ICLR 2015:San Diego, USA

International Conference on Learning Representations, May 7 - 9, 2015, San Diego, USA

Paper Num: 116 || Session Num: 3

• Main Conference - Oral Presentations 11
• Main Conference - Poster Presentations 31
• Workshop Papers 74

Main Conference - Oral Presentations 11

1. Word Representations via Gaussian Embedding

【Paper Link】 【Pages】:

【Authors】: Luke Vilnis and Andrew McCallum

【Abstract】:

【Keywords】:

2. Deep Captioning with Multimodal Recurrent Neural Networks (m-RNN)

【Paper Link】 【Pages】:

【Authors】: Junhua Mao, Wei Xu, Yi Yang, Jiang Wang, and Alan Yuille

【Abstract】:

【Keywords】:

3. Deep Structured Output Learning for Unconstrained Text Recognition

【Paper Link】 【Pages】:

【Authors】: Max Jaderberg, Karen Simonyan, Andrea Vedaldi, and Andrew Zisserman

【Abstract】:

【Keywords】:

4. Very Deep Convolutional Networks for Large-Scale Image Recognition

【Paper Link】 【Pages】:

【Authors】: Karen Simonyan and Andrew Zisserman

【Abstract】:

【Keywords】:

5. Fast Convolutional Nets With fbfft: A GPU Performance Evaluation

【Paper Link】 【Pages】:

【Authors】: Nicolas Vasilache, Jeff Johnson, Michael Mathieu, Soumith Chintala, Serkan Piantino, and Yann LeCun

【Abstract】:

【Keywords】:

6. Reweighted Wake-Sleep

【Paper Link】 【Pages】:

【Authors】: Jorg Bornschein and Yoshua Bengio

【Abstract】:

【Keywords】:

7. The local low-dimensionality of natural images

【Paper Link】 【Pages】:

【Authors】: Olivier Henaff, Johannes Balle, Neil Rabinowitz, and Eero Simoncelli

【Abstract】:

【Keywords】:

8. Memory Networks

【Paper Link】 【Pages】:

【Authors】: Jason Weston, Sumit Chopra, and Antoine Bordes

【Abstract】:

【Keywords】:

9. Object detectors emerge in Deep Scene CNNs

【Paper Link】 【Pages】:

【Authors】: Bolei Zhou, Aditya Khosla, Agata Lapedriza, Aude Oliva, and Antonio Torralba

【Abstract】:

【Keywords】:

10. Qualitatively characterizing neural network optimization problems

【Paper Link】 【Pages】:

【Authors】: Ian Goodfellow and Oriol Vinyals

【Abstract】:

【Keywords】:

11. Neural Machine Translation by Jointly Learning to Align and Translate

【Paper Link】 【Pages】:

【Authors】: Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio

【Abstract】:

【Keywords】:

Main Conference - Poster Presentations 31

12. FitNets: Hints for Thin Deep Nets

【Paper Link】 【Pages】:

【Authors】: Adriana Romero, Nicolas Ballas, Samira Ebrahimi Kahou, Antoine Chassang, Carlo Gatta, and Yoshua Bengio

【Abstract】:

【Keywords】:

13. Techniques for Learning Binary Stochastic Feedforward Neural Networks

【Paper Link】 【Pages】:

【Authors】: Tapani Raiko, Mathias Berglund, Guillaume Alain, and Laurent Dinh

【Abstract】:

【Keywords】:

14. Reweighted Wake-Sleep

【Paper Link】 【Pages】:

【Authors】: Jorg Bornschein and Yoshua Bengio

【Abstract】:

【Keywords】:

15. Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs

【Paper Link】 【Pages】:

【Authors】: Liang-Chieh Chen, George Papandreou, Iasonas Kokkinos, Kevin Murphy, and Alan Yuille

【Abstract】:

【Keywords】:

16. Multiple Object Recognition with Visual Attention

【Paper Link】 【Pages】:

【Authors】: Jimmy Ba, Volodymyr Mnih, and Koray Kavukcuoglu

【Abstract】:

【Keywords】:

17. Deep Narrow Boltzmann Machines are Universal Approximators

【Paper Link】 【Pages】:

【Authors】: Guido Montufar

【Abstract】:

【Keywords】:

18. Transformation Properties of Learned Visual Representations

【Paper Link】 【Pages】:

【Authors】: Taco Cohen and Max Welling

【Abstract】:

【Keywords】:

19. Joint RNN-Based Greedy Parsing and Word Composition

【Paper Link】 【Pages】:

【Authors】: Joël Legrand and Ronan Collobert

【Abstract】:

【Keywords】:

20. Adam: A Method for Stochastic Optimization

【Paper Link】 【Pages】:

【Authors】: Jimmy Ba and Diederik Kingma

【Abstract】:

【Keywords】:

21. Neural Machine Translation by Jointly Learning to Align and Translate

【Paper Link】 【Pages】:

【Authors】: Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio

【Abstract】:

【Keywords】:

22. Scheduled denoising autoencoders

【Paper Link】 【Pages】:

【Authors】: Krzysztof Geras and Charles Sutton

【Abstract】:

【Keywords】:

23. Embedding Entities and Relations for Learning and Inference in Knowledge Bases

【Paper Link】 【Pages】:

【Authors】: Bishan Yang, Scott Yih, Xiaodong He, Jianfeng Gao, and Li Deng

【Abstract】:

【Keywords】:

24. The local low-dimensionality of natural images

【Paper Link】 【Pages】:

【Authors】: Olivier Henaff, Johannes Balle, Neil Rabinowitz, and Eero Simoncelli

【Abstract】:

【Keywords】:

25. Explaining and Harnessing Adversarial Examples

【Paper Link】 【Pages】:

【Authors】: Ian Goodfellow, Jon Shlens, and Christian Szegedy

【Abstract】:

【Keywords】:

26. Modeling Compositionality with Multiplicative Recurrent Neural Networks

【Paper Link】 【Pages】:

【Authors】: Ozan Irsoy and Claire Cardie

【Abstract】:

【Keywords】:

27. Very Deep Convolutional Networks for Large-Scale Image Recognition

【Paper Link】 【Pages】:

【Authors】: Karen Simonyan and Andrew Zisserman

【Abstract】:

【Keywords】:

28. Speeding-up Convolutional Neural Networks Using Fine-tuned CP-Decomposition

【Paper Link】 【Pages】:

【Authors】: Vadim Lebedev, Yaroslav Ganin, Victor Lempitsky, Maksim Rakhuba, and Ivan Oseledets

【Abstract】:

【Keywords】:

29. Deep Captioning with Multimodal Recurrent Neural Networks (m-RNN)

【Paper Link】 【Pages】:

【Authors】: Junhua Mao, Wei Xu, Yi Yang, Jiang Wang, and Alan Yuille

【Abstract】:

【Keywords】:

30. Deep Structured Output Learning for Unconstrained Text Recognition

【Paper Link】 【Pages】:

【Authors】: Max Jaderberg, Karen Simonyan, Andrea Vedaldi, and Andrew Zisserman

【Abstract】:

【Keywords】:

31. Zero-bias autoencoders and the benefits of co-adapting features

【Paper Link】 【Pages】:

【Authors】: Kishore Konda, Roland Memisevic, and David Krueger

【Abstract】:

【Keywords】:

32. Automatic Discovery and Optimization of Parts for Image Classification

【Paper Link】 【Pages】:

【Authors】: Sobhan Naderi Parizi, Andrea Vedaldi, Andrew Zisserman, and Pedro Felzenszwalb

【Abstract】:

【Keywords】:

33. Understanding Locally Competitive Networks

【Paper Link】 【Pages】:

【Authors】: Rupesh Srivastava, Jonathan Masci, Faustino Gomez, and Juergen Schmidhuber

【Abstract】:

【Keywords】:

34. Leveraging Monolingual Data for Crosslingual Compositional Word Representations

【Paper Link】 【Pages】:

【Authors】: Hubert Soyer, Pontus Stenetorp, and Akiko Aizawa

【Abstract】:

【Keywords】:

35. Move Evaluation in Go Using Deep Convolutional Neural Networks

【Paper Link】 【Pages】:

【Authors】: Chris Maddison, Aja Huang, Ilya Sutskever, and David Silver

【Abstract】:

【Keywords】:

36. Fast Convolutional Nets With fbfft: A GPU Performance Evaluation

【Paper Link】 【Pages】:

【Authors】: Nicolas Vasilache, Jeff Johnson, Michael Mathieu, Soumith Chintala, Serkan Piantino, and Yann LeCun

【Abstract】:

【Keywords】:

37. Word Representations via Gaussian Embedding

【Paper Link】 【Pages】:

【Authors】: Luke Vilnis and Andrew McCallum

【Abstract】:

【Keywords】:

38. Qualitatively characterizing neural network optimization problems

【Paper Link】 【Pages】:

【Authors】: Ian Goodfellow and Oriol Vinyals

【Abstract】:

【Keywords】:

39. Memory Networks

【Paper Link】 【Pages】:

【Authors】: Jason Weston, Sumit Chopra, and Antoine Bordes

【Abstract】:

【Keywords】:

40. Generative Modeling of Convolutional Neural Networks

【Paper Link】 【Pages】:

【Authors】: Jifeng Dai, Yang Lu, and Ying-Nian Wu

【Abstract】:

【Keywords】:

41. A Unified Perspective on Multi-Domain and Multi-Task Learning

【Paper Link】 【Pages】:

【Authors】: Yongxin Yang and Timothy Hospedales

【Abstract】:

【Keywords】:

42. Object detectors emerge in Deep Scene CNNs

【Paper Link】 【Pages】:

【Authors】: Bolei Zhou, Aditya Khosla, Agata Lapedriza, Aude Oliva, and Antonio Torralba

【Abstract】:

【Keywords】:

Workshop Papers 74

43. Learning Non-deterministic Representations with Energy-based Ensembles

【Paper Link】 【Pages】:

【Authors】: Maruan Al-Shedivat, Emre Neftci, and Gert Cauwenberghs

【Abstract】:

【Keywords】:

44. Diverse Embedding Neural Network Language Models

【Paper Link】 【Pages】:

【Authors】: Kartik Audhkhasi, Abhinav Sethy, and Bhuvana Ramabhadran

【Abstract】:

【Keywords】:

45. Hot Swapping for Online Adaptation of Optimization Hyperparameters

【Paper Link】 【Pages】:

【Authors】: Kevin Bache, Dennis Decoste, and Padhraic Smyth

【Abstract】:

【Keywords】:

46. Representation Learning for cold-start recommendation

【Paper Link】 【Pages】:

【Authors】: Gabriella Contardo, Ludovic Denoyer, and Thierry Artieres

【Abstract】:

【Keywords】:

47. Training Convolutional Networks with Noisy Labels

【Paper Link】 【Pages】:

【Authors】: Sainbayar Sukhbaatar, Joan Bruna, Manohar Paluri, Lubomir Bourdev, and Rob Fergus

【Abstract】:

【Keywords】:

48. Striving for Simplicity: The All Convolutional Net

【Paper Link】 【Pages】:

【Authors】: Alexey Dosovitskiy, Jost Tobias Springenberg, Thomas Brox, and Martin Riedmiller

【Abstract】:

【Keywords】:

49. Learning linearly separable features for speech recognition using convolutional neural networks

【Paper Link】 【Pages】:

【Authors】: Dimitri Palaz, Mathew Magimai Doss, and Ronan Collobert

【Abstract】:

【Keywords】:

50. Training Deep Neural Networks on Noisy Labels with Bootstrapping

【Paper Link】 【Pages】:

【Authors】: Scott Reed, Honglak Lee, Dragomir Anguelov, Christian Szegedy, Dumitru Erhan, and Andrew Rabinovich

【Abstract】:

【Keywords】:

51. On the Stability of Deep Networks

【Paper Link】 【Pages】:

【Authors】: Raja Giryes, Guillermo Sapiro, and Alex Bronstein

【Abstract】:

【Keywords】:

52. Audio source separation with Discriminative Scattering Networks

【Paper Link】 【Pages】:

【Authors】: Joan Bruna, Yann LeCun, and Pablo Sprechmann

【Abstract】:

【Keywords】:

53. Simple Image Description Generator via a Linear Phrase-Based Model

【Paper Link】 【Pages】:

【Authors】: Pedro Pinheiro, Rémi Lebret, and Ronan Collobert

【Abstract】:

【Keywords】:

54. Stochastic Descent Analysis of Representation Learning Algorithms

【Paper Link】 【Pages】:

【Authors】: Richard Golden

【Abstract】:

【Keywords】:

55. On Distinguishability Criteria for Estimating Generative Models

【Paper Link】 【Pages】:

【Authors】: Ian Goodfellow

【Abstract】:

【Keywords】:

56. Embedding Word Similarity with Neural Machine Translation

【Paper Link】 【Pages】:

【Authors】: Felix Hill, Kyunghyun Cho, Sebastien Jean, Coline Devin, and Yoshua Bengio

【Abstract】:

【Keywords】:

57. Deep metric learning using Triplet network

【Paper Link】 【Pages】:

【Authors】: Elad Hoffer and Nir Ailon

【Abstract】:

【Keywords】:

58. Understanding Minimum Probability Flow for RBMs Under Various Kinds of Dynamics

【Paper Link】 【Pages】:

【Authors】: Daniel Jiwoong Im, Ethan Buchman, and Graham Taylor

【Abstract】:

【Keywords】:

59. A Group Theoretic Perspective on Unsupervised Deep Learning

【Paper Link】 【Pages】:

【Authors】: Arnab Paul and Suresh Venkatasubramanian

【Abstract】:

【Keywords】:

60. Learning Longer Memory in Recurrent Neural Networks

【Paper Link】 【Pages】:

【Authors】: Tomas Mikolov, Armand Joulin, Sumit Chopra, Michael Mathieu, and Marc'Aurelio Ranzato

【Abstract】:

【Keywords】:

61. Inducing Semantic Representation from Text by Jointly Predicting and Factorizing Relations

【Paper Link】 【Pages】:

【Authors】: Ivan Titov and Ehsan Khoddam

【Abstract】:

【Keywords】:

62. NICE: Non-linear Independent Components Estimation

【Paper Link】 【Pages】:

【Authors】: Laurent Dinh, David Krueger, and Yoshua Bengio

【Abstract】:

【Keywords】:

63. Discovering Hidden Factors of Variation in Deep Networks

【Paper Link】 【Pages】:

【Authors】: Brian Cheung, Jesse Livezey, Arjun Bansal, and Bruno Olshausen

【Abstract】:

【Keywords】:

64. Tailoring Word Embeddings for Bilexical Predictions: An Experimental Comparison

【Paper Link】 【Pages】:

【Authors】: Pranava Swaroop Madhyastha, Xavier Carreras, and Ariadna Quattoni

【Abstract】:

【Keywords】:

65. On Learning Vector Representations in Hierarchical Label Spaces

【Paper Link】 【Pages】:

【Authors】: Jinseok Nam and Johannes Fürnkranz

【Abstract】:

【Keywords】:

66. In Search of the Real Inductive Bias: On the Role of Implicit Regularization in Deep Learning

【Paper Link】 【Pages】:

【Authors】: Behnam Neyshabur, Ryota Tomioka, and Nathan Srebro

【Abstract】:

【Keywords】:

67. Algorithmic Robustness for Semi-Supervised (ϵ, γ, τ)-Good Metric Learning

【Paper Link】 【Pages】:

【Authors】: Maria-Irina Nicolae, Marc Sebban, Amaury Habrard, Éric Gaussier, and Massih-Reza Amini

【Abstract】:

【Keywords】:

68. Real-World Font Recognition Using Deep Network and Domain Adaptation

【Paper Link】 【Pages】:

【Authors】: Zhangyang Wang, Jianchao Yang, Hailin Jin, Eli Shechtman, Aseem Agarwala, Jon Brandt, and Thomas Huang

【Abstract】:

【Keywords】:

69. Score Function Features for Discriminative Learning

【Paper Link】 【Pages】:

【Authors】: Majid Janzamin, Hanie Sedghi, and Anima Anandkumar

【Abstract】:

【Keywords】:

70. Parallel training of DNNs with Natural Gradient and Parameter Averaging

【Paper Link】 【Pages】:

【Authors】: Daniel Povey, Xioahui Zhang, and Sanjeev Khudanpur

【Abstract】:

【Keywords】:

71. A Generative Model for Deep Convolutional Learning

【Paper Link】 【Pages】:

【Authors】: Yunchen Pu, Xin Yuan, and Lawrence Carin

【Abstract】:

【Keywords】:

72. Random Forests Can Hash

【Paper Link】 【Pages】:

【Authors】: Qiang Qiu, Guillermo Sapiro, and Alex Bronstein

【Abstract】:

【Keywords】:

73. Provable Methods for Training Neural Networks with Sparse Connectivity

【Paper Link】 【Pages】:

【Authors】: Hanie Sedghi, and Anima Anandkumar

【Abstract】:

【Keywords】:

74. Visual Scene Representations: sufficiency, minimality, invariance and approximation with deep convolutional networks

【Paper Link】 【Pages】:

【Authors】: Stefano Soatto and Alessandro Chiuso

【Abstract】:

【Keywords】:

75. Deep learning with Elastic Averaging SGD

【Paper Link】 【Pages】:

【Authors】: Sixin Zhang, Anna Choromanska, and Yann LeCun

【Abstract】:

【Keywords】:

76. Example Selection For Dictionary Learning

【Paper Link】 【Pages】:

【Authors】: Tomoki Tsuchida and Garrison Cottrell

【Abstract】:

【Keywords】:

77. Permutohedral Lattice CNNs

【Paper Link】 【Pages】:

【Authors】: Martin Kiefel, Varun Jampani, and Peter Gehler

【Abstract】:

【Keywords】:

78. Unsupervised Domain Adaptation with Feature Embeddings

【Paper Link】 【Pages】:

【Authors】: Yi Yang and Jacob Eisenstein

【Abstract】:

【Keywords】:

79. Weakly Supervised Multi-embeddings Learning of Acoustic Models

【Paper Link】 【Pages】:

【Authors】: Gabriel Synnaeve and Emmanuel Dupoux

【Abstract】:

【Keywords】:

80. Learning Activation Functions to Improve Deep Neural Networks

【Paper Link】 【Pages】:

【Authors】: Forest Agostinelli, Matthew Hoffman, Peter Sadowski, and Pierre Baldi

【Abstract】:

【Keywords】:

81. Restricted Boltzmann Machine for Classification with Hierarchical Correlated Prior

【Paper Link】 【Pages】:

【Authors】: Gang Chen and Sargur Srihari

【Abstract】:

【Keywords】:

82. Learning Deep Structured Models

【Paper Link】 【Pages】:

【Authors】: Liang-Chieh Chen, Alexander Schwing, Alan Yuille, and Raquel Urtasun

【Abstract】:

【Keywords】:

83. N-gram-Based Low-Dimensional Representation for Document Classification

【Paper Link】 【Pages】:

【Authors】: Rémi Lebret and Ronan Collobert

【Abstract】:

【Keywords】:

84. Low precision arithmetic for deep learning

【Paper Link】 【Pages】:

【Authors】: Matthieu Courbariaux, Yoshua Bengio, and Jean-Pierre David

【Abstract】:

【Keywords】:

85. Theano-based Large-Scale Visual Recognition with Multiple GPUs

【Paper Link】 【Pages】:

【Authors】: Weiguang Ding, Ruoyan Wang, Fei Mao, and Graham Taylor

【Abstract】:

【Keywords】:

86. Improving zero-shot learning by mitigating the hubness problem

【Paper Link】 【Pages】:

【Authors】: Georgiana Dinu and Marco Baroni

【Abstract】:

【Keywords】:

87. Incorporating Both Distributional and Relational Semantics in Word Representations

【Paper Link】 【Pages】:

【Authors】: Daniel Fried and Kevin Duh

【Abstract】:

【Keywords】:

88. Variational Recurrent Auto-Encoders

【Paper Link】 【Pages】:

【Authors】: Otto Fabius and Joost van Amersfoort

【Abstract】:

【Keywords】:

89. Learning Compact Convolutional Neural Networks with Nested Dropout

【Paper Link】 【Pages】:

【Authors】: Chelsea Finn, Lisa Anne Hendricks, and Trevor Darrell

【Abstract】:

【Keywords】:

90. Compact Part-Based Image Representations: Extremal Competition and Overgeneralization

【Paper Link】 【Pages】:

【Authors】: Marc Goessling and Yali Amit

【Abstract】:

【Keywords】:

91. Unsupervised Feature Learning from Temporal Data

【Paper Link】 【Pages】:

【Authors】: Ross Goroshin, Joan Bruna, Jonathan Tompson, David Eigen, and Yann LeCun

【Abstract】:

【Keywords】:

92. Classifier with Hierarchical Topographical Maps as Internal Representation

【Paper Link】 【Pages】:

【Authors】: Pitoyo Hartono, Paul Hollensen, and Thomas Trappenberg

【Abstract】:

【Keywords】:

93. Entity-Augmented Distributional Semantics for Discourse Relations

【Paper Link】 【Pages】:

【Authors】: Yangfeng Ji and Jacob Eisenstein

【Abstract】:

【Keywords】:

94. Flattened Convolutional Neural Networks for Feedforward Acceleration

【Paper Link】 【Pages】:

【Authors】: Jonghoon Jin, Aysegul Dundar, and Eugenio Culurciello

【Abstract】:

【Keywords】:

95. Gradual Training Method for Denoising Auto Encoders

【Paper Link】 【Pages】:

【Authors】: Alexander Kalmanovich and Gal Chechik

【Abstract】:

【Keywords】:

96. Deep Gaze I: Boosting Saliency Prediction with Feature Maps Trained on ImageNet

【Paper Link】 【Pages】:

【Authors】: Matthias Kümmerer, Lucas Theis, and Matthias Bethge

【Abstract】:

【Keywords】:

97. Difference Target Propagation

【Paper Link】 【Pages】:

【Authors】: Dong-Hyun Lee, Saizheng Zhang, Asja Fischer, Antoine Biard, and Yoshua Bengio

【Abstract】:

【Keywords】:

98. Predictive encoding of contextual relationships for perceptual inference, interpolation and prediction

【Paper Link】 【Pages】:

【Authors】: Mingmin Zhao, Chengxu Zhuang, Yizhou Wang, and Tai Sing Lee

【Abstract】:

【Keywords】:

99. Purine: A Bi-Graph based deep learning framework

【Paper Link】 【Pages】:

【Authors】: Min Lin, Shuo Li, Xuan Luo, and Shuicheng Yan

【Abstract】:

【Keywords】:

100. Pixel-wise Deep Learning for Contour Detection

【Paper Link】 【Pages】:

【Authors】: Jyh-Jing Hwang and Tyng-Luh Liu

【Abstract】:

【Keywords】:

101. Ensemble of Generative and Discriminative Techniques for Sentiment Analysis of Movie Reviews

【Paper Link】 【Pages】:

【Authors】: Grégoire Mesnil, Tomas Mikolov, Marc'Aurelio Ranzato, and Yoshua Bengio

【Abstract】:

【Keywords】:

102. Fast Label Embeddings for Extremely Large Output Spaces

【Paper Link】 【Pages】:

【Authors】: Paul Mineiro and Nikos Karampatziakis

【Abstract】:

【Keywords】:

103. An Analysis of Unsupervised Pre-training in Light of Recent Advances

【Paper Link】 【Pages】:

【Authors】: Tom Paine, Pooya Khorrami, Wei Han, and Thomas Huang

【Abstract】:

【Keywords】:

104. Fully Convolutional Multi-Class Multiple Instance Learning

【Paper Link】 【Pages】:

【Authors】: Deepak Pathak, Evan Shelhamer, Jonathan Long, and Trevor Darrell

【Abstract】:

【Keywords】:

105. What Do Deep CNNs Learn About Objects?

【Paper Link】 【Pages】:

【Authors】: Xingchao Peng, Baochen Sun, Karim Ali, and Kate Saenko

【Abstract】:

【Keywords】:

106. Representation using the Weyl Transform

【Paper Link】 【Pages】:

【Authors】: Qiang Qiu, Andrew Thompson, Robert Calderbank, and Guillermo Sapiro

【Abstract】:

【Keywords】:

107. Denoising autoencoder with modulated lateral connections learns invariant representations of natural images

【Paper Link】 【Pages】:

【Authors】: Antti Rasmus, Harri Valpola, and Tapani Raiko

【Abstract】:

【Keywords】:

108. Towards Deep Neural Network Architectures Robust to Adversarial Examples

【Paper Link】 【Pages】:

【Authors】: Shixiang Gu and Luca Rigazio

【Abstract】:

【Keywords】:

109. Explorations on high dimensional landscapes

【Paper Link】 【Pages】:

【Authors】: Levent Sagun, Ugur Guney, and Yann LeCun

【Abstract】:

【Keywords】:

110. Generative Class-conditional Autoencoders

【Paper Link】 【Pages】:

【Authors】: Jan Rudy and Graham Taylor

【Abstract】:

【Keywords】:

111. Attention for Fine-Grained Categorization

【Paper Link】 【Pages】:

【Authors】: Pierre Sermanet, Andrea Frome, and Esteban Real

【Abstract】:

【Keywords】:

112. A Baseline for Visual Instance Retrieval with Deep Convolutional Networks

【Paper Link】 【Pages】:

【Authors】: Ali Sharif Razavian, Josephine Sullivan, Atsuto Maki, and Stefan Carlsson

【Abstract】:

【Keywords】:

113. Visual Scene Representation: Scaling and Occlusion

【Paper Link】 【Pages】:

【Authors】: Stefano Soatto, Jingming Dong, and Nikolaos Karianakis

【Abstract】:

【Keywords】:

114. Deep networks with large output spaces

【Paper Link】 【Pages】:

【Authors】: Sudheendra Vijayanarasimhan, Jon Shlens, Jay Yagnik, and Rajat Monga

【Abstract】:

【Keywords】:

115. Efficient Exact Gradient Update for training Deep Networks with Very Large Sparse Targets

【Paper Link】 【Pages】:

【Authors】: Pascal Vincent

【Abstract】:

【Keywords】:

116. Self-informed neural network structure learning

【Paper Link】 【Pages】:

【Authors】: David Warde-Farley, Andrew Rabinovich, and Dragomir Anguelov

【Abstract】:

【Keywords】: