The selection of features that are relevant for a prediction or classification problem is an important problem in many domains involving high-dimensional data. Selecting features h...
Michel Verleysen, Fabrice Rossi, Damien Fran&ccedi...
Nonparametric methods are widely applicable to statistical learning problems, since they rely on a few modeling assumptions. In this context, the fresh look advocated here permeat...
Compressed sensing, an emerging multidisciplinary field involving mathematics, probability, optimization, and signal processing, focuses on reconstructing an unknown signal from a...
Shiqian Ma, Wotao Yin, Yin Zhang, Amit Chakraborty
The quantum adversary method is one of the most successful techniques for proving lower bounds on quantum query complexity. It gives optimal lower bounds for many problems, has ap...
Regime switching models, in which the state of the world is locally stationary, are a useful abstraction for many continuous valued data streams. In this paper we develop an onlin...
Gordon J. Ross, Dimitris K. Tasoulis, Niall M. Ada...