Slide 1Mining the MACHO dataset Markus Hegland, Mathematical Sciences Institute, ANU Margaret Kahn, ANU Supercomputer Facility Slide 2 The MACHO project Woods data set Data…
Slide 1 Bootstrapping Goals: –Utilize a minimal amount of (initial) supervision –Obtain learning from many unlabeled examples (vs. selective sampling) General scheme:…
Slide 1 AdaBoost Robert E. Schapire (Princeton University) Yoav Freund (University of California at San Diego) Presented by Zhi-Hua Zhou (Nanjing University) Slide 2 Ensemble…
Slide 1 131 Feed-Forward Artificial Neural Networks MEDINFO 2004, T02: Machine Learning Methods for Decision Support and Discovery Constantin F. Aliferis & Ioannis Tsamardinos…
Stochastic Subgradient Approach for Solving Linear Support Vector Machines Jan Rupnik Jozef Stefan Institute Outline Introduction Support Vector Machines Stochastic Subgradient…
Published as a conference paper at ICLR 2015 EXPLAINING AND HARNESSING ADVERSARIAL EXAMPLES Ian J. Goodfellow, Jonathon Shlens & Christian Szegedy Google Inc., Mountain…
Instance Based Learning CS 478 - Learning Rules 1 Learning Sets of Rules 1 CS 478 - Learning Rules 2 Learning Rules If (Color = Red) and (Shape = round) then Class is A If…
An Ad Omnia Approach to Defining and Achieving Private Data Analysis Boosting and Differential Privacy Cynthia Dwork, Microsoft Research TexPoint fonts used in EMF. Read…