'Noisy training data' presentation slideshows

Machine Learning CS 165B Spring 2012

Machine Learning CS 165B Spring 2012. Course outline. Introduction (Ch. 1) Concept learning (Ch. 2) Decision trees (Ch. 3) Ensemble learning Neural Networks (Ch. 4) Support Vector Machines Bayesian Learning (Ch. 6) Bayesian Networks Clustering Computational l earning theory.

810 views • 71 slides

Semi-Supervised Cause Identification from Aviation Safety Reports

Isaac Persing and Vincent Ng. Semi-Supervised Cause Identification from Aviation Safety Reports. The Aviation Safety Reporting System (ASRS). Established in 1967. ASRS collects aviation safety incident reports submitted by aviation personnel.

522 views • 35 slides

Sudheendra Vijayanarasimhan Kristen Grauman Dept. of Computer Sciences

Keywords to Visual Categories: Multiple-Instance Learning for Weakly Supervised Object Categorization. Sudheendra Vijayanarasimhan Kristen Grauman Dept. of Computer Sciences University of Texas at Austin. Learning about images from keyword-based search.

470 views • 32 slides

Lecture 2: Basics and definitions

Lecture 2: Basics and definitions. Networks as Data Models. Last lecture: an artificial neuron. Bias: input = 1. x 0 = 1. b 1. w 11. x 1. y 1. w 12. x 2. w 1m. y i. x m. Thus the artificial neuron is defined by the components: A set of inputs , x i .

285 views • 28 slides

K-Nearest Neighbor

403 views • 20 slides

Adaptive Goal Recognition

243 views • 15 slides

Text segmentation in Informedia

Text segmentation in Informedia. The Problem. Use closed-captioning cues to segment the text stream into coherent regions (stories). Training data is provided by news provider with paragraph separators (>>>) denoting the boundary between stories.

157 views • 7 slides