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Smøla
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#	Item
11	Spectral Methods for the Hierarchical Dirichlet Process Hsiao-Yu Fish Tung, Chao-Yuan Wu, Manzil Zaheer, Alexander J. Smola Machine Learning Department Carnegie Mellon University 5000 Forbes Ave, Pittsburgh, PA 15213 Add to Reading List Source URL: www.andrew.cmu.edu Language: English - Date: 2016-04-25 14:45:05 Algebra Mathematics Linear algebra Differential geometry Multilinear algebra Tensors Binary operations Metric tensor Higher-order singular value decomposition
12	Microsoft PowerPointRecitation 1.pptx Add to Reading List Source URL: alex.smola.org Language: English - Date: 2015-02-24 18:00:08
13	Some Tricks For efficient implementation Logistic Regression • Another popular classification model • Usual setting Add to Reading List Source URL: alex.smola.org Language: English - Date: 2015-02-19 19:00:09
14	SISE 9128: Introduction to Machine Learning Alex Smola, RSISE ANU Problem Sheet — Week 1 The due date for these problems is Friday, October 12 Teaching Period Add to Reading List Source URL: alex.smola.org Language: English - Date: 2013-09-09 02:28:38
15	Gradient Descent Objective Function Some differentiable function f : Rn → R. Gradient Descent Start with some x0, i = 0 and learning rate λ repeat Add to Reading List Source URL: alex.smola.org Language: English - Date: 2013-09-09 02:28:42
16	Bild: PPeter Smola / pixelio.de HINSEHEN UND HANDELN! Diakonische Verantwortung vor Ort TERMIN Add to Reading List Source URL: www.kfd-aachen.de - Date: 2016-03-31 09:05:37
17	kernlab – An S4 Package for Kernel Methods in R Alexandros Karatzoglou Alex Smola Technische Universit¨ Add to Reading List Source URL: mran.revolutionanalytics.com Language: English - Date: 2016-03-29 08:14:54
18	An Introduction to Machine Learning L1: Basics and Probability Theory Alexander J. Smola Statistical Machine Learning Program Canberra, ACT 0200 Australia Add to Reading List Source URL: alex.smola.org Language: English - Date: 2013-09-09 02:27:55
19	Prior Probability Idea 1 Quite often we have a rough idea of what function we can expect beforehand. • We observe similar functions in practice. • We think that e.g. smooth functions should be more likely. • We wou Add to Reading List Source URL: alex.smola.org Language: English - Date: 2013-09-09 02:28:50
20	Gradient Descent in Feature Space Linear Functions in Feature Space f (x) = hw, Φ(x)i Empirical Risk Functional m Add to Reading List Source URL: alex.smola.org Language: English - Date: 2013-09-09 02:28:42