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ICIP
2004
IEEE
16 years 8 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
16 years 2 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...
204
Voted
IICAI
2003
15 years 8 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
16 years 1 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
237
Voted
EMMCVPR
2011
Springer
14 years 6 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