Listed below are the workshop papers accepted to the International Conference on Learning Representations (ICLR) 2013. A Nested HDP for Hierarchical Topic Models [video] John Paisley, Chong Wang, David Blei, Michael I. Jordan Affinity Weighted Embedding [video] Jason Weston, Ron Weiss, Hector Yee Big Neural Networks Waste Capacity [video] Yann N. Dauphin, Yoshua Bengio Zero-Shot Learning Through Cross-Modal Transfer [video] Richard Socher, Milind Ganjoo, Hamsa Sridhar, Osbert Bastani, Christopher D. Manning, Andrew Y. Ng Why Size Matters: Feature Coding as Nystrom Sampling [video] Oriol Vinyals, Yangqing Jia, Trevor Darrell Joint Training Deep Boltzmann Machines for Classification [video] Ian J. Goodfellow, Aaron Courville, Yoshua Bengio Deep Learning for Detecting Robotic Grasps [video] Ian Lenz, Honglak Lee, Ashutosh Saxena The Manifold of Human Emotions Seungyeon Kim, Fuxin Li, Guy Lebanon, Irfan Essa Two SVDs produce more focal deep learning representations
Hinrich Schuetze, Christian Scheible Visual Objects Classification with Sliding Spatial Pyramid Matching
Hao Wooi Lim, Yong Haur Tay Learnable Pooling Regions for Image Classification Mateusz Malinowski, Mario Fritz Tommi Vatanen, Tapani Raiko, Harri Valpola, Yann LeCun Learning New Facts From Knowledge Bases With Neural Tensor Networks and Semantic Word Vectors Danqi Chen, Richard Socher, Christopher D. Manning, Andrew Y. Ng Gradient Driven Learning for Pooling in Visual Pipeline Feature Extraction Models Derek Rose, Itamar Arel Deep Predictive Coding Networks Rakesh Chalasani, Jose C. Principe Clustering Learning for Robotic Vision Eugenio Culurciello, Jordan Bates, Aysegul Dundar, Jose Carrasco, Clement Farabet Matrix Approximation under Local Low-Rank Assumption Joonseok Lee, Seungyeon Kim, Guy Lebanon, Yoram Singer Linear-Nonlinear-Poisson Neuron Networks Perform Bayesian Inference On Boltzmann Machines Louis Yuanlong Shao Learning Stable Group Invariant Representations with Convolutional Networks Joan Bruna, Arthur Szlam, Yann LeCun Boltzmann Machines and Denoising Autoencoders for Image Denoising Kyunghyun Cho Regularized Discriminant Embedding for Visual Descriptor Learning Kye-Hyeon Kim, Rui Cai, Lei Zhang, Seungjin Choi Hierarchical Data Representation Model - Multi-layer NMF Hyun Ah Song, Soo-Young Lee Efficient Estimation of Word Representations in Vector Space Tomas Mikolov, Kai Chen, Greg Corrado, Jeffrey Dean A Semantic Matching Energy Function for Learning with Multi-relational Data Xavier Glorot, Antoine Bordes, Jason Weston, Yoshua Bengio Latent Relation Representations for Universal Schemas Sebastian Riedel, Limin Yao, Andrew McCallum Tree structured sparse coding on cubes Arthur Szlam Razvan Pascanu, Yoshua Bengio Learning Features with Structure-Adapting Multi-view Exponential Family Harmoniums Yoonseop Kang, Seungjin Choi |
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