In recent years, a fundamental problem structure has emerged as very useful in a variety of machine learning applications: Submodularity is an intuitive diminishing returns proper...
In this paper the sequential prediction problem with expert advice is considered when the loss is unbounded under partial monitoring scenarios. We deal with a wide class of the par...
Principal Component Analysis (PCA) is a well-established technique in image processing and pattern recognition. Incremental PCA and robust PCA are two interesting problems with nu...
Yongmin Li Li, Li-Qun Xu, Jason Morphett, Richard ...
Conditional log-linear models are a commonly used method for structured prediction. Efficient learning of parameters in these models is therefore an important problem. This paper ...
Amir Globerson, Terry Koo, Xavier Carreras, Michae...
—Inspired by the contours in topography, this paper proposes a contour method for the population-based stochastic algorithms to solve the problems with continuous variables. Rely...