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Boltzmann machine
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11	Latent Variable Models for Predicting File Dependencies in Large-Scale Software Development Diane J. Hu1 , Laurens van der Maaten1,2 , Youngmin Cho1 , Lawrence K. Saul1 , Sorin Lerner1 1 Dept. of Computer Science & Engin Add to Reading List Source URL: lvdmaaten.github.io Language: English - Date: 2016-07-16 15:30:43 Software Probability Statistics Archive formats Dimension reduction Principal component analysis Mixture model Apache Subversion Markov chain Restricted Boltzmann machine Version control Tar
12	Deep Learning in Partially-labeled Data Streams Jesse Read Aalto University and HIIT Helsinki, Finland Fernando Perez-Cruz Add to Reading List Source URL: users.ics.aalto.fi Language: English - Date: 2014-12-09 08:08:51 Machine learning Learning Artificial intelligence Artificial neural networks Statistical classification Data mining Deep learning K-nearest neighbors algorithm Multi-label classification Deep belief network Restricted Boltzmann machine Concept drift
13	arXiv:1506.00019v4 [cs.LG] 17 OctA Critical Review of Recurrent Neural Networks for Sequence Learning Zachary C. Lipton Add to Reading List Source URL: arxiv.org Language: English - Date: 2015-10-19 21:37:55 Artificial neural networks Cybernetics Applied mathematics Machine learning Recurrent neural network Deep learning Feedforward neural network Long short-term memory Convolutional neural network Backpropagation Connectionism Restricted Boltzmann machine
14	In: European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Bruges, Belgium, 2010 Exploiting Local Structure in Stacked Boltzmann Machines Hannes Schulz, Andreas M¨ ul Add to Reading List Source URL: amueller.github.io Language: English - Date: 2016-08-04 15:59:56 Artificial neural networks Statistics Probability Statistical models Machine learning Artificial intelligence Computational neuroscience Restricted Boltzmann machine Boltzmann machine Feature learning Deep belief network Convolutional neural network
15	Artificial Neural Networks Martin Anthony Abstract ‘Artificial neural networks’ are machines (or models of computation) based loosely on the ways in which the brain is believed to work. In this chapter, we discuss so Add to Reading List Source URL: www.maths.lse.ac.uk Language: English - Date: 2000-04-03 14:18:14 Artificial neural networks Feedforward neural network Perceptron Boltzmann machine Backpropagation Supervised learning Artificial neuron Restricted Boltzmann machine Deep learning
16	NIPS 2010 Workshop on Deep Learning and Unsupervised Feature Learning, Whistler, Canada, DecemberInvestigating Convergence of Restricted Boltzmann Machine Learning Hannes Schulz Add to Reading List Source URL: amueller.github.io Language: English - Date: 2016-08-04 15:59:56 Artificial neural networks Machine learning Computational neuroscience Estimation theory Statistical theory Restricted Boltzmann machine Deep learning Boltzmann machine Feature learning Deep belief network MNIST database Likelihood function
17	arXiv:1506.00019v4 [cs.LG] 17 OctA Critical Review of Recurrent Neural Networks for Sequence Learning Zachary C. Lipton Add to Reading List Source URL: arxiv.org Language: English - Date: 2015-10-19 21:37:55 Artificial neural networks Cybernetics Applied mathematics Machine learning Recurrent neural network Deep learning Long short-term memory Feedforward neural network Convolutional neural network Backpropagation Connectionism Restricted Boltzmann machine
18	Contents Meeting Keynote: Thermal issues: past and present Prof. Paul Shore, Cranfield – Loxham Precision Ltd, UK Meeting Keynote: The Boltzmann Constant: accurate measurements for the new kelvin Dr Robin Underwood, NP Add to Reading List Source URL: www.euspen.eu Language: English - Date: 2015-07-30 07:18:54 Manufacturing Business Technology Mechanical engineering Precision engineering Compensation Machine tool Metal lathe
19	arXiv:1509.01053v1 [cs.LG] 3 SepTraining a Restricted Boltzmann Machine for classification by labeling model samples Malte Probst, Franz Rothlauf Technical Report Add to Reading List Source URL: arxiv.org Language: English - Date: 2015-09-03 20:36:41
20	arXiv:1402.3337v2 [stat.ML] 10 NovZero-bias autoencoders and the benefits of co-adapting features Roland Memisevic Add to Reading List Source URL: arxiv.org Language: English - Date: 2014-11-11 20:54:00 Artificial neural networks Machine learning Learning Artificial intelligence Unsupervised learning Autoencoder Computational neuroscience Computational statistics Feature learning Rectifier Restricted Boltzmann machine Supervised learning