| 2016 | 4th International Conference on Learning Representations, ICLR 2016, San Juan, Puerto Rico, May 2-4, 2016, Conference Track Proceedings Yoshua Bengio, Yann LeCun |
| 2016 | 8-Bit Approximations for Parallelism in Deep Learning. Tim Dettmers |
| 2016 | A Test of Relative Similarity For Model Selection in Generative Models. Wacha Bounliphone, Eugene Belilovsky, Matthew B. Blaschko, Ioannis Antonoglou, Arthur Gretton |
| 2016 | A note on the evaluation of generative models. Lucas Theis, Aäron van den Oord, Matthias Bethge |
| 2016 | ACDC: A Structured Efficient Linear Layer. Marcin Moczulski, Misha Denil, Jeremy Appleyard, Nando de Freitas |
| 2016 | Actor-Mimic: Deep Multitask and Transfer Reinforcement Learning. Emilio Parisotto, Lei Jimmy Ba, Ruslan Salakhutdinov |
| 2016 | Adversarial Manipulation of Deep Representations. Sara Sabour, Yanshuai Cao, Fartash Faghri, David J. Fleet |
| 2016 | All you need is a good init. Dmytro Mishkin, Jiri Matas |
| 2016 | An Exploration of Softmax Alternatives Belonging to the Spherical Loss Family. Alexandre de Brébisson, Pascal Vincent |
| 2016 | Auxiliary Image Regularization for Deep CNNs with Noisy Labels. Samaneh Azadi, Jiashi Feng, Stefanie Jegelka, Trevor Darrell |
| 2016 | Better Computer Go Player with Neural Network and Long-term Prediction. Yuandong Tian, Yan Zhu |
| 2016 | BlackOut: Speeding up Recurrent Neural Network Language Models With Very Large Vocabularies. Shihao Ji, S. V. N. Vishwanathan, Nadathur Satish, Michael J. Anderson, Pradeep Dubey |
| 2016 | Censoring Representations with an Adversary. Harrison Edwards, Amos J. Storkey |
| 2016 | Compression of Deep Convolutional Neural Networks for Fast and Low Power Mobile Applications. Yong-Deok Kim, Eunhyeok Park, Sungjoo Yoo, Taelim Choi, Lu Yang, Dongjun Shin |
| 2016 | Continuous control with deep reinforcement learning. Timothy P. Lillicrap, Jonathan J. Hunt, Alexander Pritzel, Nicolas Heess, Tom Erez, Yuval Tassa, David Silver, Daan Wierstra |
| 2016 | Convergent Learning: Do different neural networks learn the same representations? Yixuan Li, Jason Yosinski, Jeff Clune, Hod Lipson, John E. Hopcroft |
| 2016 | Convolutional neural networks with low-rank regularization. Cheng Tai, Tong Xiao, Xiaogang Wang, Weinan E |
| 2016 | Data Representation and Compression Using Linear-Programming Approximations. Hristo S. Paskov, John C. Mitchell, Trevor J. Hastie |
| 2016 | Data-Dependent Path Normalization in Neural Networks. Behnam Neyshabur, Ryota Tomioka, Ruslan Salakhutdinov, Nathan Srebro |
| 2016 | Data-dependent Initializations of Convolutional Neural Networks. Philipp Krähenbühl, Carl Doersch, Jeff Donahue, Trevor Darrell |
| 2016 | Deep Compression: Compressing Deep Neural Network with Pruning, Trained Quantization and Huffman Coding. Song Han, Huizi Mao, William J. Dally |
| 2016 | Deep Linear Discriminant Analysis. Matthias Dorfer, Rainer Kelz, Gerhard Widmer |
| 2016 | Deep Reinforcement Learning in Parameterized Action Space. Matthew J. Hausknecht, Peter Stone |
| 2016 | Deep multi-scale video prediction beyond mean square error. Michaël Mathieu, Camille Couprie, Yann LeCun |
| 2016 | Delving Deeper into Convolutional Networks for Learning Video Representations. Nicolas Ballas, Li Yao, Chris Pal, Aaron C. Courville |
| 2016 | Density Modeling of Images using a Generalized Normalization Transformation. Johannes Ballé, Valero Laparra, Eero P. Simoncelli |
| 2016 | Digging Deep into the Layers of CNNs: In Search of How CNNs Achieve View Invariance. Amr Bakry, Mohamed Elhoseiny, Tarek El-Gaaly, Ahmed M. Elgammal |
| 2016 | Distributional Smoothing by Virtual Adversarial Examples. Takeru Miyato, Shin-ichi Maeda, Masanori Koyama, Ken Nakae, Shin Ishii |
| 2016 | Diversity Networks. Zelda Mariet, Suvrit Sra |
| 2016 | Evaluating Prerequisite Qualities for Learning End-to-End Dialog Systems. Jesse Dodge, Andreea Gane, Xiang Zhang, Antoine Bordes, Sumit Chopra, Alexander H. Miller, Arthur Szlam, Jason Weston |
| 2016 | Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs). Djork-Arné Clevert, Thomas Unterthiner, Sepp Hochreiter |
| 2016 | Gated Graph Sequence Neural Networks. Yujia Li, Daniel Tarlow, Marc Brockschmidt, Richard S. Zemel |
| 2016 | Generating Images from Captions with Attention. Elman Mansimov, Emilio Parisotto, Lei Jimmy Ba, Ruslan Salakhutdinov |
| 2016 | Geodesics of learned representations. Olivier J. Hénaff, Eero P. Simoncelli |
| 2016 | Grid Long Short-Term Memory. Nal Kalchbrenner, Ivo Danihelka, Alex Graves |
| 2016 | High-Dimensional Continuous Control Using Generalized Advantage Estimation. John Schulman, Philipp Moritz, Sergey Levine, Michael I. Jordan, Pieter Abbeel |
| 2016 | Importance Weighted Autoencoders. Yuri Burda, Roger B. Grosse, Ruslan Salakhutdinov |
| 2016 | Large-Scale Approximate Kernel Canonical Correlation Analysis. Weiran Wang, Karen Livescu |
| 2016 | Learning Representations from EEG with Deep Recurrent-Convolutional Neural Networks. Pouya Bashivan, Irina Rish, Mohammed Yeasin, Noel Codella |
| 2016 | Learning Visual Predictive Models of Physics for Playing Billiards. Katerina Fragkiadaki, Pulkit Agrawal, Sergey Levine, Jitendra Malik |
| 2016 | Learning to Diagnose with LSTM Recurrent Neural Networks. Zachary Chase Lipton, David C. Kale, Charles Elkan, Randall C. Wetzel |
| 2016 | Metric Learning with Adaptive Density Discrimination. Oren Rippel, Manohar Paluri, Piotr Dollár, Lubomir D. Bourdev |
| 2016 | Modeling Visual Representations: Defining Properties and Deep Approximations Stefano Soatto, Alessandro Chiuso |
| 2016 | MuProp: Unbiased Backpropagation for Stochastic Neural Networks. Shixiang Gu, Sergey Levine, Ilya Sutskever, Andriy Mnih |
| 2016 | Multi-Scale Context Aggregation by Dilated Convolutions. Fisher Yu, Vladlen Koltun |
| 2016 | Multi-task Sequence to Sequence Learning. Minh-Thang Luong, Quoc V. Le, Ilya Sutskever, Oriol Vinyals, Lukasz Kaiser |
| 2016 | Net2Net: Accelerating Learning via Knowledge Transfer. Tianqi Chen, Ian J. Goodfellow, Jonathon Shlens |
| 2016 | Neural GPUs Learn Algorithms. Lukasz Kaiser, Ilya Sutskever |
| 2016 | Neural Networks with Few Multiplications. Zhouhan Lin, Matthieu Courbariaux, Roland Memisevic, Yoshua Bengio |
| 2016 | Neural Programmer-Interpreters. Scott E. Reed, Nando de Freitas |
| 2016 | Neural Programmer: Inducing Latent Programs with Gradient Descent. Arvind Neelakantan, Quoc V. Le, Ilya Sutskever |
| 2016 | Neural Random-Access Machines. Karol Kurach, Marcin Andrychowicz, Ilya Sutskever |
| 2016 | Order Matters: Sequence to sequence for sets. Oriol Vinyals, Samy Bengio, Manjunath Kudlur |
| 2016 | Order-Embeddings of Images and Language. Ivan Vendrov, Ryan Kiros, Sanja Fidler, Raquel Urtasun |
| 2016 | Particular object retrieval with integral max-pooling of CNN activations. Giorgos Tolias, Ronan Sicre, Hervé Jégou |
| 2016 | Policy Distillation. Andrei A. Rusu, Sergio Gomez Colmenarejo, Çaglar Gülçehre, Guillaume Desjardins, James Kirkpatrick, Razvan Pascanu, Volodymyr Mnih, Koray Kavukcuoglu, Raia Hadsell |
| 2016 | Predicting distributions with Linearizing Belief Networks. Yann N. Dauphin, David Grangier |
| 2016 | Prioritized Experience Replay. Tom Schaul, John Quan, Ioannis Antonoglou, David Silver |
| 2016 | Reasoning about Entailment with Neural Attention. Tim Rocktäschel, Edward Grefenstette, Karl Moritz Hermann, Tomás Kociský, Phil Blunsom |
| 2016 | Reasoning in Vector Space: An Exploratory Study of Question Answering. Moontae Lee, Xiaodong He, Wen-tau Yih, Jianfeng Gao, Li Deng, Paul Smolensky |
| 2016 | Recurrent Gaussian Processes. César Lincoln C. Mattos, Zhenwen Dai, Andreas C. Damianou, Jeremy Forth, Guilherme A. Barreto, Neil D. Lawrence |
| 2016 | Reducing Overfitting in Deep Networks by Decorrelating Representations. Michael Cogswell, Faruk Ahmed, Ross B. Girshick, Larry Zitnick, Dhruv Batra |
| 2016 | Regularizing RNNs by Stabilizing Activations. David Krueger, Roland Memisevic |
| 2016 | Segmental Recurrent Neural Networks. Lingpeng Kong, Chris Dyer, Noah A. Smith |
| 2016 | Sequence Level Training with Recurrent Neural Networks. Marc'Aurelio Ranzato, Sumit Chopra, Michael Auli, Wojciech Zaremba |
| 2016 | Session-based Recommendations with Recurrent Neural Networks. Balázs Hidasi, Alexandros Karatzoglou, Linas Baltrunas, Domonkos Tikk |
| 2016 | SparkNet: Training Deep Networks in Spark. Philipp Moritz, Robert Nishihara, Ion Stoica, Michael I. Jordan |
| 2016 | Super-Resolution with Deep Convolutional Sufficient Statistics. Joan Bruna, Pablo Sprechmann, Yann LeCun |
| 2016 | Surpassing Humans in Boundary Detection using Deep Learning. Iasonas Kokkinos |
| 2016 | The Goldilocks Principle: Reading Children's Books with Explicit Memory Representations. Felix Hill, Antoine Bordes, Sumit Chopra, Jason Weston |
| 2016 | The Variational Fair Autoencoder. Christos Louizos, Kevin Swersky, Yujia Li, Max Welling, Richard S. Zemel |
| 2016 | Towards AI-Complete Question Answering: A Set of Prerequisite Toy Tasks. Jason Weston, Antoine Bordes, Sumit Chopra, Tomás Mikolov |
| 2016 | Towards Universal Paraphrastic Sentence Embeddings. John Wieting, Mohit Bansal, Kevin Gimpel, Karen Livescu |
| 2016 | Training CNNs with Low-Rank Filters for Efficient Image Classification. Yani Ioannou, Duncan P. Robertson, Jamie Shotton, Roberto Cipolla, Antonio Criminisi |
| 2016 | Unifying distillation and privileged information. David Lopez-Paz, Léon Bottou, Bernhard Schölkopf, Vladimir Vapnik |
| 2016 | Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks. Alec Radford, Luke Metz, Soumith Chintala |
| 2016 | Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks. Jost Tobias Springenberg |
| 2016 | Variable Rate Image Compression with Recurrent Neural Networks. George Toderici, Sean M. O'Malley, Sung Jin Hwang, Damien Vincent, David Minnen, Shumeet Baluja, Michele Covell, Rahul Sukthankar |
| 2016 | Variational Auto-encoded Deep Gaussian Processes. Zhenwen Dai, Andreas C. Damianou, Javier González, Neil D. Lawrence |
| 2016 | Variational Gaussian Process. Dustin Tran, Rajesh Ranganath, David M. Blei |
| 2016 | When crowds hold privileges: Bayesian unsupervised representation learning with oracle constraints. Theofanis Karaletsos, Serge J. Belongie, Gunnar Rätsch |