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Deep learning
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#	Item
601	How does Rainforest Explorer link to Lifelong Learning in SOSE? Rainforest Explorer addresses all seven lifelong learner categories. Knowledgeable person with deep understanding: Rainforest Explorer requires students to Add to Reading List Source URL: www.wettropics.gov.au Language: English - Date: 2012-07-14 00:23:34
602	On the importance of initialization and momentum in deep learning Ilya Sutskever1 James Martens George Dahl Geoffrey Hinton Add to Reading List Source URL: www.cs.toronto.edu Language: English - Date: 2013-05-14 14:30:22 Mathematics Mathematical optimization Stochastic gradient descent Convex optimization Gradient descent Backpropagation Perceptron Gradient method Autoencoder Neural networks Numerical analysis Applied mathematics
603	Department of Computer Science On the use of Cortical Principles in Deep Learning Benjamin Pryke __________________________________________ Add to Reading List Source URL: dl.dropboxusercontent.com Language: English Statistics Spiking neural network Backpropagation Feedforward neural network Synaptic weight Autoencoder Artificial neural network Types of artificial neural networks Neural networks Cybernetics Science
604	A Holistic Education for Secondary School Students - LEAPS 2.0 A holistic education provides students with a broad and deep foundation for lifelong learning. This includes learning not just in the academic areas. Equally Add to Reading List Source URL: www.moe.edu.sg Language: English - Date: 2014-02-10 20:45:01 Marine Parade Anglo-Chinese School Tanjong Katong Secondary School Education in Singapore Singapore Co-curricular activity
605	8th ISCA Speech Synthesis Workshop • August 31 – September 2, 2013 • Barcelona, Spain Combining a Vector Space Representation of Linguistic Context with a Deep Neural Network for Text-To-Speech Synthesis Heng Lu, Add to Reading List Source URL: www.cstr.ed.ac.uk Language: English - Date: 2013-10-07 08:11:17 Artificial intelligence Neural networks Machine learning Assistive technology Speech synthesis Speech recognition Supervised learning Hidden Markov model Science Computational linguistics Computational neuroscience
606	CS 224D: Deep Learning for NLP1 1 Lecture Notes: Part I2 Add to Reading List Source URL: cs224d.stanford.edu Language: English - Date: 2015-05-02 14:21:27 Abstract algebra Vector calculus Statistical theory Matrix theory Vector space Maximum likelihood Euclidean vector Matrix Naive Bayes classifier Algebra Mathematics Linear algebra
607	Microsoft PowerPoint - Technology Budget15.pptx Add to Reading List Source URL: www.wi.k12.ny.us Language: English - Date: 2015-03-19 07:31:15 New media Cisco Systems Deep packet inspection Videotelephony Internet access Internet Educational technology Personal digital assistant E-learning Technology Education Digital media
608	Adaptive dropout for training deep neural networks Lei Jimmy Ba Brendan Frey Department of Electrical and Computer Engineering University of Toronto jimmy, Add to Reading List Source URL: papers.nips.cc Language: English - Date: 2014-11-25 16:08:01 Artificial intelligence Computational neuroscience Computational statistics Autoencoder Artificial neural network Supervised learning Unsupervised learning Boltzmann machine Backpropagation Neural networks Machine learning Statistics
609	The Evolution of Religion: How Cognitive By-Products, Adaptive Learning Heuristics, Ritual Displays, and Group Competition Generate Deep Commitments to Prosocial Religions Scott Atran Add to Reading List Source URL: www.littlebang.org Language: English - Date: 2015-01-09 09:34:13 Anthropology of religion Evolutionary psychology Study of religion Joseph Henrich Human evolution Norm Evolutionary origin of religions Counterintuitive Adaptive bias Zoology Megafauna Science
610	Multi-source Deep Learning for Human Pose Estimation Wanli Ouyang Xiao Chu Xiaogang Wang Department of Electronic Engineering, The Chinese University of Hong Kong , Abstract Add to Reading List Source URL: www.ee.cuhk.edu.hk Language: English - Date: 2014-06-20 01:45:24 Learning Mixture model Pose Unsupervised learning Pattern recognition Neural network Boltzmann machine Regularization Machine learning Artificial intelligence Statistics

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