We design and analyze interacting online algorithms for multitask classification that perform better than independent learners whenever the tasks are related in a certain sense. W...
We address the problem of computing joint sparse representation of visual signal across multiple kernel-based representations. Such a problem arises naturally in supervised visual...
This paper presents an optimal procrastinating voltage scheduling (OP-DVS) for hard real-time systems using stochastic workload information. Algorithms are presented for both sing...
Yan Zhang, Zhijian Lu, John Lach, Kevin Skadron, M...
Abstract. We present the OnlineDoubleMaxMinOver approach to obtain the Support Vectors in two class classification problems. With its linear time complexity and linear convergence ...
We introduce confidence-weighted linear classifiers, which add parameter confidence information to linear classifiers. Online learners in this setting update both classifier param...