The success of tensor-based subspace learning depends heavily on reducing correlations along the column vectors of the mode-k flattened matrix. In this work, we study the problem ...
Shuicheng Yan, Dong Xu, Stephen Lin, Thomas S. Hua...
— This paper describes the hardware architecture for a flexible probability density estimation unit to be used in a Large Vocabulary Speech Recognition System, and targeted for m...
Decoupling capacitance (decap) is an efficient way to reduce transient noise in on-chip power supply networks. However, excessive decap may cause more leakage power, chip resource...
Linear Discriminant Analysis (LDA) is one of the wellknown methods for supervised dimensionality reduction. Over the years, many LDA-based algorithms have been developed to cope w...
In this paper we propose an approximated structured prediction framework for large scale graphical models and derive message-passing algorithms for learning their parameters effic...