'Loss functions' diaporamas de présentation

Predictive Learning from Data

Predictive Learning from Data. LECTURE SET 4 Statistical Learning Theory (VC-theory). Electrical and Computer Engineering. OUTLINE. Objectives Inductive learning problem setting Keep-It-Direct Principle Statistical Learning Theory Applications Measuring the VC-dimension

1.32k views • 105 slides

Tuyen N. Huynh Adviser: Prof. Raymond J. Mooney

Improving the Accuracy and Scalability of Discriminative Learning Methods for Markov Logic Networks. PhD Defense. May 2 nd , 2011. Tuyen N. Huynh Adviser: Prof. Raymond J. Mooney. Biochemistry. Predicting mutagenicity [ Srinivasan et. al, 1995]. Natural language processing.

765 views • 68 slides

Feedback from last week

Feedback from last week. Too much slides / Too much information in too little time ? AI is a complex topic with different subjects ? Overall lecture is not enough time (1.5h + Practice)

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Matrix Factorization

681 views • 50 slides

Outline

Medical Image Classification with Advanced Markov Random Field/Gibbs Classification A Dissertation Proposal Zhihong Yang May 30,2000 Advisor committee Dr. Ian R. Greenshields Dr. Howard Sholl Dr. Reda Ammar. Outline. Medical image classification and its time-consuming properties

603 views • 46 slides

Machine Learning

700 views • 39 slides

Evaluation of Probability Forecasts

Evaluation of Probability Forecasts. Shulamith T Gross C ity U niversity of N ew Y ork B aruch C ollege Joint work with Tze Leung Lai, David Bo Shen: S tanford U niversity Catherine Huber U niversitee R ene D escartes Rutgers 4.30.2012. Quality of Prediction.

418 views • 32 slides

Online Max-Margin Weight Learning with Markov Logic Networks

Machine Learning Group Department of Computer Science The University of Texas at Austin. Online Max-Margin Weight Learning with Markov Logic Networks. Star AI 2010, July 12, 2010. Tuyen N. Huynh and Raymond J. Mooney. Outline. Motivation Background Markov Logic Networks

466 views • 30 slides

Active Random Fields

Active Random Fields. Adrian Barbu. The MAP Estimation Problem. Estimation problem: Given input data y, solve Example: Image denoising Given noisy image y , find denoised image x Issues Modeling : How to approximate ? Computing : How to find x fast?. Noisy image y.

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Loss Functions for Detecting Outliers in Panel Data

Loss Functions for Detecting Outliers in Panel Data. Charles D. Coleman Thomas Bryan Jason E. Devine U.S. Census Bureau. Prepared for the Spring 2000 meetings of the Federal-State Cooperative Program for Population Estimates, Los Angeles, CA, March, 2000. Panel Data.

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Loss Functions for Detecting Outliers in Panel Data

Loss Functions for Detecting Outliers in Panel Data. Charles D. Coleman Thomas Bryan Jason E. Devine U.S. Census Bureau. Prepared for the Spring 2000 meetings of the Federal-State Cooperative Program for Population Estimates, Los Angeles, CA, March, 2000. Panel Data.

367 views • 27 slides

Data Science for Business: Book Review Tutorial

Data Science for Business: Book Review Tutorial. Dr. Brand Niemann Director and Senior Data Scientist Semantic Community http://semanticommunity.info http://www.meetup.com/Federal-Big-Data-Working-Group/ http://semanticommunity.info/Data_Science/Federal_Big_Data_Working_Group_Meetup

423 views • 20 slides

Jakub Bijak Division of Social Statistics and Centre for Population Change

Dealing with uncertainty in international migration predictions: From probabilistic forecasting to decision analysis. Jakub Bijak Division of Social Statistics and Centre for Population Change University of Southampton.

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Boosting

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A PAC-Bayes Risk Bound for General Loss Functions

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Acquiring traces from random walks

Acquiring traces from random walks. Project final presentation By: Yaniv Sabo Aviad Hasnis Supervisor: Daniel Vainsencher. Project Goal. Creating traces of indoor walks using signals collected by different agents. Possible problem: GPS is not feasible indoors. Possible Solution.

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Origin of Idea on Central Bank Independence

Origin of Idea on Central Bank Independence. Central Bank Independence in Practice. Spirit of Central Bank Independence. Economic and Political Independence of a CB. Theoretical Case for Central Bank Independence. Analysis of inflationary Bias.

787 views • 16 slides

Chapter 2

Chapter 2. Basic Considerations for Successful Forecasting. Six Considerations. Decision Environment - Loss Function Forecast Objective Forecast Statement Forecast Horizon Information Set Complexity of Methodology. Decision Environment.

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A pre-Weekend Talk on Online Learning

A pre-Weekend Talk on Online Learning. TGIF Talk Series Purushottam Kar. Outline. Some Motivating Examples Discovering customer preferences Learning investment profiles Detecting credit card fraud The Formal Online Learning Framework Notion of regret Formalization of motivating examples

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