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» Learning with Knowledge from Multiple Experts
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ICCV
2003
IEEE
14 years 3 months ago
Reinforcement Learning for Combining Relevance Feedback Techniques
Relevance feedback (RF) is an interactive process which refines the retrievals by utilizing user’s feedback history. Most researchers strive to develop new RF techniques and ign...
Peng-Yeng Yin, Bir Bhanu, Kuang-Cheng Chang, Anlei...
ICASSP
2009
IEEE
14 years 4 months ago
Multi-view tracking of articulated human motion in silhouette and pose manifolds
This paper presents a multi-view articulated human motion tracking framework using particle filter with manifold learning through Gaussian process latent variable model. The dime...
Feng Guo, Gang Qian
IJCAI
2007
13 years 11 months ago
A Hybrid Ontology Directed Feedback Selection Algorithm for Supporting Creative Problem Solving Dialogues
We evaluate a new hybrid language processing approach designed for interactive applications that maintain an interaction with users over multiple turns. Specifically, we describe ...
Hao-Chuan Wang, Rohit Kumar, Carolyn Penstein Ros&...
ACSC
2006
IEEE
14 years 3 months ago
Using formal concept analysis with an incremental knowledge acquisition system for web document management
It is necessary to provide a method to store Web information effectively so it can be utilised as a future knowledge resource. A commonly adopted approach is to classify the retri...
Timothy J. Everts, Sung Sik Park, Byeong Ho Kang
ICML
2000
IEEE
14 years 10 months ago
Discovering Homogeneous Regions in Spatial Data through Competition
If all features causing heterogeneity were observed, a mixture of experts approach (Jacobs et al., 1991) is likely to be superior to using a single model. When unobserved or very n...
Slobodan Vucetic, Zoran Obradovic