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FLAIRS
2004
15 years 5 months ago
Semi-Supervised Sequence Classification with HMMs
Using unlabeled data to help supervised learning has become an increasingly attractive methodology and proven to be effective in many applications. This paper applies semi-supervi...
Shi Zhong
DATAMINE
2006
139views more  DATAMINE 2006»
15 years 4 months ago
Discovering Classification from Data of Multiple Sources
In many large e-commerce organizations, multiple data sources are often used to describe the same customers, thus it is important to consolidate data of multiple sources for intell...
Charles X. Ling, Qiang Yang
INTERSPEECH
2010
14 years 11 months ago
Still talking to machines (cognitively speaking)
This overview article reviews the structure of a fully statistical spoken dialogue system (SDS), using as illustration, various systems and components built at Cambridge over the ...
Steve Young
ECML
2004
Springer
15 years 9 months ago
Batch Reinforcement Learning with State Importance
Abstract. We investigate the problem of using function approximation in reinforcement learning where the agent’s policy is represented as a classifier mapping states to actions....
Lihong Li, Vadim Bulitko, Russell Greiner

Publication
922views
16 years 11 months ago
Multi-Class Active Learning for Image Classification
One of the principal bottlenecks in applying learning techniques to classification problems is the large amount of labeled training data required. Especially for images and video, ...
Ajay J. Joshi, Fatih Porikli, Nikolaos Papanikolop...