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IR
2010
14 years 9 months ago
Learning to rank with (a lot of) word features
In this article we present Supervised Semantic Indexing (SSI) which defines a class of nonlinear (quadratic) models that are discriminatively trained to directly map from the word...
Bing Bai, Jason Weston, David Grangier, Ronan Coll...
WWW
2009
ACM
15 years 6 months ago
A probabilistic model based approach for blended search
In this paper, we propose to model the blended search problem by assuming conditional dependencies among queries, VSEs and search results. The probability distributions of this mo...
Ning Liu, Jun Yan, Zheng Chen
ISVC
2010
Springer
14 years 9 months ago
Attention-Based Target Localization Using Multiple Instance Learning
Abstract. We propose a novel Multiple Instance Learning (MIL) framework to perform target localization from image sequences. The proposed approach consists of a softmax logistic re...
Karthik Sankaranarayanan, James W. Davis
AAAI
2004
15 years 22 days ago
Learning and Inferring Transportation Routines
This paper introduces a hierarchical Markov model that can learn and infer a user's daily movements through the commue model uses multiple levels of abstraction in order to b...
Lin Liao, Dieter Fox, Henry A. Kautz
ICASSP
2011
IEEE
14 years 3 months ago
Use of VTL-wise models in feature-mapping framework to achieve performance of multiple-background models in speaker verification
Recently, Multiple Background Models (M-BMs) [1, 2] have been shown to be useful in speaker verification, where the M-BMs are formed based on different Vocal Tract Lengths (VTLs)...
Achintya Kumar Sarkar, Srinivasan Umesh