For many ranking applications we would like to understand not only which items are top-ranked, but also why they are top-ranked. However, many of the best ranking algorithms (e.g....
Ansaf Salleb-Aouissi, Bert C. Huang, David L. Walt...
Abstract. In this study we propose a methodology to investigate possible prosody and voice quality correlates of social signals, and test-run it on annotated naturalistic recording...
High dimensionality of POMDP's belief state space is one major cause that makes the underlying optimal policy computation intractable. Belief compression refers to the method...
Xin Li, William Kwok-Wai Cheung, Jiming Liu, Zhili...
This paper examines high dimensional regression with noise-contaminated input and output data. Goals of such learning problems include optimal prediction with noiseless query poin...
We study a class of overrelaxed bound optimization algorithms, and their relationship to standard bound optimizers, such as ExpectationMaximization, Iterative Scaling, CCCP and No...