Conference Proceedings

Listed below are the conference papers accepted to the International Conference on Learning Representations (ICLR) 2014.

Multilingual Distributed Representations without Word Alignment

    Karl Moritz Hermann; Phil Blunsom

Zero-Shot Learning by Convex Combination of Semantic Embeddings

    Mohammad Norouzi; Tomas Mikolov; Samy Bengio; Yoram Singer; Jonathon Shlens; Andrea Frome; Greg S. Corrado; Jeffrey Dean

Exact solutions to the nonlinear dynamics of learning in deep linear neural networks

    Andrew M. Saxe; James L. McClelland; Surya Ganguli

Revisiting Natural Gradient for Deep Networks

    Razvan Pascanu; Yoshua Bengio

Unit Tests for Stochastic Optimization
    Tom Schaul; Ioannis Antonoglou; David Silver 

The return of AdaBoost.MH: multi-class Hamming trees

    Balázs Kégl

Neuronal Synchrony in Complex-Valued Deep Networks

    David P. Reichert; Thomas Serre

Bounding the Test Log-Likelihood of Generative Models

    Yoshua Bengio; Li Yao; KyungHyun Cho

A Generative Product-of-Filters Model of Audio

    Dawen Liang; Mathew D. Hoffman; Gautham Mysore

How to Construct Deep Recurrent Neural Networks

    Razvan Pascanu; Caglar Gulcehre; Kyunghyun Cho; Yoshua Bengio

Zero-Shot Learning and Clustering for Semantic Utterance Classification

    Yann N. Dauphin; Gokhan Tur; Dilek Hakkani-Tur; Larry Heck

An empirical analysis of dropout in piecewise linear networks

    David Warde-Farley; Ian J. Goodfellow; Aaron Courville; Yoshua Bengio

An Empirical Investigation of Catastrophic Forgeting in Gradient-Based Neural Networks

    Ian J. Goodfellow; Mehdi Mirza; Da Xiao; Aaron Courville; Yoshua Bengio;

On Fast Dropout and its Applicability to Recurrent Networks

    Justin Bayer; Christian Osendorfer; Daniela Korhammer; Nutan Chen; Sebastian Urban; Patrick van der Smagt

Network In Network

    Min Lin; Qiang Chen; Shuicheng Yan

Auto-Encoding Variational Bayes

    Diederik P. Kingma; Max Welling

Group-sparse Embeddings in Collective Matrix Factorization

    Arto Klami; Guillaume Bouchard; Abhishek Tripathi

Learning Human Pose Estimation Features with Convolutional Networks

    Ajrun Jain; Jonathan Tompson; Mykhaylo Andriluka; Graham W. Taylor; Christoph Bregler

EXMOVES: Classifier-based Features for Scalable Action Recognition

    Du Tran; Lorenzo Torresani

On the number of inference regions of deep feed forward networks with piece-wise linear activations

    Razvan Pascanu; Guido Montufar; Yoshua Bengio

Intriguing properties of neural networks

    Christian Szegedy; Wojciech Zaremba; Ilya Sutskever; Joan Bruna; Dumitru Erhan; Ian Goodfellow; Rob Fergus

Fast Training of Convolutional Networks through FFTs

    Michael Mathieu; Mikael Henaff; Yann LeCun

Deep and Wide Multiscale Recursive Networks for Robust Image Labeling

    Gary B. Huang; Viren Jain

Some Improvements on Deep Convolutional Neural Network Based Image Classification

    Andrew G. Howard

Deep Convolutional Ranking for Multilabel Image Annotation

    Yunchao Gong; Yangqing Jia; Thomas Leung; Alexander Toshev; Sergey Ioffe

Learning to encode motion using spatio-temporal synchrony

    Kishore Reddy Konda; Roland Memisevic; Vincent Michalski

Multi-View Priors for Learning Detectors from Sparse Viewpoint Data

    Bojan Pepik; Michael Stark; Peter Gehler; Bernt Schiele

k-Sparse Autoencoders

    Alireza Makhzani; Brendan Frey

OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks

    Pierre Sermanet; Rob Fergus; Yann LeCun; Xiang Zhang; David Eigen; Michael Mathieu

Multi-digit Number Recognition from Street View Imagery using Deep Convolutional Neural Networks

    Ian J. Goodfellow; Yaroslav Bulatov; Julian Ibarz; Sacha Arnoud; Vinay Shet

Sequentially Generated Instance-Dependent Image Representations for Classification

    Ludovic Denoyer; Matthieu Cord; Patrick Gallinari; Nicolas Thome; Gabriel Dulac-Arnold

Learned versus Hand-Designed Feature Representations for 3d Agglomeration

    John A. Bogovic; Gary B. Huang; Viren Jain

Spectral Networks and Locally Connected Networks on Graphs

    Joan Bruna; Wojciech Zaremba; Arthur Szlam; Yann LeCun

Sparse similarity-preserving hashing

    Alex M. Bronstein; Pablo Sprechmann; Michael M. Bronstein; Jonathan Masci; Guillermo Sapiro

Learning Transformations for Classification Forests

    Qiang Qiu; Guillermo Sapiro