ICLR 2016 - Workshop Track International Conference on Learning Representations 论文papers

Please see the venue website (http://www.iclr.cc/doku.php?id=iclr2016:main) for more information.

Submission deadline: 18 Feb 2016

BLACK BOX VARIATIONAL INFERENCE FOR STATE SPACE MODELSpdf

Evan Archer, Il Memming Park, Lars Buesing, John Cunningham, Liam Paninski

Fine-grained pose prediction, normalization, and recognitionpdf

Ning Zhang, Evan Shelhamer, Yang Gao, Trevor Darrell

Neural Network Training Variations in Speech and Subsequent Performance Evaluationpdf

Ewout van den Berg, Bhuvana Ramabhadran, Michael Picheny

Improving Variational Inference with Inverse Autoregressive Flowpdf

Diederik P. Kingma, Tim Salimans, Max Welling

Manifold traversal using density ridgespdf

Jonas Nordhaug Myhre, Michael Kampffmeyer, Robert Jenssen

Neural Variational Random Field Learningpdf

Volodymyr Kuleshov, Stefano Ermon

Learning Genomic Representations to Predict Clinical Outcomes in Cancerpdf

Safoora Yousefi, Congzheng Song, Nelson Nauata, Lee Cooper

Understanding Very Deep Networks via Volume Conservationpdf

Thomas Unterthiner, Sepp Hochreiter

Fixed Point Quantization of Deep Convolutional Networkspdf

Darryl D. Lin, Sachin S. Talathi, V. Sreekanth Annapureddy

Learning stable representations in a changing world with on-line t-SNE: proof of concept in the songbirdpdf

Stéphane Deny, Emily Mackevicius, Tatsuo Okubo, Gordon Berman, Joshua Shaevitz, Michale Fee

A Neural Architecture for Representing and Reasoning about Spatial Relationshipspdf

Eric Weiss, Brian Cheung, Bruno Olshausen

Stuck in a What? Adventures in Weight Spacepdf

Zachary C. Lipton

Contextual convolutional neural network filtering improves EM image segmentationpdf

Xundong Wu, Yong Wu, Ligia Toro,Enrico Stefani

Input-Convex Deep Networkspdf

Brandon Amos, J. Zico Kolter

Distinct Class Saliency Maps for Multiple Object Imagespdf

Wataru Shimoda, Keiji Yanai

Learning to SMILE(S)pdf

Stanisław Jastrzębski, Damian Leśniak, Wojciech Marian Czarnecki

Understanding Visual Concepts with Continuation Learningpdf

William F. Whitney, Michael Chang, Tejas Kulkarni, Joshua B. Tenenbaum

Generative Adversarial Metricpdf

Daniel Jiwoong Im, Chris Dongjoo Kim, Hui Jiang, Roland Memisevic

Why are deep nets reversible: A simple theory, with implications for trainingpdf

Sanjeev Arora, Yingyu Liang, Tengyu Ma

Revise Saturated Activation Functionspdf

Bing Xu, Ruitong Huang, Mu Li

Learning Retinal Tiling in a Model of Visual Attentionpdf

Brian Cheung, Eric Weiss, Bruno Olshausen

Applying Representation Learning for Educational Data Miningpdf

Milagro Teruel, Laura Alonso Alemany

Deep Motif: Visualizing Genomic Sequence Classificationspdf

Jack Lanchantin, Ritambhara Singh, Zeming Lin, & Yanjun Qi

JOINT STOCHASTIC APPROXIMATION LEARNING OF HELMHOLTZ MACHINESpdf

HaotianXu, Zhijian Ou

Alternative structures for character-level RNNspdf

Piotr Bojanowski, Armand Joulin, Tomas Mikolov

Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learningpdf

Christian Szegedy, Sergey Ioffe, Vincent Vanhoucke

Learning Dense Convolutional Embeddings for Semantic Segmentationpdf

Adam W. Harley, Konstantinos G. Derpanis, Iasonas Kokkinos

Do Deep Convolutional Nets Really Need to be Deep (Or Even Convolutional)?pdf

Gregor Urban, Krzysztof J. Geras, Samira Ebrahimi Kahou, Ozlem Aslan Shengjie Wang, Rich Caruana, Abdelrahman Mohamed, Matthai Philipose, Matt Richardson

A Differentiable Transition Between Additive and Multiplicative Neuronspdf

Wiebke Koepp, Patrick van der Smagt, Sebastian Urban

Blending LSTMs into CNNspdf

Krzysztof J. Geras, Abdel-rahman Mohamed, Rich Caruana, Gregor Urban, Shengjie Wang, Ozlem Aslan, Matthai Philipose, Matthew Richardson, Charles Sutton

A CONTROLLER-RECOGNIZER FRAMEWORK: HOW NECESSARY IS RECOGNITION FOR CONTROL?pdf

Marcin Moczulski, Kelvin Xu, Aaron Courville, Kyunghyun Cho

A constrained l1 minimization approach for estimating multiple Sparse Gaussian or Nonparanormal Graphical Modelspdf

Beilun Wang, Ritambhara Singh, Yanjun Qi

Unsupervised Learning with Imbalanced Data via Structure Consolidation Latent Variable Modelpdf

Fariba Yousefi, Zhenwen Dai, Carl Henrik Ek, Neil Lawrence

Fully Convolutional Nerual Network for Body Part Segmentationpdf

David Frank, Richard Kelley, David Feil-Seifer

Spatio-Temporal Video Autoencoder with Differentiable Memorypdf

Viorica Patraucean, Ankur Handa, Roberto Cipolla

Learning visual groups from co-occurrences in space and timepdf

Phillip Isola, Daniel Zoran, Dilip Krishnan, Edward H. Adelson

Deep Autoresolution Networkspdf

Gabriel Pereyra, Christian Szegedy

Resnet in Resnet: Generalizing Residual Architecturespdf

Sasha Targ, Diogo Almeida, Kevin Lyman

Doctor AI: Predicting Clinical Events via Recurrent Neural Networkspdf

Edward Choi, Mohammad Taha Bahadori, Andy Schuetz, Walter F. Stewart, Joshua C. Denny, Bradley A. Malin, Jimeng Sun

Hardware-Oriented Approximation of Convolutional Neural Networkspdf

Philipp Gysel, Mohammad Motamedi, Soheil Ghiasi

Sequence Modeling with Recurrent Tensor Networkspdf

Richard Kelley

GradNets: Dynamic Interpolation Between Neural Architecturespdf

Diogo Almeida, Nate Sauder

Visualizing and Understanding Recurrent Networkspdf

Andrej Karpathy, Justin Johnson, Li Fei-Fei

On-the-fly Network Pruning for Object Detectionpdf

Marc Masana,Joost van de Weijer,Andrew D. Bagdanov

Using Encoder-Decoder Convolutional Networks to Segment Carbon Fiber CTpdf

Daniel Sammons, William P. Winfree

Convolutional Monte Carlo Rollouts for the Game of Gopdf

Peter H Jin, Kurt Keutzer

Neurogenic Deep Learningpdf

Timothy J. Draelos, Nadine E. Miner, Jonathan A. Cox, Christopher C. Lamb, Conrad D. James, James B. Aimone

Rectified Factor Networks for Biclusteringpdf

Djork-Arné Clevert, Thomas Unterthiner, Sepp Hochreiter

Seq-NMS for Video Object Detectionpdf

Wei Han, Pooya Khorrami, Tom Le Paine, Prajit Ramachandran, Mohammad Babaeizadeh, Honghui Shi, Jiana Li, Shuicheng Yan, Thomas S. Huang

CMA-ES for Hyperparameter Optimization of Deep Neural Networkspdf

Ilya Loshchilov, Frank Hutter

Lookahead Convolution Layer for Unidirectional Recurrent Neural Networkspdf

Chong Wang, Dani Yogatama, Adam Coates, Tony Han, Awni Hannun, Bo Xiao

RandomOut: Using a convolutional gradient norm to win The Filter Lotterypdf

Joseph Paul Cohen, Henry Z. Lo, Wei Ding

HARDWARE-FRIENDLY CONVOLUTIONAL NEURAL NETWORK WITH EVEN-NUMBER FILTER SIZEpdf

Song Yao, Song Han, Kaiyuan Guo, Jianqiao Wangni, Yu Wang

Initializing Entity Representations in Relational Modelspdf

Teng Long, Ryan Lowe, Jackie Cheung, Doina Precup

ADDING GRADIENT NOISE IMPROVES LEARNING FOR VERY DEEP NETWORKSpdf

Arvind Neelakantan, Luke Vilnis, Quoc V. Le, Ilya Sutskever, Lukasz Kaiser, Karol Kurach, James Martens

Robust Convolutional Neural Networks under Adversarial Noisepdf

Jonghoon Jin, Aysegul Dundar, Eugenio Culurciello

Guided Sequence-to-Sequence Learning with External Rule Memorypdf

Jiatao Gu, Baotian Hu, Zhengdong Lu, Hang Li, Victor O.K. Li

Deconstructing the Ladder Network Architecturepdf

Mohammad Pezeshki, Linxi Fan, Philemon Brakel, Aaron Courville, Yoshua Bengio

Scalable Gradient-Based Tuning of Continuous Regularization Hyperparameterspdf

Jelena Luketina,Mathias Berglund,Tapani Raiko

Scale Normalizationpdf

Henry Z Lo, Kevin Amaral, Wei Ding

Neural Text Understanding with Attention Sum Readerpdf

Rudolf Kadlec, Martin Schmid, Ondřej Bajgar, Jan Kleindienst

Incorporating Nesterov Momentum into Adampdf

Timothy Dozat

Binding via Reconstruction Clusteringpdf

Klaus Greff, Rupesh Srivastava, Jürgen Schmidhuber

Variational Inference for On-line Anomaly Detection in High-Dimensional Time Seriespdf

Maximilian Sölch, Justin Bayer, Marvin Ludersdorfer, Patrick van der Smagt

Deep Directed Generative Models with Energy-Based Probability Estimationpdf

Taesup Kim, Yoshua Bengio

Unsupervised Learning of Visual Structure using Predictive Generative Networkspdf

William Lotter, Gabriel Kreiman, David Cox

A metric learning approach for graph-based label propagationpdf

Pauline Wauquier,Mikaela Keller

Task Loss Estimation for Structured Predictionpdf

Dzmitry Bahdanau, Dmiriy Serdyuk, Philémon Brakel, Nan Rosemary Ke, Jan Chorowski, Aaron Courville, Yoshua Bengio

Autoencoding for Joint Relation Factorization and Discovery from Textpdf

Diego Marcheggiani, Ivan Titov

Adaptive Natural Gradient Learning Based on Riemannian Metric of Score Matchingpdf

Ryo Karakida, Masato Okada, Shun-ichi Amari

Data Cleaning by Deep Dictionary Learningpdf

Zhongqi Lu,Qiang Yang

RECURRENT MODELS FOR AUDITORY ATTENTION IN MULTI-MICROPHONE DISTANCE SPEECH RECOGNITIONpdf

Suyoun Kim, Ian Lane

Embedding Entity Pairs through Observed Relations for Knowledge Base Completionpdf

Dirk Weissenborn

Neural Enquirer: Learning to Query Tables in Natural Languagepdf

Pengcheng Yin, Zhengdong Lu, Hang Li, Ben Kao

End to end speech recognition in English and Mandarinpdf

Dario Amodei, Rishita Anubhai, Eric Battenberg, Carl Case, Jared Casper, Bryan Catanzaro, Jingdong Chen, Mike Chrzanowski, Adam Coates, Greg Diamos, Erich Elsen, Jesse Engel, Linxi Fan, Christopher Fougner, Tony Han, Awni Hannun, Billy Jun, Patrick LeGresley, Libby Lin, Sharan Narang, Andrew Ng, Sherjil Ozair, Ryan Prenger, Jonathan Raiman, Sanjeev Satheesh, David Seetapun, Shubho Sengupta, Yi Wang, Zhiqian Wang, Chong Wang, Bo Xiao, Dani Yogatama, Jun Zhan, Zhenyao Zhu

Revisiting Distributed Synchronous SGDpdf

Jianmin Chen, Rajat Monga, Samy Bengio, Rafal Jozefowicz

Sparse Distance Weighted Discriminationpdf

Boxiang Wang, Hui Zou

Sequence-to-Sequence RNNs for Text Summarizationpdf

Ramesh Nallapati, Bing Xiang, Bowen Zhou

Document Context Language Modelspdf

Yangfeng Ji, Trevor Cohn, Lingpeng Kong, Chris Dyer, Jacob Eisenstein

Lessons from the Rademacher Complexity for Deep Learningpdf

Jure Sokolic, Raja Giryes, Guillermo Sapiro, Miguel R. D. Rodrigues

Unitary Evolution Recurrent Neural Networkspdf

Martin Arjovsky, Amar Shah, Yoshua Bengio

LSTM-based Deep Learning Models for non-factoid answer selectionpdf

Ming Tan,Cicero dos Santos,Bing Xiang,Bowen Zhou

Variance Reduction in SGD by Distributed Importance Samplingpdf

Guillaume Alain, Alex Lamb, Chinnadhurai Sankar, Aaron Courville, Yoshua Bengio

Neural Variational Inference for Text Processingpdf

Yishu Miao, Lei Yu, Phil Blunsom

Nonparametric Canonical Correlation Analysispdf

Tomer Michaeli, Weiran Wang, Karen Livescu

Persistent RNNs: Stashing Weights on Chippdf

Greg Diamos, Shubho Sengupta, Bryan Catanzaro, Mike Chrzanowski, Adam Coates, Erich Elsen, Jesse Engel, Awni Hannun, Sanjeev Satheesh

Convolutional Clustering for Unsupervised Learningpdf

Aysegul Dundar, Jonghoon Jin, and Eugenio Culurciello

Temporal Convolutional Neural Networks for Diagnosis from Lab Testspdf

Narges Razavian, David Sontag

Bidirectional Helmholtz Machinespdf

Jorg Bornschein, Samira Shabanian, Asja Fischer, Yoshua Bengio

Data Cleaning by Deep Dictionary Learningpdf

Zhongqi Lu, Qiang Yang

Neural network-based clustering using pairwise constraintspdf

Yen-Chang Hsu, Zsolt Kira

Multi-layer Representation Learning for Medical Conceptspdf

Edward Choi,Mohammad Taha Bahadori,Jimeng Sun,Elizabeth Searles,Catherine Coffey

Deep Bayesian Neural Nets as Deep Matrix Gaussian Processespdf

Christos Louizos, Max Welling

Online Batch Selection for Faster Training of Neural Networkspdf

Ilya Loshchilov,Frank Hutter

Close-to-clean regularization relates virtual adversarial training, ladder networks and otherspdf

Mudassar Abbas, Jyri Kivinen, Tapani Raiko

Neural Generative Question Answeringpdf

Jun Yin, Xin Jiang, Zhengdong Lu, Lifeng Shang, Hang Li, Xiaoming Li

Convolutional Models for Joint Object Categorization and Pose Estimationpdf

Mohamed Elhoseiny, Tarek El-Gaaly, Amr Bakry, Ahmed Elgammal

Learning to Represent Words in Context with Multilingual Supervisionpdf

Kazuya Kawakami, Chris Dyer

Comparative Study of Caffe, Neon, Theano, and Torch for Deep Learningpdf

Soheil Bahrampour, Naveen Ramakrishnan, Lukas Schott, Mohak Shah

ParseNet: Looking Wider to See Betterpdf

Wei Liu, Andrew Rabinovich, Alexander C. Berg

How far can we go without convolution: Improving fully-connected networkspdf

Zhouhan Lin, Roland Memisevic, Kishore Konda

Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inferencepdf

Yarin Gal, Zoubin Ghahramani

VARIATIONAL STOCHASTIC GRADIENT DESCENTpdf

Michael Tetelman

Mixtures of Sparse Autoregressive Networkspdf

Marc Goessling, Yali Amit

Efficient Inference in Occlusion-Aware Generative Models of Imagespdf

Jonathan Huang, Kevin Murphy

PerforatedCNNs: Acceleration through Elimination of Redundant Convolutionspdf

Michael Figurnov, Dmitry Vetrov, Pushmeet Kohli

Dynamic Capacity Networkspdf

Amjad Almahairi, Nicolas Ballas, Tim Cooijmans, Yin Zheng, Hugo Larochelle, Aaron Courville

Conditional computation in neural networks for faster modelspdf

Emmanuel Bengio, Pierre-Luc Bacon, Joelle Pineau, Doina Precup

Adversarial Autoencoderspdf

Alireza Makhzani, Jonathon Shlens, Navdeep Jaitly, Ian Goodfellow

Learning to Decompose for Object Detection and Instance Segmentationpdf

Eunbyung Park, Alexander C. Berg

Coverage-based Neural Machine Translationpdf

Zhaopeng Tu, Zhengdong Lu, Yang Liu, Xiaohua Liu, Hang Li

Stacked What-Where Auto-encoderspdf

Junbo Zhao, Michael Mathieu, Ross Goroshin, Yann LeCun

Learning Representations of Affect from Speechpdf

Sayan Ghosh, Eugene Laksana, Louis-Philippe Morency, Stefan Scherer

Universum Prescription: Regularization using Unlabeled Datapdf

Xiang Zhang,Yann LeCun

Deep Reinforcement Learning with an Action Space Defined by Natural Languagepdf

Ji He, Jianshu Chen, Xiaodong He, Jianfeng Gao, Lihong Li, Li Deng, Mari Ostendorf

Generating Sentences from a Continuous Spacepdf

Samuel R. Bowman, Luke Vilnis, Oriol Vinyals, Andrew M. Dai, Rafal Jozefowicz, Samy Bengio

Using Deep Learning to Predict Demographics from Mobile Phone Metadatapdf

Bjarke Felbo, Pål Sundsøy, Alex 'Sandy' Pentland, Sune Lehmann, Yves-Alexandre de Montjoye

A Minimalistic Approach to Sum-Product Network Learning for Real Applicationspdf

Viktoriya Krakovna, Moshe Looks

Feed-Forward Networks with Attention Can Solve Some Long-Term Memory Problemspdf

Colin Raffel,Daniel P. W. Ellis

Improving performance of recurrent neural network with relu nonlinearitypdf

Sachin S. Talathi, Aniket Vartak

Basic Level Categorization Facilitates Visual Object Recognitionpdf

Panqu Wang, Garrison Cottrell

A Deep Memory-based Architecture for Sequence-to-Sequence Learningpdf

Fandong Meng, Zhengdong Lu, Zhaopeng Tu, Hang Li, Qun Liu

Action Recognition using Visual Attentionpdf

Shikhar Sharma, Ryan Kiros, Ruslan Salakhutdinov

Empirical performance upper bounds for image and video captioningpdf

Li Yao, Nicolas Ballas, Kyunghyun Cho, John R. Smith, Yoshua Bengio

Learning Document Embeddings by Predicting N-grams for Sentiment Classification of Long Movie Reviewspdf

Bofang Li, Tao Liu, Xiaoyong Du, Deyuan Zhang, Zhe Zhao