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ICIP
2004
IEEE
15 years 11 months ago
Automatically learning structural units in educational videos with the hierarchical hidden markov models
In this paper we present a coherent approach using the hierarchical HMM with shared structures to extract the structural units that form the building blocks of an education/traini...
Dinh Q. Phung, Svetha Venkatesh, Hung Hai Bui
MICCAI
2009
Springer
15 years 4 months ago
On the Manifold Structure of the Space of Brain Images
This paper investigates an approach to model the space of brain images through a low-dimensional manifold. A data driven method to learn a manifold from a collections of brain imag...
Samuel Gerber, Tolga Tasdizen, Sarang C. Joshi, Ro...
IICAI
2003
14 years 11 months ago
Performance Analysis of an Acyclic Genetic approach to Learn Bayesian Network Structure
Abstract. We introduce a new genetic algorithm approach for learning a Bayesian network structure from data. Our method is capable of learning over all node orderings and structure...
Pankaj B. Gupta, Vicki H. Allan
IJCNN
2007
IEEE
15 years 4 months ago
Agnostic Learning versus Prior Knowledge in the Design of Kernel Machines
Abstract— The optimal model parameters of a kernel machine are typically given by the solution of a convex optimisation problem with a single global optimum. Obtaining the best p...
Gavin C. Cawley, Nicola L. C. Talbot
EMMCVPR
2011
Springer
13 years 9 months ago
Multiple-Instance Learning with Structured Bag Models
Traditional approaches to Multiple-Instance Learning (MIL) operate under the assumption that the instances of a bag are generated independently, and therefore typically learn an in...
Jonathan Warrell, Philip H. S. Torr