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Computational learning theory
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41	Published as a conference paper at ICLRA DAM : A M ETHOD FOR S TOCHASTIC O PTIMIZATION Diederik P. Kingma* University of Amsterdam Add to Reading List Source URL: arxiv.org Language: English - Date: 2015-07-26 20:01:45 M-estimators Computational statistics Computational neuroscience Estimation theory Stochastic optimization Stochastic gradient descent Deep learning Artificial neural network Convolutional neural network Mathematical optimization Loss function Feature learning
42	In Computational Approaches to Connecting Levels of Analysis in Networked Learning Communities, a Workshop at Learning Analytics and Knowledge 2014, 24-28 March 2014, Indianapolis, IN. Multilevel Analysis of Uptake, Sess Add to Reading List Source URL: www.tappedin.org Language: English - Date: 2014-09-04 15:31:34 Network theory Networks Network analysis Graph theory Social information processing Graph partition Graph Community structure Social network analysis Social network Clustering coefficient Centrality
43	arXiv:1410.7455v8 [cs.NE] 22 Jun 2015 Add to Reading List Source URL: arxiv.org Language: English - Date: 2015-06-23 20:50:51 Stochastic optimization Estimation theory Computational statistics M-estimators Convex optimization Stochastic gradient descent Matrix Fisher information Deep learning Covariance matrix
44	Probabilistic ‘Generalization’ of Functions and Dimension-based Uniform Convergence Results Martin Anthony Department of Mathematics London School of Economics and Political Science Add to Reading List Source URL: www.maths.lse.ac.uk Language: English - Date: 2000-04-03 14:58:43 Computational learning theory Machine learning Probably approximately correct learning Uniform convergence VC dimension Probability distribution Stability Generalization error
45	Microsoft Word - MSc in Applied Statisticsoutline.docx Add to Reading List Source URL: www.stats.ox.ac.uk Language: English - Date: 2016-02-12 07:15:48 Bayesian statistics Statistical inference Statistical models Estimation theory Computational statistics Bayesian network Coalescent theory Bayesian Markov chain Monte Carlo Particle filter Ensemble learning Deep learning
46	PAC Learning and Artificial Neural Networks Martin Anthony and Norman Biggs Department of Mathematics, London School of Economics and Political Science (University of London), Houghton St., London WC2A 2AE, United Kingdo Add to Reading List Source URL: www.maths.lse.ac.uk Language: English - Date: 2000-04-03 14:19:07 Computational learning theory Artificial neural networks Machine learning Computational statistics Learning VC dimension Sample complexity Probably approximately correct learning Backpropagation Perceptron Vladimir Vapnik Radial basis function network
47	Visual Concept Learning: Combining Machine Vision and Bayesian Generalization on Concept Hierarchies Yangqing Jia1 , Joshua Abbott2 , Joseph Austerweil3 , Thomas Griffiths2 , Trevor Darrell1 1 UC Berkeley EECS 2 Dept of Add to Reading List Source URL: cocosci.berkeley.edu Language: English - Date: 2014-02-14 18:19:32 Statistics Artificial intelligence Machine learning Cognition Computational neuroscience Concept learning Learning theory ImageNet Artificial neural network Supervised learning Support vector machine Probability distribution
48	ANNEXURE D: LIST OF REPUTED PUBLICATIONS IN CSE Acronym SIGCOMM SIGMETRICS CCS Add to Reading List Source URL: www.cse.iitd.ernet.in Language: English - Date: 2016-03-26 00:11:24 Theoretical computer science Association for Computing Machinery ACM SIGACT Computer science International Conference on Functional Programming Computational geometry Computational intelligence Computational learning theory International Symposium on Symbolic and Algebraic Computation Algorithmica Draft:Chittoor V. Ramamoorthy Vasant Honavar
49	Appearing in Proceedings of the 17th Annual Conference on Computational Learning Theory, Performance Guarantees for Regularized Maximum Entropy Density Estimation Miroslav Dud´ık1 , Steven J. Phillips2 , and Rob Add to Reading List Source URL: rob.schapire.net Language: English - Date: 2015-07-13 19:42:58
50	Journal of Machine Learning Research2801 Submitted 1/08; Revised 9/08; PublishedRobust Submodular Observation Selection Andreas Krause Add to Reading List Source URL: select.cs.cmu.edu Language: English - Date: 2009-08-13 03:47:05 Computational complexity theory Theory of computation Mathematics Submodular set function Greedy algorithm Algorithm Optimization problem Reduction NP Time complexity