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» Making inferences with small numbers of training sets
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CVPR
2009
IEEE
15 years 2 months ago
Shared Kernel Information Embedding for Discriminative Inference
Latent Variable Models (LVM), like the Shared-GPLVM and the Spectral Latent Variable Model, help mitigate over- fitting when learning discriminative methods from small or modera...
David J. Fleet, Leonid Sigal, Roland Memisevic
IVA
2009
Springer
14 years 2 months ago
Predicting User Psychological Characteristics from Interactions with Empathetic Virtual Agents
Enabling virtual agents to quickly and accurately infer users’ psychological characteristics such as their personality could support a broad range of applications in education, t...
Jennifer L. Robison, Jonathan P. Rowe, Scott W. Mc...
ICANN
2001
Springer
14 years 2 days ago
Fast Training of Support Vector Machines by Extracting Boundary Data
Support vector machines have gotten wide acceptance for their high generalization ability for real world applications. But the major drawback is slow training for classification p...
Shigeo Abe, Takuya Inoue
MM
2009
ACM
277views Multimedia» more  MM 2009»
14 years 2 months ago
Inferring semantic concepts from community-contributed images and noisy tags
In this paper, we exploit the problem of inferring images’ semantic concepts from community-contributed images and their associated noisy tags. To infer the concepts more accura...
Jinhui Tang, Shuicheng Yan, Richang Hong, Guo-Jun ...
WABI
2004
Springer
142views Bioinformatics» more  WABI 2004»
14 years 28 days ago
Linear Reduction for Haplotype Inference
Abstract. Haplotype inference problem asks for a set of haplotypes explaining a given set of genotypes. Popular software tools for haplotype inference (e.g., PHASE, HAPLOTYPER) as ...
Jingwu He, Alexander Zelikovsky