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185
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SIGIR
2012
ACM
13 years 6 months ago
Top-k learning to rank: labeling, ranking and evaluation
In this paper, we propose a novel top-k learning to rank framework, which involves labeling strategy, ranking model and evaluation measure. The motivation comes from the difficul...
Shuzi Niu, Jiafeng Guo, Yanyan Lan, Xueqi Cheng
ICPR
2010
IEEE
15 years 11 months ago
Gait Learning-Based Regenerative Model: A Level Set Approach
We propose a learning method for gait synthesis from a sequence of shapes(frames) with the ability to extrapolate to novel data. It involves the application of PCA, first to redu...
Muayed Sattar Al-Huseiny, Sasan Mahmoodi, Mark Nix...
149
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EMNLP
2007
15 years 5 months ago
A Discriminative Learning Model for Coordinate Conjunctions
We propose a sequence-alignment based method for detecting and disambiguating coordinate conjunctions. In this method, averaged perceptron learning is used to adapt the substituti...
Masashi Shimbo, Kazuo Hara
WWW
2004
ACM
16 years 4 months ago
Mining models of human activities from the web
The ability to determine what day-to-day activity (such as cooking pasta, taking a pill, or watching a video) a person is performing is of interest in many application domains. A ...
Mike Perkowitz, Matthai Philipose, Kenneth P. Fish...
HIS
2008
15 years 5 months ago
Artificial Data Sets Based on Knowledge Generators: Analysis of Learning Algorithms Efficiency
This paper proposes a methodology to generate artificial data sets to evaluate the behavior of machine learning techniques. The methodology relies in the definition of a domain an...
Joaquin Rios-Boutin, Albert Orriols-Puig, Josep Ma...