Covariate shift is a situation in supervised learning where training and test inputs follow different distributions even though the functional relation remains unchanged. A common...
Yuta Tsuboi, Hisashi Kashima, Shohei Hido, Steffen...
— The exploration problem is a central issue in mobile robotics. A complete coverage is not practical if the environment is large with a few small hotspots, and the sampling cost...
Kian Hsiang Low, Geoffrey J. Gordon, John M. Dolan...
We present a near-optimal reduction from approximately counting the cardinality of a discrete set to approximately sampling elements of the set. An important application of our wo...
We present a new "hp" parameter multi-domain certified reduced basis method for rapid and reliable online evaluation of functional outputs associated with parametrized el...
Jens L. Eftang, Anthony T. Patera, Einar M. R&osla...
In this paper, we present a new Adaptive Scale Kernel Consensus (ASKC) robust estimator as a generalization of the popular and state-of-the-art robust estimators such as RANSAC (R...