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ICCV
2009
IEEE
1019views Computer Vision» more  ICCV 2009»
15 years 3 months ago
Similarity Functions for Categorization: from Monolithic to Category Specific
Similarity metrics that are learned from labeled training data can be advantageous in terms of performance and/or efficiency. These learned metrics can then be used in conjuncti...
Boris Babenko, Steve Branson, Serge Belongie
ICANN
2009
Springer
14 years 2 months ago
Efficient Uncertainty Propagation for Reinforcement Learning with Limited Data
In a typical reinforcement learning (RL) setting details of the environment are not given explicitly but have to be estimated from observations. Most RL approaches only optimize th...
Alexander Hans, Steffen Udluft
PADL
2012
Springer
12 years 5 months ago
LearnPADS + + : Incremental Inference of Ad Hoc Data Formats
An ad hoc data source is any semi-structured, non-standard data source. The format of such data sources is often evolving and frequently lacking documentation. Consequently, off-t...
Kenny Qili Zhu, Kathleen Fisher, David Walker
SEMWEB
2012
Springer
12 years 5 months ago
How to deal with massively heterogeneous cultural heritage data - lessons learned in CultureSampo
Abstract. This paper presents the CultureSampo system from the viewpoint of publishing heterogeneous linked data as a service. Discussed are the problems of converting legacy data ...
Eetu Mäkelä, Eero Hyvönen, Tuukka R...
KDD
2007
ACM
211views Data Mining» more  KDD 2007»
14 years 10 months ago
Enhanced max margin learning on multimodal data mining in a multimedia database
The problem of multimodal data mining in a multimedia database can be addressed as a structured prediction problem where we learn the mapping from an input to the structured and i...
Zhen Guo, Zhongfei Zhang, Eric P. Xing, Christos F...