
Accounting for Variance in Machine Learning Benchmarks
Strong empirical evidence that one machinelearning algorithm A outperfo...
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Fast Approximate Natural Gradient Descent in a Kroneckerfactored Eigenbasis
Optimization algorithms that leverage gradient covariance information, s...
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Exact gradient updates in time independent of output size for the spherical loss family
An important class of problems involves training deep neural networks wi...
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Theano: A Python framework for fast computation of mathematical expressions
Theano is a Python library that allows to define, optimize, and evaluate...
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Dropout as data augmentation
Dropout is typically interpreted as bagging a large number of models sha...
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EmoNets: Multimodal deep learning approaches for emotion recognition in video
The task of the emotion recognition in the wild (EmotiW) Challenge is to...
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Efficient Exact Gradient Update for training Deep Networks with Very Large Sparse Targets
An important class of problems involves training deep neural networks wi...
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Xavier Bouthillier
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