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Network intelligence
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#	Item
111	Univ. of Pittsburgh Conditional Random Fields Add to Reading List Source URL: people.cs.pitt.edu Language: English - Date: 2014-10-25 10:56:22 Graphical models Machine learning Statistical models Learning Artificial intelligence Statistics Conditional random field Generative model Markov random field Discriminative model Bayesian network Factor graph
112	arXiv:1602.03935v2 [cs.CV] 21 JunFace Attribute Prediction Using Off-the-Shelf CNN Features Yang Zhong Josephine Sullivan Add to Reading List Source URL: arxiv.org Language: English - Date: 2016-06-21 21:29:10 Computational neuroscience Artificial neural networks Applied mathematics Cybernetics Neuroscience Computer vision Convolutional neural network Deep learning Receptive field Artificial intelligence Object Process Methodology
113	Generating Natural Language Aggregations Using a Propositional Representation of Sets Susan Haller1 , Barbara Di Eugenio2 , and Michael Trolio2 1 Computer Science Department University of Wisconsin–Parkside Add to Reading List Source URL: nlp.cs.uic.edu Language: English - Date: 2013-03-02 15:00:28 Computing Artificial intelligence Cognitive architecture SNePS Software Aggregation Node Rope Semantic network
114	A Machine Learning Approach for Filtering Monte Carlo Noise Add to Reading List Source URL: cvc.ucsb.edu Language: English - Date: 2015-05-13 18:18:10 Artificial intelligence Statistics Computational neuroscience Machine learning Artificial neural networks Computational statistics Mathematical psychology Noise reduction Backpropagation Bilateral filter Mixture model Convolutional neural network
115	The Pulse of Allegheny County and Pittsburgh FINAL RESEARCH REPORT José M F Moura (PI), Evgeny Toropov, Joya Deri, Satwik Kottur Add to Reading List Source URL: utc.ices.cmu.edu Language: English - Date: 2016-04-20 09:36:36 Computational neuroscience Artificial intelligence Applied mathematics Cybernetics Computer vision Convolutional neural network Artificial neural network
116	CS224d: Deep NLP Lecture 9: Wrap up: LSTMs and Recursive Neural Networks Richard Socher Add to Reading List Source URL: cs224d.stanford.edu Language: English - Date: 2016-04-30 00:52:50 Artificial neural networks Neuroscience Computational neuroscience Applied mathematics Cybernetics Artificial intelligence Recurrent neural network Computational statistics Long short-term memory Neural networks Biological neural network Backpropagation
117	Knowledge Guided Disambiguation for Scene Recognition with Multi-Resolution CNNs Limin Wang, Sheng Guo, Weilin Huang, Yu Qiao Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences Multi-Resolution CNNs Add to Reading List Source URL: image-net.org Language: English - Date: 2015-12-21 11:37:40 Computational neuroscience Applied mathematics Cybernetics Cognitive science Convolutional neural network Artificial intelligence ImageNet Artificial neural network Word-sense disambiguation Corr Knowledge
118	Probabilistic Inference and Accuracy Guarantees Stefano Ermon CS Department, Stanford Add to Reading List Source URL: intelligence.org Language: English - Date: 2016-06-01 20:00:33 Theoretical computer science PP Quantum complexity theory Boolean algebra Mathematics Numerical software Logic in computer science Bayesian network PROPT
119	CS 224D: Deep Learning for NLP1 1 Lecture Notes: Part IV2 Add to Reading List Source URL: cs224d.stanford.edu Language: English - Date: 2016-05-16 12:49:36 Artificial neural networks Applied mathematics Machine learning Cybernetics Recurrent neural network Deep learning Long short-term memory Vanishing gradient problem Backpropagation Language model Artificial intelligence Types of artificial neural networks
120	Around Inverse Reinforcement Learning and Score-based Classification Matthieu Geist IMS - MaLIS Research Group (Supélec) Metz, France Add to Reading List Source URL: www.metz.supelec.fr Language: English - Date: 2014-01-18 03:53:53 Machine learning Artificial intelligence Learning Applied mathematics Computational neuroscience Dynamic programming Stochastic control Reinforcement learning Apprenticeship learning Markov decision process Artificial neural network Supervised learning

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