Different FeaturesDifferent Features

Glasses vs. No GlassesGlasses vs. No Glasses

Beard vs. No BeardBeard vs. No Beard

Beard DistinctionBeard Distinction

Ghodsi et, al 2007

Glasses DistinctionGlasses Distinction

Ghodsi et, al 2007

Multiple-Attribute MetricMultiple-Attribute Metric

Ghodsi et, al 2007

Embedding of sparse music Embedding of sparse music similarity graphsimilarity graph

Platt, 2004

Reinforcement learningReinforcement learning

Mahadevan and Maggioini, 2005

Semi-supervised learningSemi-supervised learning

Use graph-based discretization of manifold to infer missing labels.

Build classifiers from bottom eigenvectors of graph Laplacian.

Belkin & Niyogi, 2004; Zien et al, Eds., 2005

correspondencescorrespondences

http://www.bushorchimp.com

Learning correspondencesLearning correspondences

How can we learn manifold structure that is shared across multiple data sets?

c et al, 2003, 2005

Mapping and robot localizationMapping and robot localization

Bowling, Ghodsi, Wilkinson 2005

Ham, Lin, D.D. 2005

ClassificationClassification

ClassificationClassification

DataData

Features (X)

(Green, 6, 4, 4.5)

(Green, 7, 4.5, 5)

(Red, 6, 3, 3.5)

(Red, 4.5, 4, 4.5)

(Yellow, 1.5, 8, 2)

(Yellow, 1.5, 7, 2.5)

Data RepresentationData Representation

Data RepresentationData Representation

11 11 11 11 11

11 00 11 00 11

11 11 11 11 11

11 0.50.5 0.50.5 0.50.5 11

11 11 11 11 11

Data RepresentationData Representation

Features and labelsFeatures and labels

(Green, 6, 4, 4.5)

(Green, 7, 4.5, 5)

(Red, 6, 3, 3.5)

(Red, 4.5, 4, 4.5)

(Yellow, 1.5, 8, 2)

(Yellow, 1.5, 7, 2.5)

Green Pepper

Green Pepper

Red Pepper

Red Pepper

Hot Pepper

Hot Pepper

Features and labelsFeatures and labels

Objects Features (X) Labels (Y)

Classification (New point)Classification (New point)

(Red, 7, 4, 4.5)h(Red, 7, 4, 4.5)

?

Classification (New point)Classification (New point)

(Red, 5, 3, 4.5)h(Red, 5, 3, 4.5)

?

Digit RecognitionDigit Recognition

ClassificationClassification

ClassificationClassification

ClassificationClassification

ClassificationClassification

Computer VisionComputer Vision

N. Jojic and B.J. Frey, “ Learning flexible sprites in video layers”, CVPR 2001, (Video)

ReadingReading

• Journals: Neural Computation, JMLR, ML, IEEE PAMI• Conferences: NIPS, UAI, ICML, AI-STATS, IJCAI,

IJCNN• Vision: CVPR, ECCV, SIGGRAPH• Speech: EuroSpeech, ICSLP, ICASSP• Online: citesser, google• Books:

– Elements of Statistical Learning, Hastie, Tibshirani, Friedman– Learning from Data, Cherkassky, Mulier– Pattern classification, Duda, Hart, Stork– Neural Networks for pattern Recognition, Bishop– Pattern recognition and machine learning, Bishop