In many applications it is desirable to learn from several kernels. "Multiple kernel learning" (MKL) allows the practitioner to optimize over linear combinations of kern...
We examine the problem of evaluating a policy in the contextual bandit setting using only observations collected during the execution of another policy. We show that policy evalua...
John Langford, Alexander L. Strehl, Jennifer Wortm...
A good distance measure for time series needs to properly incorporate the temporal structure, and should be applicable to sequences with unequal lengths. In this paper, we propose...
Zhengdong Lu, Todd K. Leen, Yonghong Huang, Deniz ...
We propose new features and algorithms for automating Web-page classification tasks such as content recommendation and ad blocking. We show that the automated classification of We...
Abstract. A class of probabilistic-logic models is considered, which increases the expressibility from HMM's and SCFG's regular and contextfree languages to, in principle...