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k-Nearest Neighbors (kNN) algorithm is a method to find the closest points in a dataset to a query point. The result of kNN can be used for classification and regression, both of which are commonly used in data mining and machine learning. In this paper, Enhanced Vote Count (EVC) circuit, which uses hardware to compare the quantized projected values of query and training/reference vectors instead...
Vote count (VC) is a fast search algorithm originally designed for similarity search on large scale data set. VC can be efficiently implemented using simple modification to the Random Access Memory (RAM) or other memory structures such as NOR or NAND Flash memory, such that the search complexity reduces to O(1) regardless of the dimensionality of data or the size of the data set. This paper proposes...
We propose a time-utility function (TUF)-based packet scheduling algorithm for streaming scalable media. In the proposed system, the scalable media is partitioned into data units of different quality layers, which are then prioritized and transmitted according to their TUFs that capture both their quality contributions to the decoded media and urgencies with respect to their playback schedule. For...
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