Up to now, most contributions to collaborative filtering rely on rating prediction to generate the recommendations. We, instead, try to correctly rank the items according to the users’ tastes. First, we define a ranking error function which takes available pairwise preferences between items into account. Then we design an effective algorithm that optimizes this error. Finally we illustrate the ...

This paper presents our Chinese-toJapanese patent machine translation system for WAT 2015 (Group ID: ntt) that uses syntactic pre-ordering over Chinese dependency structures. A head word and its modifier words are reordered by hand-written rules or a learning-to-rank model. Our system outperforms baseline phrase-based machine translations and competes with baseline tree-to-string machine transl...

Gait is a useful biometric because it can operate from a distance and without subject cooperation. However, it is affected by changes in covariate conditions (carrying, clothing, view angle, etc.). Existing methods suffer from lack of training samples, can only cope with changes in a subset of conditions with limited success, and implicitly assume subject cooperation. We propose a novel approac...

In this paper, we study the impact of relational and syntactic representations for an interesting and challenging task: the automatic resolution of crossword puzzles. Automatic solvers are typically based on two answer retrieval modules: (i) a web search engine, e.g., Google, Bing, etc. and (ii) a database (DB) system for accessing previously resolved crossword puzzles. We show that learning to...

Uncovering unknown or missing links in social networks is a difficult task because of their sparsity, and because links may represent different types of relationships, characterized by different structural patterns. In this paper, we define a simple yet efficient supervised learning-to-rank framework, called RankMerging, which aims at combining information provided by various unsupervised ranki...

Abstract In this work, we consider the issue of unveiling unknown links in a social network, one of the difficulties of this problem being the small number of unobserved links in comparison of the total number of pairs of nodes. We define a simple supervised learning-to-rank framework, called RankMerging, which aims at combining information provided by various unsupervised rankings. As an illus...

[1] Tsochantaridis, Ioannis, Joachims, Thorsten, Hofmann, Thomas, and Altun, Yasemin. Large margin methods for structured and interdependent output variables. JMLR, 6: 1453-1484, 2005. [2] Joachims, Thorsten, Finley, Thomas, and Yu, Chun-nam John. Cuttingplane training of structural SVMs. Machine Learning, 77(1):27-59, 2009. References Da ta Matchings 506,688 439,161 Users 294,832 247,430 Queri...