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PKDD
2010
Springer
212views Data Mining» more  PKDD 2010»
13 years 9 months ago
Cross Validation Framework to Choose amongst Models and Datasets for Transfer Learning
Abstract. One solution to the lack of label problem is to exploit transfer learning, whereby one acquires knowledge from source-domains to improve the learning performance in the t...
ErHeng Zhong, Wei Fan, Qiang Yang, Olivier Versche...
KDD
2006
ACM
134views Data Mining» more  KDD 2006»
14 years 11 months ago
Learning to rank networked entities
Several algorithms have been proposed to learn to rank entities modeled as feature vectors, based on relevance feedback. However, these algorithms do not model network connections...
Alekh Agarwal, Soumen Chakrabarti, Sunny Aggarwal
ELPUB
2007
ACM
14 years 2 months ago
Designing Metadata Surrogates for Search Result Interfaces of Learning Object Repositories: Linear versus Clustered Metadata Des
This study reports the findings of a usability test conducted to examine users' interaction with two different learning object metadata-driven search result interfaces. The f...
Panos Balatsoukas, Anne Morris, Ann O'Brien
DAGSTUHL
2009
13 years 11 months ago
Learning Highly Structured Manifolds: Harnessing the Power of SOMs
Abstract. In this paper we elaborate on the challenges of learning manifolds that have many relevant clusters, and where the clusters can have widely varying statistics. We call su...
Erzsébet Merényi, Kadim Tasdemir, Li...
CORR
2011
Springer
178views Education» more  CORR 2011»
13 years 2 months ago
Online Learning: Stochastic and Constrained Adversaries
Learning theory has largely focused on two main learning scenarios. The first is the classical statistical setting where instances are drawn i.i.d. from a fixed distribution and...
Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari