'Weak hypotheses' presentation slideshows

Supervised and semi-supervised learning for NLP

Supervised and semi-supervised learning for NLP. John Blitzer. ??????? http://research.microsoft.com/asia/group/nlc/. Why should I know about machine learning?. This is an NLP summer school. Why should I care about machine learning?

683 views • 48 slides

FilterBoost: Regression and Classification on Large Datasets

FilterBoost: Regression and Classification on Large Datasets. Joseph K. Bradley 1 and Robert E. Schapire 2 1 Carnegie Mellon University 2 Princeton University. Dataset. Final Hypothesis. Booster. Typical Framework for Boosting. Batch Framework.

341 views • 25 slides

A. Opelt, M. Fussenegger, A. Pinz, P. Auer

A. Opelt, M. Fussenegger, A. Pinz, P. Auer. Weak Hypotheses and Boosting for Generic Object Detection and Recognition. Agenda. The Basic Idea Our Framework for generic Object Recognition ? The techniques used The Learning Model ? Our Model The Weak Hypotheses Finder Experiments

360 views • 23 slides

On-line learning and Boosting

230 views • 22 slides