Boosting is a general method for improving the accuracy of a learning algorithm. AdaBoost, short form for Adaptive Boosting method, consists of repeated use of a weak or a base le...
T. Ravindra Babu, M. Narasimha Murty, Vijay K. Agr...
This paper presents an adaptive discriminative generative model that generalizes the conventional Fisher Linear Discriminant algorithm and renders a proper probabilistic interpret...
Ruei-Sung Lin, David A. Ross, Jongwoo Lim, Ming-Hs...
Withthe proliferationof software agents and smart hardware devices there is a growing realization that large-scale problems can be addressed by integration of such standalone syst...
Many DTM schemes rely heavily on the accurate knowledge of the chip's dynamic thermal state to make optimal performance/ temperature trade-off decisions. This information is ...
This paper studies MIMO based rate adaptation (RA) in 802.11n wireless networks. Our case study shows that existing RA algorithms offer much lower throughput than even a fixed-rat...
Ioannis Pefkianakis, Yun Hu, Starsky H. Y. Wong, H...