Selecting the optimal kernel is an important and difficult challenge in applying kernel methods to pattern recognition. To address this challenge, multiple kernel learning (MKL) ...
We study the problem of context-sensitive ranking for document retrieval, where a context is defined as a sub-collection of documents, and is specified by queries provided by do...
Tag recommendation is the task of predicting a personalized list of tags for a user given an item. This is important for many websites with tagging capabilities like last.fm or de...
Naive Bayes has been widely used in data mining as a simple and effective classification algorithm. Since its conditional independence assumption is rarely true, numerous algorit...
Liangxiao Jiang, Harry Zhang, Zhihua Cai, Jiang Su
ent abstract presents OASIS, an Online Algorithm for Scalable Image Similarity learning that learns a bilinear similarity measure over sparse representations. OASIS is an online du...
Gal Chechik, Varun Sharma, Uri Shalit, Samy Bengio