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4 papers · 2 filters
Sparse Frequency Analysis with Sparse-Derivative Instantaneous Amplitude and Phase Functions
Yin Ding, Ivan W. Selesnick
This paper addresses the problem of expressing a signal as a sum of frequency components (sinusoids) wherein each sinusoid may exhibit abrupt changes in its amplitude and/or phase.…
Stochastic Pooling for Regularization of Deep Convolutional Neural Networks
Matthew D. Zeiler, Rob Fergus
We introduce a simple and effective method for regularizing large convolutional neural networks. We replace the conventional deterministic pooling operations with a stochastic proc…
Discriminative Recurrent Sparse Auto-Encoders
Jason Tyler Rolfe, Yann LeCun
We present the discriminative recurrent sparse auto-encoder model, comprising a recurrent encoder of rectified linear units, unrolled for a fixed number of iterations, and connecte…
Adaptive learning rates and parallelization for stochastic, sparse, non-smooth gradients
Tom Schaul, Yann LeCun
Recent work has established an empirically successful framework for adapting learning rates for stochastic gradient descent (SGD). This effectively removes all needs for tuning, wh…