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Structured learning
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#	Item
141	Topics in Structured Prediction: Problems and Approaches DRAFT Ankan Saha June 9, 2010 Add to Reading List Source URL: people.cs.uchicago.edu Language: English - Date: 2010-06-09 21:19:59 Supervised learning Structured prediction Structured learning Support vector machine Empirical risk minimization Regression analysis Natural language processing Algorithm Pattern recognition Statistics Machine learning Artificial intelligence
142	High Order Regularization for Semi-Supervised Learning of Structured Output Problems Yujia Li1 Richard Zemel1,2 1 Department of Computer Science, University of Toronto, Toronto, ON, Canada Add to Reading List Source URL: www.cs.toronto.edu Language: English - Date: 2014-05-13 01:07:16 Statistics Semi-supervised learning Supervised learning Segmentation Transduction Support vector machine Graph Co-training Regularization Machine learning Artificial intelligence Learning
143	What to expect What will my course be like? The University of Worcester emphasises an independent approach to learning in a supportive environment. Your time may be considerably less structured than at school or college Add to Reading List Source URL: www.worc.ac.uk Language: English - Date: 2015-05-27 17:31:48 Standards-based education Teaching Tutor Homework Education Learning Education reform
144	Structured Generative Models of Natural Source Code Chris J. Maddison† University of Toronto CMADDIS @ CS . TORONTO . EDU Add to Reading List Source URL: www.cs.toronto.edu Language: English - Date: 2014-06-20 04:13:18 Graphical models Bayesian statistics Machine learning Tree traversal Generative model Bayesian network Latent variable Hidden Markov model N-gram Statistics Statistical models Probability
145	e-Modules If a learner needs to work on a specific skill rather than taking an entire course, teachers should assign an e-Module. An e-Module is essentially a lesson plan -- a structured set of extralearning activitie Add to Reading List Source URL: www.extralearning.org Language: English - Date: 2008-12-28 22:59:00 Pedagogy E-learning 24 Game Practice Delta Education Learning Distance education
146	Tell Me What You See and I will Show You Where It Is Jia Xu1 Alexander G. Schwing2 Raquel Urtasun2,3 1 University of Wisconsin-Madison 2 University of Toronto 3 TTI Chicago Add to Reading List Source URL: www.cs.toronto.edu Language: English - Date: 2014-04-21 14:33:16 Theoretical computer science Graphical models Categorical data Artificial intelligence Structured prediction Conditional random field Expectation–maximization algorithm Market segmentation Probabilistic latent semantic analysis Statistics Mathematics Machine learning
147	Journal of Artificial Intelligence Research407 Submitted 10/13; published 6/14 HC-Search: A Learning Framework for Search-based Structured Prediction Add to Reading List Source URL: jair.org Language: English - Date: 2014-06-19 15:15:45 Heuristic Function Mathematical optimization Structured SVM Algorithm Mathematics Heuristic function Heuristics
148	Mach Learn manuscript No. (will be inserted by the editor) Efficient Max-Margin Multi-Label Classification with Applications to Zero-Shot Learning Bharath Hariharan · S. V. N. Vishwanathan · Add to Reading List Source URL: www.stat.purdue.edu Language: English - Date: 2011-09-02 09:44:19 Support vector machine Multi-label classification Supervised learning Multiclass classification Regression analysis Feature selection Classifier chains Structured SVM Statistics Machine learning Statistical classification
149	Re-learning labeled categories reveals structured representations Andrew T. Hendrickson; George Kachergis; Caitlin M. Fausey; Robert L. Goldstone ({athendri, gkacherg, cfausey, rgoldsto} @indiana.edu) Department of Psych Add to Reading List Source URL: www.indiana.edu Language: English - Date: 2012-08-11 04:25:20 Educational psychology Machine learning Learning theory Learning Concept learning Perceptual learning Categorization E-learning Second-language acquisition Education Knowledge Cognition
150	Common Criteria Framework for the Vetting of Instructional Materials Published by the National Association of State Textbook Administrators (NASTA) Content Content is structured to ensure all students meet grade‐specif Add to Reading List Source URL: simra.us Language: English - Date: 2012-07-05 09:46:01 Teaching Educational technology Learning Differentiated instruction Instructional design English-language learner WestEd Formative assessment Education Educational psychology Pedagogy

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