This paper proposes a novel approach for directly tuning the gaussian kernel matrix for one class learning. The popular gaussian kernel includes a free parameter, σ, that requires...
Paul F. Evangelista, Mark J. Embrechts, Boleslaw K...
In this paper, we present performance analysis of two NASA applications using performance tools like Tuning and Analysis Utilities (TAU) and SGI MPInside. MITgcmUV and OVERFLOW ar...
Abstract. This paper focuses in the analysis of 100% static and distributed inter-cell interference coordination techniques in the context of LTE networks. Several methods have bee...
Adaptive Monte Carlo methods are specialized Monte Carlo simulation techniques where the methods are adaptively tuned as the simulation progresses. The primary focus of such techn...
We propose a general framework for improving the query processing performance on multi-level memory hierarchies. Our motivation is that (1) the memory hierarchy is an important pe...