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221	Artificial Neural Networks Examination, June 2005 Instructions There are SIXTY questions. (The pass mark is 30 out of 60). For each question, please select a maximum of ONE of the given answers (either A, B, C, D or E). Add to Reading List Source URL: aass.oru.se Language: English - Date: 2005-06-05 12:55:59 Artificial intelligence Perceptron Artificial neural network Feedforward neural network Multilayer perceptron Backpropagation Generalization error Statistical classification ADALINE Neural networks Cybernetics Science
222	Artificial Neural Networks Examination, March 2005 Instructions There are SIXTY questions. (The pass mark is 30 out of 60.) For each question, please select a maximum of ONE of the given answers (either A, B, C, D or E). Add to Reading List Source URL: aass.oru.se Language: English - Date: 2005-03-21 10:47:39 Learning Artificial neuron Artificial neural network Perceptron Generalization error Statistical classification Supervised learning Multilayer perceptron Activation function Neural networks Cybernetics Artificial intelligence
223	MITSUBISHI ELECTRIC RESEARCH LABORATORIES http://www.merl.com Robust 1-Bit Compressive Sensing via Gradient Support Pursuit Add to Reading List Source URL: www.merl.com Language: English - Date: 2013-07-10 09:09:12 Convex optimization Operations research Logarithms Linear programming Perceptron Mathematical optimization Mathematics Mathematical analysis
224	Artificial Neural Networks Examination, March 2003 Instructions There are SIXTY questions (worth up to 60 marks). The exam mark (maximum 60) will be added to the mark obtained in the laborations (maximum 5). The total pa Add to Reading List Source URL: aass.oru.se Language: English - Date: 2004-06-07 09:38:12 Neuroscience Perceptron Artificial neural network Multilayer perceptron Backpropagation Pattern recognition Statistical classification Winner-take-all Activation function Neural networks Cybernetics Science
225	egu_logo_without_circle_grey Add to Reading List Source URL: www.the-cryosphere.net Language: English - Date: 2014-12-04 08:12:30 Machine learning Computational neuroscience Computational statistics Cryosphere Artificial neural network Statistical classification Regression analysis Snow Perceptron Statistics Neural networks Econometrics
226	Artificial Neural Networks Examination, March 2004 Instructions There are SIXTY questions (worth up to 60 marks). The exam mark (maximum 60) will be added to the mark obtained in the laborations (maximum 5). The total pa Add to Reading List Source URL: aass.oru.se Language: English - Date: 2004-06-07 09:38:12 Artificial intelligence Feedforward neural network Perceptron Artificial neuron Artificial neural network Multilayer perceptron Backpropagation Generalization error ADALINE Neural networks Cybernetics Science
227	Online Large-Margin Training of Dependency Parsers Ryan McDonald Koby Crammer Fernando Pereira Department of Computer and Information Science University of Pennsylvania Add to Reading List Source URL: www.aclweb.org Language: English - Date: 2010-06-15 02:43:30 Computational linguistics Corpus linguistics Formal languages Parsing Treebank Chart parser Conditional random field Context-free grammar Perceptron Linguistics Natural language processing Compiler construction
228	Neural Decision Forests for Semantic Image Labelling Samuel Rota Bul`o Fondazione Bruno Kessler Trento, Italy Peter Kontschieder Add to Reading List Source URL: www.dsi.unive.it Language: English - Date: 2014-04-15 04:23:50 Perceptron Multilayer perceptron Maximum likelihood Artificial neuron Random forest Activation function Decision tree learning Backpropagation Artificial neural network Neural networks Machine learning Statistics
229	Artificial Neural Networks Examination, June 2004 Instructions There are SIXTY questions (worth up to 60 marks). The exam mark (maximum 60) will be added to the mark obtained in the laborations (maximum 5). The total pas Add to Reading List Source URL: aass.oru.se Language: English - Date: 2004-09-08 10:30:53 Neuroscience Perceptron Feedforward neural network Artificial neural network Multilayer perceptron ADALINE Activation function Statistical classification Supervised learning Neural networks Cybernetics Science
230	A Scalable Probabilistic Classifier for Language Modeling Joel Lang Institute for Language, Cognition and Computation School of Informatics, University of Edinburgh 10 Crichton Street, Edinburgh EH8 9AB, UK Add to Reading List Source URL: www.aclweb.org Language: English - Date: 2011-05-20 16:12:48 Bayesian statistics Machine learning N-gram Maximum likelihood Hidden Markov model Principle of maximum entropy Training set Perceptron Entropy Statistics Probability and statistics Statistical theory

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