Journal of Machine Learning Research1958 Submitted 11/13; Published 6/14 Dropout: A Simple Way to Prevent Neural Networks from Overfitting

Source URL: www.cs.toronto.edu

• Artificial neural networks
• Artificial intelligence
• Machine learning
• Learning
• Computational neuroscience
• Computer vision
• Convolutional neural network
• Computational statistics
• Deep learning
• Dropout
• Backpropagation
• Autoencoder

REGULARIZATION OF CONTEXT-DEPENDENT DEEP NEURAL NETWORKS WITH CONTEXT-INDEPENDENT MULTI-TASK TRAINING Peter Bell and Steve Renals Centre for Speech Technology Research, University of Edinburgh, Edinburgh EH8 9AB, UK ABST

Source URL: www.cstr.ed.ac.uk

• Artificial neural networks
• Machine learning
• Artificial intelligence
• Applied mathematics
• Speech recognition
• Boltzmann machine
• Recurrent neural network
• Multi-task learning
• Deep belief network
• Backpropagation
• Acoustic model
• Language model

Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation Kyunghyun Cho Bart van Merri¨enboer Caglar Gulcehre Universit´e de Montr´eal

Source URL: arxiv.org

• Artificial neural networks
• Artificial intelligence
• Machine learning
• Applied mathematics
• Deep learning
• Recurrent neural network
• Recursive neural network
• Feature learning
• Word embedding
• Statistical machine translation
• Language model
• Autoencoder

Journal of Machine Learning Research660 Submitted 8/09; Published 2/10 Why Does Unsupervised Pre-training Help Deep Learning? Dumitru Erhan∗

Source URL: jmlr.org

Chris Olah "I want to understand things clearly and explain them well." Work Experience May - Sep., 2015

Source URL: colah.github.io

• Computational neuroscience
• DIY culture
• Artificial neural networks
• 3D printing
• Deep learning
• Convolutional neural network
• OpenSCAD
• 3D modeling
• RepRap project

From Image-level to Pixel-level Labeling with Convolutional Networks Pedro O. Pinheiro1,2 Ronan Collobert1,3,† 1 Idiap Research Institute, Martigny, Switzerland 2

Source URL: ronan.collobert.com

• Artificial intelligence
• Computer vision
• Vision
• Image processing
• Image segmentation
• Convolutional neural network
• ImageNet
• Conference on Computer Vision and Pattern Recognition
• Mixture model
• Deep learning

arXiv:1406.1833v2 [cs.NE] 10 JunUnsupervised Feature Learning through Divergent Discriminative Feature Accumulation Paul A. Szerlip, Gregory Morse, Justin K. Pugh, and Kenneth O. Stanley Department EECS (Computer

Source URL: eplex.cs.ucf.edu

• Artificial neural networks
• Artificial intelligence
• Machine learning
• Learning
• Applied mathematics
• Evolutionary algorithms
• Computational neuroscience
• Evolutionary computation
• Neuroevolution
• Deep learning
• HyperNEAT
• Feature learning

arXiv:1502.04623v2 [cs.CV] 20 MayDRAW: A Recurrent Neural Network For Image Generation Karol Gregor Ivo Danihelka

Source URL: arxiv.org

• Artificial neural networks
• Artificial intelligence
• Computational neuroscience
• Cybernetics
• Applied mathematics
• Computational statistics
• Deep learning
• Machine learning
• Convolutional neural network
• Feature learning
• Recurrent neural network
• MNIST database

Deep Convex Network: Architectures and Parallelizable Learning Li Deng and Dong Yu Microsoft Research, Redmond, WA , Abstract

Source URL: snowbird.djvuzone.org

Karl Moritz Hermann Education 2014–2014 Postdoctoral Researcher, Department of Computer Science, University of Oxford. Research on Semantic Parsing with Deep Learning.

Source URL: www.karlmoritz.com