Rapport final du projet jeunes chercheurs du gdr isis bisou (BIStochastic Optimization and application to mUltiple kernel learning) Sandrine Anthoine1 , Liva Ralaivola2 , Marie Szafranski3 , Matthieu Kowalski4 , Thomas

Source URL: www.gdr-isis.fr

Int J Comput Vis:115–132 DOIs11263z Iterative Category Discovery via Multiple Kernel Metric Learning Carolina Galleguillos · Brian McFee · Gert R. G. Lanckriet

Source URL: eceweb.ucsd.edu

Multiple Kernel Learning, Conic Duality, and the SMO Algorithm Francis R. Bach & Gert R. G. Lanckriet {fbach,gert}@cs.berkeley.edu Department of Electrical Engineering and Computer Science, University of California, Ber

Source URL: eceweb.ucsd.edu

• Machine learning
• Learning
• Support vector machines
• Artificial intelligence
• Sequential minimal optimization
• Multiple kernel learning
• NC
• Kernel method
• KarushKuhnTucker conditions

Multi-Class Object Localization by Combining Local Contextual Interactions Carolina Galleguillos† Brian McFee† Serge Belongie† Gert Lanckriet‡ † Computer Science and Engineering Department

Source URL: eceweb.ucsd.edu

• Machine learning
• Learning
• Artificial intelligence
• Statistical classification
• Image processing
• Data mining
• Multiple kernel learning
• Image segmentation
• Kernel
• K-nearest neighbors algorithm
• Conditional random field
• Outline of object recognition

570 IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 20, NO. 2, FEBRUARY 2011 Contextual Object Localization With Multiple Kernel Nearest Neighbor

Source URL: eceweb.ucsd.edu

• Machine learning
• Artificial intelligence
• Learning
• Image processing
• Feature detection
• K-nearest neighbors algorithm
• Statistical classification
• Multiple kernel learning
• Kernel
• Image segmentation
• Outline of object recognition
• Positive-definite kernel

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 0, NO. 0, Doubly Sparse Relevance Vector Machine for Continuous Facial Behavior Estimation

Source URL: ibug.doc.ic.ac.uk

• Relevance vector machine
• Multiple kernel learning
• Normal distribution
• Support vector machine
• Positive-definite kernel
• Affective computing

Multi-Instance Methods for Partially Supervised Image Segmentation Andreas M¨ uller? and Sven Behnke , Autonomous Intelligent Systems

Source URL: amueller.github.io

• Machine learning
• Formal sciences
• Artificial intelligence
• Image processing
• Image segmentation
• Computer vision
• Support vector machine
• Pattern recognition
• Kernel method
• Multiple-instance learning
• Statistical classification
• Multiple kernel learning

Online Learning of Structured Predictors with Multiple Kernels Andr´e F. T. Martins∗† Noah A. Smith∗ Eric P. Xing∗ Pedro M. Q. Aguiar‡ M´ario A. T. Figueiredo† ∗ ‡ †

Source URL: users.isr.ist.utl.pt

• Data mining
• Multiple kernel learning
• Statistical classification
• Machine learning
• Support vector machine
• Kernel method
• Feature selection
• Positive-definite kernel
• Kernel
• Structured prediction

Decentralized Detection and Classification using Kernel Methods XuanLong Nguyen Computer Science Division University of California, Berkeley

Source URL: dept.stat.lsa.umich.edu

• Hilbert space
• Statistical classification
• Operator theory
• Positive-definite kernel
• Machine learning
• Support vector machine
• Reproducing kernel Hilbert space
• Learning
• Statistics
• Analysis
• Multiple kernel learning
• Kernel embedding of distributions

A Binary Classification Framework for Two-Stage Multiple Kernel Learning Abhishek Kumar Department of Computer Science, University of Maryland, College Park, MD 20742, USA

Source URL: koray.kavukcuoglu.org