Components of 3-Partite 3-Uniform Hypergraphs Nicolas Neubauer and Klaus Obermayer |
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| 157 | Why Feature Selection Works? Rich Caruana and Art Munson |
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| 155 | Hierarchical Latent Variable Models for Human Pose Inference Catalin Ionescu and Cristian Sminchisescu |
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| 153 | Automatic discrimination of mislabeled training points for large margin classifiers Romer Rosales, Glenn Fung and Wei Tong |
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| 152 | Semi-Supervised Embedding for Predicting Protein-Protein Interactions from Multiple Sources Yanjun Qi, Oznur Tastan, Jaime Carbonell, Judith Klein-Seetharaman, Jason Weston |
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| 150 | Learning Representation and Control in Markov Decision Processes Sridhar Mahadevan |
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| 143 | Latent Feature Models for Link Prediction Kurt T Miller and Thomas L Griffiths and Michael I Jordan |
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| 142 | Relational models for generating labeled real-world graphs Christoph Lippert and Nino Shervashidze and Oliver Stegle and Karsten Borgwardt |
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| 141 | Efficient Discovery of Common Patterns in Sequences Pavel Kuksa and Vladimir Pavlovic |
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| 139 | Unsupervised Rank Aggregation with Domain-Specific Expertise Alexandre Klementiev and Dan Roth and Kevin Small and Ivan Titov |
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| 136 | An Efficient Convolutional Framework for Multitask Learning Michalis K. Titsias and Mauricio Alvarez and David Luengo and Neil D. Lawrence |
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| 122 | Repulsive Affinity-Based Clustering Laurens J.P. van der Maaten |
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| 121 | Learning and Recognizing American Football Plays Eran Swears and Anthony Hoogs |
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| 120 | Monte-Carlo Simulation Balancing David Silver and Gerald Tesauro |
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| 118 | Online Learning with Knowledge-Based SVMs Gautam Kunapuli and Kristin P. Bennett and Richard Maclin and Jude Shavlik |
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| 117 | Performance Prediction of the Influence Relevance Voter Chloe-Agathe Azencott and Joshua S. Swamidass and Pierre Baldi |
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| 109 | Learning Kinematic Models for Articulated Objects Juergen Sturm and Cyrill Stachniss and Vijay Pradeep and Christian Plagemann and Kurt Konolige and Wolfram Burgard |
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| 108 | Video-based Lane Detection using Boosting Principles Raghuraman Gopalan and Tsai Hong and Mike Shneier and Rama Chellappa |
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| 107 | From Clustering to Co-clustering: Generative Model Approach Danial Lashkari and Polina Golland |
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| 106 | Supervised Semantic Indexing for Ranking Documents Bing Bai and Jason Weston and Ronan Collobert and David Grangier |
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| 103 | A Nonconformity Approach to Model Selection for SVMs David R. Hardoon and Zakria Hussain and John Shawe-Taylor |
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POSTER SESSION B: Wednesday April 15, 19:30
| 158 | CNP: An FPGA-based Processor for Convolutional Networks Clement Farabet and Cyril Poulet and Jefferson Y. Han and Yann LeCun |
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| 149 | Polylingual Topic Models David Mimno and Hanna M. Wallach and Limin Yao and Jason Naradowsky and Andrew McCallum |
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| 147 | Functional Bundle Methods Nathan Ratliff and J. Andrew Bagnell |
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| 146 | Mixtures-of-Clusterings by Boosting Jonathan Chang and David M. Blei |
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| 145 | SVM Multi-Task Learning and Non convex Sparsity Measure R. Flamary and A. Rakotomamonjy and G. Gasso and S. Canu |
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| 144 | Perturbation Methods for Discriminant Analysis Yung-Kyun Noh and Jihun Hamm and Daniel D. Lee |
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| 135 | Rank Priors for Continuous Non-Linear Dimensionality Reduction Raquel Urtasun and Andreas Geiger and Trevor Darrell |
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| 134 | Co-training with Noisy Perceptual Observations C. Mario Christoudias and Raquel Urtasun and Ashish Kapoor and Trevor Darrell |
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| 133 | Second-Order PCA-Style Dimensionality Reduction Algorithm by Semidefinite Programming Rong Jin and Wei Tong |
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| 131 | Hierarchical Affinity Propagation Inmar Givoni and Brendan Frey |
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| 130 | Estimation of conditional mutual information and its application as a measure of conditional dependence Sohan Seth and Jose C. Principe |
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| 129 | Dynamic Modeling by Support Vector Machines Haini Qu and Yacine Oussar and Gérard DREYFUS |
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| 127 | Symmetrized Bregman Divergences and Metrics Arindam Banerjee and Daniel Boley and Sreansgu Acharyya |
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| 126 | Extracting the Measurement Information Core for Model Selection of Dynamical Systems Alberto G. Busetto and Cheng Soon Ong and Joachim M. Buhmann |
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| 124 | Machine learning for shock decision in implanted defibrillators P. Bouchet and R. Dubois and C. Henry and P. Roussel and G. Dreyfus |
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| 123 | Freezing and Sleeping: Tracking Experts that Learn by Evolving Past Posteriors Tim van Erven and Wouter M. Koolen |
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| 115 | Robust Probabilistic Matrix Factorization Wu-Jun Li and Yi Zhen and Dit-Yan Yeung and Zhihua Zhang |
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| 114 | Semi-Markov Clustering Matthew Robards and Peter Sunehag |
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| 113 | Towards Large Scale Transfer Learning Alexandru Niculescu-Mizil |
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| 112 | Vehicle Routing with an Environment Model Tomas Singliar and Milos Hauskrecht |
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| 111 | Learning Using Group Information Vladimir Cherkassky and Feng Cai |
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