From the 1 of 140 linked papers with an AI index.
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OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks
Pierre Sermanet, David Eigen, Xiang Zhang +3
We present an integrated framework for using Convolutional Networks for classification, localization and detection. We show how a multiscale and sliding window approach can be effi…
Spectral Networks and Locally Connected Networks on Graphs
Joan Bruna, Wojciech Zaremba, Arthur Szlam +1
Convolutional Neural Networks are extremely efficient architectures in image and audio recognition tasks, thanks to their ability to exploit the local translational invariance of s…
Fast Training of Convolutional Networks through FFTs
Michael Mathieu, Mikael Henaff, Yann LeCun
Convolutional networks are one of the most widely employed architectures in computer vision and machine learning. In order to leverage their ability to learn complex functions, lar…
Understanding Deep Architectures using a Recursive Convolutional Network
David Eigen, Jason Rolfe, Rob Fergus +1
A key challenge in designing convolutional network models is sizing them appropriately. Many factors are involved in these decisions, including number of layers, feature maps, kern…
Signal Recovery from Pooling Representations
Joan Bruna, Arthur Szlam, Yann LeCun
In this work we compute lower Lipschitz bounds of pooling operators for as well as pooling operators preceded by half-rectification layers. These…
Learning Stable Group Invariant Representations with Convolutional Networks
Joan Bruna, Arthur Szlam, Yann LeCun
Transformation groups, such as translations or rotations, effectively express part of the variability observed in many recognition problems. The group structure enables the constru…