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List of results
- 10-601 PAC + (20:46:42, 6 January 2016)
- 10-601 Clustering + (20:49:38, 6 January 2016)
- 10-601 SSL + (20:51:01, 6 January 2016)
- 10-601 Decision Trees + (20:58:44, 6 January 2016)
- Machine Learning 10-601 in Fall 2013 + (21:24:40, 6 January 2016)
- 10-601B Decision Trees + (14:17:56, 12 January 2016)
- 10-601B Boosting and Other Ensembles + (14:18:39, 12 January 2016)
- 10-601B Theory 1 + (14:19:07, 12 January 2016)
- 10-601B Theory 2 + (14:19:40, 12 January 2016)
- Draft schedule for 10-601B in Spring 2016 + (14:21:55, 12 January 2016)
- File:Spring16 10601 HW1.pdf + (03:01:34, 15 January 2016)
- File:Homework1.pdf + (14:02:15, 15 January 2016)
- 10-601 Introduction to Probability + (21:38:09, 15 January 2016)
- 10-601 Course Overview + (18:06:18, 19 January 2016)
- File:10601b-s16-homework2.pdf + (14:44:47, 20 January 2016)
- 10-601 Naive Bayes + (15:03:09, 20 January 2016)
- File:Homework1 solution.pdf + (20:07:08, 26 January 2016)
- File:HW1 solutions 10601 2015 spring.pdf + (20:11:53, 26 January 2016)
- 10-601 Linear Regression + (15:11:37, 27 January 2016)
- File:Perceptron-svm 02 01.pptx + (23:22:54, 1 February 2016)
- File:Perceptron-svm 02 01.pdf + (23:24:41, 1 February 2016)
- File:Margins-kernels-02-03.pdf + (02:42:45, 4 February 2016)
- 10-601B Kernels + (02:44:25, 4 February 2016)
- File:Kernelized-svms.pdf + (03:04:30, 9 February 2016)
- File:Kernelized-svms.pptx + (03:05:57, 9 February 2016)
- 10-601B Neural networks and Backprop + (03:06:37, 9 February 2016)
- File:Intro-anns.pdf + (03:26:26, 9 February 2016)
- File:Intro-anns.pptx + (03:31:28, 9 February 2016)
- 10-601B Kernelized SVMs + (03:34:58, 9 February 2016)
- 10-601B Perceptrons and Large Margin + (03:36:30, 9 February 2016)
- File:10601-homework-3.pdf + (21:53:15, 9 February 2016)
- File:Anns-02-10.pptx + (05:22:03, 11 February 2016)
- File:Anns-02-10.pdf + (05:22:33, 11 February 2016)
- 10-601B Intro to Neural Networks + (05:25:02, 11 February 2016)
- 10-601B Neural Networks + (05:25:15, 11 February 2016)
- File:Boosting-2016.pptx + (15:26:56, 16 February 2016)
- 10-601B AdaBoost + (16:51:05, 16 February 2016)
- File:Boosting-2016.pdf + (22:54:50, 16 February 2016)
- File:10601-Homework-4.pdf + (17:00:01, 17 February 2016)
- 10-601 Logistic Regression + (06:37:05, 18 February 2016)
- File:Hw2 solutions.pdf + (17:06:15, 21 February 2016)
- File:Sample-complexity1.pdf + (01:45:24, 22 February 2016)
- File:Sample-complexity1.pptx + (01:45:53, 22 February 2016)
- 10-601B Generalization and Overfitting: Sample Complexity Results for Supervised Classification + (01:46:05, 22 February 2016)
- File:Sample-complexity2-2016.pdf + (14:52:52, 23 February 2016)
- File:Sample-complexity2-2016.pptx + (14:53:19, 23 February 2016)
- 10-601B Generalization and Overfitting: Sample Complexity Results for Supervised Classification 2 + (14:53:30, 23 February 2016)
- File:Homework3 solution.pdf + (14:51:21, 24 February 2016)
- File:Sample-complexity3-post.pdf + (01:34:24, 27 February 2016)
- 10-601B Model Selection + (01:53:18, 27 February 2016)
- File:Clustering.pdf + (01:43:15, 3 March 2016)