NIPS 2014 5267 on the computational efficiency of training neural networks pdf

NIPS
2014 5267 on the computational efficiency of training neural networks pdf

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Total Files	1237
Hash	96E2DAD913038AADAE4BE8023F0115DE30A5595F

/2014/5267-on-the-computational-efficiency-of-training-neural-networks.pdf	377.6 KB
/2014/5422-on-the-number-of-linear-regions-of-deep-neural-networks.pdf	765.6 KB
/2014/5265-fast-sampling-based-inference-in-balanced-neuronal-networks.pdf	849.1 KB
/2013/5020-on-the-representational-efficiency-of-restricted-boltzmann-machines.pdf	424.6 KB
/2014/5275-global-belief-recursive-neural-networks.pdf	337.6 KB
/2014/5346-sequence-to-sequence-learning-with-neural-networks.pdf	143.5 KB
/2014/5347-how-transferable-are-features-in-deep-neural-networks.pdf	437.3 KB
/2013/5032-adaptive-dropout-for-training-deep-neural-networks.pdf	397.4 KB
/2014/5250-a-representation-theory-for-ranking-functions.pdf	249.7 KB
/2014/5488-on-the-information-theoretic-limits-of-learning-ising-models.pdf	1.8 MB
/2013/5166-training-and-analysing-deep-recurrent-neural-networks.pdf	341.2 KB
/2014/5348-convolutional-kernel-networks.pdf	224.3 KB
/2013/5026-learning-stochastic-feedforward-neural-networks.pdf	3.1 MB
/2012/4814-learning-visual-motion-in-recurrent-neural-networks.pdf	1.2 MB
/2014/5404-on-the-relations-of-lfps-neural-spike-trains.pdf	534.0 KB
Showing first 15 files of 1237 total files