'Task learning' presentation slideshows

Human Factors in VR

Electrical and Computer Engineering Dept. Human Factors in VR. User (programmer, trainee, etc.). System architecture. Human Performance Efficiency. Health and Safety. Societal Implications. Human factors in VR. (Stanney et al., 1998).

1.64k views • 95 slides

476 Midterm Results

# of students. Score. 476 Midterm Results. Midterm average: 75.6. Electrical and Computer Engineering Dept. Human Factors in VR. User (programmer, trainee, etc.). System architecture. Human Performance Efficiency. Health and Safety. Societal

1.11k views • 95 slides

Situation decomposition method extracts partial data which contains some rules.

Situation decomposition method extracts partial data which contains some rules. Hiroshi Yamakawa (FUJITSU LABORATORIES LTD.). Abstract.

496 views • 40 slides

Learning to Interpret Natural Language Instructions

Learning to Interpret Natural Language Instructions. Monica Babe?-Vroman + , James MacGlashan * , Ruoyuan Gao + , Kevin Winner * Richard Adjogah * , Marie desJardins * , Michael Littman + and Smaranda Muresan ++ *Department of Computer Science and Electrical Engineering

486 views • 37 slides

Unsupervised Learning of Compositional Sparse Code for Natural Image Representation

Unsupervised Learning of Compositional Sparse Code for Natural Image Representation Ying Nian Wu UCLA Department of Statistics October 5, 2012, MURI Meeting Based on joint work with Yi Hong, Zhangzhang Si, Wenze Hu , Song-Chun Zhu. Sparse Representation.

528 views • 36 slides

Building and evaluating models of human-level intelligence Josh Tenenbaum MIT

Building and evaluating models of human-level intelligence Josh Tenenbaum MIT Department of Brain and Cognitive Sciences Computer Science and AI Lab (CSAIL). The big problem of intelligence.

429 views • 28 slides

Multi-Task Learning for Boosting with Application to Web Search Ranking Olivier Chapelle et al.

Multi-Task Learning for Boosting with Application to Web Search Ranking Olivier Chapelle et al. Presenter: Wei Cheng. Outline. Motivation Backgrounds Algorithm From svm to boosting using L1 regularization ? -boosting for optimization Overall algorithm Evaluation

347 views • 24 slides

Work Group on Student-Centered Learning in High School October 22, 2013 2:00-3:30pm

Work Group on Student-Centered Learning in High School October 22, 2013 2:00-3:30pm Superintendent's Conference Room 960 Main Street, 8 th Fl. General Updates. New Member Introductions Community of Practice session/Virtual Meetings Professional Learning Communities Survey.

300 views • 20 slides

Learning From Demonstration Atkeson and Schaal

Learning From Demonstration Atkeson and Schaal. Dang, RLAB Feb 28 th , 2007. Goal. Robot Learning from Demonstration Small number of human demonstrations Task level learning (learn intent, not just mimicry) Explore Parametric vs. nonparametric learning role of a priori knowledge.

252 views • 16 slides

Learning From Demonstration Atkeson and Schaal

Learning From Demonstration Atkeson and Schaal. Dang, RLAB Feb 28 th , 2007. Goal. Robot Learning from Demonstration Small number of human demonstrations Task level learning (learn intent, not just mimicry) Explore Parametric vs. nonparametric learning role of a priori knowledge.

165 views • 16 slides

Welcome ! Today is School Assembly Day!

619 views • 10 slides

Task Learning in COLLAGEN

Task Learning in COLLAGEN. The COLLAGEN Architecture; Task Learning from Demonstrations Work @: Mitshubishi Electric Research Labs Andrew Garland, Neal Lesh, Kathy Ryall, Charles Rich, Candy Sidner Carnegie Mellon University, 2001. Outline . The COLLAGEN Architecture:

240 views • 10 slides

EVALUATION PROCESS

111 views • 5 slides