'Learning problem' diaporamas de présentation

Rebecca Fiebrink Perry Cook, Advisor FPO, 12/13/2010

Real-time Human Interaction with Supervised Learning Algorithms for Music Composition and Performance. Rebecca Fiebrink Perry Cook, Advisor FPO, 12/13/2010. Source: googleisagiantrobot.com. function [ x flag hist dt ] = pagerank(A,optionsu ) [ m n ] = size(A ); if ( m ~= n )

1.18k views • 105 slides

High-Dimensional Statistical Modeling and Analysis Of Custom Integrated Circuits

High-Dimensional Statistical Modeling and Analysis Of Custom Integrated Circuits. Trent McConaghy Co-founder & CSO, Solido Design Automation Custom Integrated Circuits Conference (CICC) San Jose, CA, Sept 2011. How does Google find furry robots?

820 views • 61 slides

821 views • 60 slides

Kshitij Judah EECS, OSU

Developing Learning Systems that Interact and Learn from Human Teachers. Kshitij Judah EECS, OSU. Dissertation Proposal Presentation. Outline. PART I: User-Initiated Learning PART II: RL via Practice and Critique Advice PART III: Proposed future directions for the PhD program

707 views • 59 slides

???? machine learning

???? machine learning. ??? ??????. Textbook. Machine learning ? Tom M. Mitchell ????? http://cit.sjtu.edu.cn/Machinelearning2012 Reference ? Pattern Recognition and Machine Learning, Christopher M. Bishop, 2006. Grading. Homework ---20 ? Project ---20% Exam --- 60 ? ;. Outline.

980 views • 58 slides

Artificial Intelligence

Artificial Intelligence. Learning from observations Chapter 18, AIMA. Two types of learning in AI. Deductive : Deduce rules/facts from already known rules/facts. (We have already dealt with this) Inductive : Learn new rules/facts from a data set D.

644 views • 51 slides

Using Bayesian Networks to Analayze Expression Data

Using Bayesian Networks to Analayze Expression Data. Shelly Bar-Nahor. Today. 1. Introduction to Bayesian Networks. 2. Describe a method for recovering gene interactions from microarray data, using tools for learning Bayesian Networks.

640 views • 49 slides

School-Based Medicaid Programs

School-Based Medicaid Programs. Mississippi Department of Education Lea Ann McElroy, Director Bureau of Health Services Mississippi Division of Medicaid Cindy Thames, Director Bureau of Maternal & Child Heath. Former Surgeon General Dr. Antonio Novello

740 views • 45 slides

Support Vector Machine and String Kernels for Protein Classification

Christina Leslie. Support Vector Machine and String Kernels for Protein Classification. Department of Computer Science Columbia University. Learning Sequence-based Protein Classification. Problem: classification of protein sequence data into families and superfamilies

526 views • 36 slides

Issues in Motor Control

Issues in Motor Control. Serial Order and Timing Problem Degrees of Freedom Problem Perceptual-Motor Integration Problem Learning Problem. (Rosenbaum, 2002). Earlier Ideas Used Response Chaining: Closed (feedback)-Loop Control:. No, because delays too long between movements

691 views • 35 slides

Hidden Markov Models

Hidden Markov Models. So far: considered systems for making a single decision (e.g. discriminant functions or estimation of class-conditional densities.) Now we consider: the problem of sequential decision making Example : Automatic Speech Recognition (ASR).

568 views • 34 slides

CS 440/ECE448 Lecture 20: Bayes Net Inference & Learning

CS 440/ECE448 Lecture 20: Bayes Net Inference & Learning. Slides by Svetlana Lazebnik , 11/2016 Modified by Mark Hasegawa-Johnson, 11/2017. Bayes Network Inference & Learning. Bayes net is a memory-efficient model of dependencies among: Query variables: X

684 views • 31 slides

Anna Ly & Hain -Lee Hsueh

Anna Ly & Hain -Lee Hsueh. About Us. Hain -Lee Hsueh. Anna Ly. Background in HCI, Business & Communication Design from Carnegie Mellon. Formally worked for IBM Strategy. Background in ECE and Software Engineering from Cornell. Formally worked for Oracle Enterprise Applications.

406 views • 28 slides

A Framework for Learning Rules from Multi-Instance Data

393 views • 23 slides

Reinforcement Learning for 3 vs. 2 Keepaway

Reinforcement Learning for 3 vs. 2 Keepaway. P. Stone, R. S. Sutton, and S. Singh Presented by Brian Light. Robotic Soccer. Sequential decision problem Distributed multi-agent domain Real-time Partially observable Noise Large state space. Reinforcement Learning.

342 views • 23 slides

EEL 6586-Automatic Speech Processing Hidden Markov Models for Speech Recognition

EEL 6586-Automatic Speech Processing Hidden Markov Models for Speech Recognition. Savyasachi Singh Computational NeuroEngineering Lab March 19, 2008. Introduction. Model Parameters. Assumptions. Three basic problems. Evaluation Problem. Forward Algorithm. Backward Algorithm.

428 views • 20 slides

Tutorial on Hidden Markov Models

Tutorial on Hidden Markov Models. Overview. Markov chains Mixture Models Hidden Markov Model Definition Three basic problems Issues. Markov chain: an example. Weather model: 3 states {rainy, cloudy, sunny} Problem: Forecast weather state, based on the current weather state.

546 views • 16 slides

Suki Goodman Section of Organisational Psychology School of Management Studies

Suki Goodman Section of Organisational Psychology School of Management Studies . DFAQ Simple interventions for complex problems. Outline . Context What was the teaching or learning problem? How did you use a teaching and learning technology as part of a solution? How well did this work?

252 views • 16 slides

Goal Setting and Self- regulation

Goal Setting and Self- regulation. Susan Helldorfer Leonardtown Elementary SMCPS. Can a student with poor work habits and study habits set personal achievement goals and be successful? Under what conditions is this most likely to happen?.

756 views • 15 slides

Lecture 33 of 42 Fall, 2005 Relational Graphical Models

Lecture 33 of 42 Fall, 2005 Relational Graphical Models. William H. Hsu Friday, 11 November 2005 CIS 490: Introduction to Artificial Intelligence CIS 730: Principles of Artificial Intelligence Kansas State University http://www.kddresearch.org/Courses/Fall-2005/CIS730. Lecture Outline.

156 views • 4 slides