ICLR 2015
104 papers
Algorithmic Robustness for Semi-Supervised (ε, Γ, Τ)-Good Metric Learning
Maria-Irina Nicolae, Marc Sebban, Amaury Habrard, Éric Gaussier, Massih-Reza Amini Attention for Fine-Grained Categorization
Pierre Sermanet, Andrea Frome, Esteban Real Automatic Discovery and Optimization of Parts for Image Classification
Sobhan Naderi Parizi, Andrea Vedaldi, Andrew Zisserman, Pedro F. Felzenszwalb Deep Learning with Elastic Averaging SGD
Sixin Zhang, Anna Choromanska, Yann LeCun Deep Networks with Large Output Spaces
Sudheendra Vijayanarasimhan, Jonathon Shlens, Rajat Monga, Jay Yagnik Discovering Hidden Factors of Variation in Deep Networks
Brian Cheung, Jesse A. Livezey, Arjun K. Bansal, Bruno A. Olshausen Diverse Embedding Neural Network Language Models
Kartik Audhkhasi, Abhinav Sethy, Bhuvana Ramabhadran Embedding Word Similarity with Neural Machine Translation
Felix Hill, Kyunghyun Cho, Sébastien Jean, Coline Devin, Yoshua Bengio Explaining and Harnessing Adversarial Examples
Ian J. Goodfellow, Jonathon Shlens, Christian Szegedy Fast Convolutional Nets with Fbfft: A GPU Performance Evaluation
Nicolas Vasilache, Jeff Johnson, Michaël Mathieu, Soumith Chintala, Serkan Piantino, Yann LeCun FitNets: Hints for Thin Deep Nets
Adriana Romero, Nicolas Ballas, Samira Ebrahimi Kahou, Antoine Chassang, Carlo Gatta, Yoshua Bengio Fully Convolutional Multi-Class Multiple Instance Learning
Deepak Pathak, Evan Shelhamer, Jonathan Long, Trevor Darrell Learning Activation Functions to Improve Deep Neural Networks
Forest Agostinelli, Matthew D. Hoffman, Peter J. Sadowski, Pierre Baldi Learning Deep Structured Models
Liang-Chieh Chen, Alexander G. Schwing, Alan L. Yuille, Raquel Urtasun Learning Longer Memory in Recurrent Neural Networks
Tomás Mikolov, Armand Joulin, Sumit Chopra, Michaël Mathieu, Marc'Aurelio Ranzato Low Precision Arithmetic for Deep Learning
Matthieu Courbariaux, Yoshua Bengio, Jean-Pierre David Memory Networks
Jason Weston, Sumit Chopra, Antoine Bordes Object Detectors Emerge in Deep Scene CNNs
Bolei Zhou, Aditya Khosla, Àgata Lapedriza, Aude Oliva, Antonio Torralba On the Stability of Deep Networks
Raja Giryes, Guillermo Sapiro, Alexander M. Bronstein Permutohedral Lattice CNNs
Martin Kiefel, Varun Jampani, Peter V. Gehler Random Forests Can Hash
Qiang Qiu, Guillermo Sapiro, Alexander M. Bronstein Real-World Font Recognition Using Deep Network and Domain Adaptation
Zhangyang Wang, Jianchao Yang, Hailin Jin, Eli Shechtman, Aseem Agarwala, Jonathan Brandt, Thomas S. Huang Representation Learning for Cold-Start Recommendation
Gabriella Contardo, Ludovic Denoyer, Thierry Artières Representation Using the Weyl Transform
Qiang Qiu, Andrew Thompson, A. Robert Calderbank, Guillermo Sapiro Reweighted Wake-Sleep
Jörg Bornschein, Yoshua Bengio Scheduled Denoising Autoencoders
Krzysztof J. Geras, Charles Sutton Self-Informed Neural Network Structure Learning
David Warde-Farley, Andrew Rabinovich, Dragomir Anguelov Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs
Liang-Chieh Chen, George Papandreou, Iasonas Kokkinos, Kevin Murphy, Alan L. Yuille Speeding-up Convolutional Neural Networks Using Fine-Tuned CP-Decomposition
Vadim Lebedev, Yaroslav Ganin, Maksim Rakhuba, Ivan V. Oseledets, Victor S. Lempitsky Striving for Simplicity: The All Convolutional Net
Jost Tobias Springenberg, Alexey Dosovitskiy, Thomas Brox, Martin A. Riedmiller Target Propagation
Dong-Hyun Lee, Saizheng Zhang, Antoine Biard, Yoshua Bengio The Local Low-Dimensionality of Natural Images
Olivier J. Hénaff, Johannes Ballé, Neil C. Rabinowitz, Eero P. Simoncelli Training Deep Neural Networks on Noisy Labels with Bootstrapping
Scott E. Reed, Honglak Lee, Dragomir Anguelov, Christian Szegedy, Dumitru Erhan, Andrew Rabinovich Understanding Locally Competitive Networks
Rupesh Kumar Srivastava, Jonathan Masci, Faustino J. Gomez, Jürgen Schmidhuber Unsupervised Feature Learning from Temporal Data
Ross Goroshin, Joan Bruna, Jonathan Tompson, David Eigen, Yann LeCun Variational Recurrent Auto-Encoders
Otto Fabius, Joost R. van Amersfoort, Diederik P. Kingma Visual Instance Retrieval with Deep Convolutional Networks
Ali Sharif Razavian, Josephine Sullivan, Atsuto Maki, Stefan Carlsson What Do Deep CNNs Learn About Objects?
Xingchao Peng, Baochen Sun, Karim Ali, Kate Saenko