| Tuesday, April 6 | ||
| 16:00 | Registration | |
| 18:00 | Dinner | |
| 19:00 | Oral Session 1 | |
| 19:00 | FOLS: Factorized Orthogonal Latent Spaces Mathieu Salzmann and Carl Henrik Ek and Raquel Urtasun and Trevor Darrell |
[DjVu|PDF] |
| 19:20 | Collaborative, Structured, and Hierarchical Sparse Image Models Guillermo Sapiro (U. Minnesota) |
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| 20:00 | Break | |
| 20:20 | Third-Order Edge Statistics Reveal Curvature Dependency Matthew Lawlor and Steven W. Zucker |
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| 20:40 | Proximal Methods for Sparse Hierarchical Dictionary Learning Rodolphe Jenatton and Julien Mairal and Guillaume Obozinski and Francis Bach |
[DjVu|PDF] |
| 21:00 | Deep Learning on GPUs with Theano James Bergstra and Olivier Breuleux and Frédéric Bastien and Pascal Lamblin and Joseph Turian and Guillaume Desjardins and Razvan Pascanu and Dumitru Erhan and Olivier Delalleau and Yoshua Bengio |
[DjVu|PDF] |
| 21:20 | Adjourn | |
| Wednesday, April 7 | ||
| 10:30 | Oral Session 2 | |
| 10:30 | Graphical Modeling and Inference with Perfect Graphs Tony Jebara |
[DjVu|PDF] |
| 10:50 | A Collective Approach to Graph Identification Galileo Namata and Lise Getoor |
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| 11:10 | Can computer vision help us understand biological vision? Mitya Chkolvskii (HHMI Janelia Farm) |
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| 11:50 | Break | |
| 12:10 | Inverse Reinforcement Learning for Following Instructions Nicholas Roy and Thomas Kollar and Stefanie Tellex (MIT) |
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| 12:50 | Learning low-dimensional Lagrangian models of high-dimensional trajectories via Fermat Components Analysis Paul Vernaza and Daniel D. Lee |
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| 13:10 | Learning Deep Inference Machines J. Andrew Bagnell and Alex Grubb and Daniel Munoz and Stephane Ross |
[DjVu|PDF] |
| 13:30 | Lunch, Golden Cliff | |
| 18:30 | Dinner, Golden Cliff | |
| 19:30-22:00 | Poster Session A | |
| Thursday, April 8 | ||
| 07:00 | Breakfast | |
| 08:00 | Oral Session 2 | |
| 08:00 | Early attention-related mechanisms integrate information about stimulus statistics and reward P. Kallerhoff and A. Hollaender and J.-D. Haynes and K. Obermayer |
[DjVu|PDF] |
| 08:20 | Efficient Sequence Classification with Spatial Representations Pavel Kuksa and Vladimir Pavlovic |
[DjVu|PDF] |
| 08:40 | Learning local spatio-temporal features for activity recognition Graham W. Taylor and Chris Bregler |
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| 09:00 | Are categories necessary for recognition? Alyosha Efros (CMU) |
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| 09:40 | Break | |
| 10:00 | Double Feature! 1. Human versus machine: comparing visual object recognition systems on a level playing field Nicolas Pinto (MIT) with Najib J. Majaj, Youssef Barhomi, Ethan A. Solomon, David D. Cox & James J. DiCarlo |
[DjVu|PDF] |
| 2. A High-Throughput Screening Approach to Biologically-Inspired Object Recognition David Cox (Harvard), with Nicolas Pinto and James J. DiCarlo |
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| 10:40 | Web Scale Image Annotation: Learning to Rank with Joint Word-Image Embeddings Jason Weston and Samy Bengio and Nicolas Usunier |
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| 11:00 | Analysis of Feature Learning and Feature Pooling for Image Recognition Y-Lan Boureau, Francis Bach, Yann LeCun, and Jean Ponce |
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| 11:20 | Lunch, Golden Cliff | |
| 17:30 | Dinner, Golden Cliff | |
| 19:00-22:00 | Poster Session B | |
| Friday, April 9 | ||
| 07:00 | Breakfast | |
| 08:00 | Oral Session 2 | |
| 08:00 | Markov Logic Networks: A Step Towards a Unified Theory of Learning and Cognition Pedro Domingos (U. Washington) |
[DjVu|PDF] |
| 08:40 | Learning with Privileged Information: New Optimization Algorithms and Applications Dmitry Pechyony and Leon Bottou and Vladimir Vapnik |
[DjVu|PDF] |
| 09:00 | A fast natural Newton method Nicolas Le Roux and Andrew Fitzgibbon |
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| 09:20 | Deep Segmentation Networks Nicolas Le Roux and Nicolas Heess and Jamie Shotton and John Winn |
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| 09:40 | Break | |
| 10:00 | Object Detection Grammars Pedro Felzenszwalb and David McAllester (U. Chicago, TTI-C) |
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| 10:40 | Weak Recovery Conditions using Graph Partitioning Bounds Alexandre d'Aspremont and Noureddine El Karoui |
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| 11:00 | Answering Reading Comprehension Tests using Multi-View Regression Dean Foster and Daniel Kim and Andrew Pak and Lyle Ungar |
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| 11:20 | Tracking Climate Models Claire Monteleoni and Shailesh Saroha and Gavin Schmidt |
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| 11:40 | Lunch, Golden Cliff | |
| 17:30 | Banquet, Golden Cliff | |
| 19:30 | An Iterative Path Integral Reinforcement Learning Approach Evangelos Theodorou, Jonas Buchli, Freek Stulp, and Stefan Schaal (USC) |
[DjVu|PDF] |
| 20:10 | Identifying People based on their Motion Signature George Williams, Graham W. Taylor, Ian Spiro, Chris Bregler |
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