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ACL
2006
15 years 3 months ago
Japanese Dependency Parsing Using Co-Occurrence Information and a Combination of Case Elements
In this paper, we present a method that improves Japanese dependency parsing by using large-scale statistical information. It takes into account two kinds of information not consi...
Takeshi Abekawa, Manabu Okumura
104
Voted
ML
2010
ACM
15 years 19 days ago
Semi-supervised local Fisher discriminant analysis for dimensionality reduction
When only a small number of labeled samples are available, supervised dimensionality reduction methods tend to perform poorly due to overfitting. In such cases, unlabeled samples ...
Masashi Sugiyama, Tsuyoshi Idé, Shinichi Na...
135
Voted
ICALT
2011
IEEE
14 years 1 months ago
Personalized Forecasting Student Performance
Abstract—This work proposes a novel approach - personalized forecasting - to take into account the sequential effect in predicting student performance (PSP). Instead of using all...
Nguyen Thai-Nghe, Tomás Horváth, Lar...
130
Voted
ICML
2007
IEEE
16 years 3 months ago
Learning to rank: from pairwise approach to listwise approach
The paper is concerned with learning to rank, which is to construct a model or a function for ranking objects. Learning to rank is useful for document retrieval, collaborative fil...
Zhe Cao, Tao Qin, Tie-Yan Liu, Ming-Feng Tsai, Han...
115
Voted
ML
2010
ACM
124views Machine Learning» more  ML 2010»
15 years 19 days ago
Large scale image annotation: learning to rank with joint word-image embeddings
Image annotation datasets are becoming larger and larger, with tens of millions of images and tens of thousands of possible annotations. We propose a strongly performing method tha...
Jason Weston, Samy Bengio, Nicolas Usunier