By Jin-Yi Cai
This number of contemporary papers on computational complexity conception grew out of actions in the course of a unique yr at DIMACS. With contributions by way of many of the top specialists within the box, this ebook is of lasting price during this fast-moving box, delivering expositions now not discovered in other places. even supposing aimed essentially at researchers in complexity conception and graduate scholars in arithmetic or desktop technology, the ebook is on the market to a person with an undergraduate schooling in arithmetic or computing device technological know-how. via pertaining to a number of the significant subject matters in complexity idea, this e-book sheds gentle in this burgeoning quarter of analysis.
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Extra resources for Advances in Computational Complexity Theory
Details are shown in equation (5). CTR Prediction for DSP with Improved Cube Factorization Model 21 For the sake of enhancing efficiency for training, we borrow the way how matrix factorization approach is developed from SVD via absorbing the singular value matrix and deal with the tensor C in the similar means. Our experimental results show that extremely similar performance is achieved whether or not the tensor C is considered. 1 Experimental Setup 2 2 + p + a + bu 2 + bp 2 + ba 2 (7) λis a regularization coefficient.
Shan et al. High-order SVD Based Factor Model Lathauwer etc.  extend two-dimensional matrix Singular Value Decomposition (SVD) to high-order tensor and obtain high-order SVD (HOSVD). According to HOSVD, if given N = 3, then a tensor R can be factored into R = C ×1 X ×2 Y ×3 Z (Fig. 1). Matrix factorization closely related to SVD is used to solve matrix filling problem. Similarly, we apply third-order SVD-based factor model to address threedimensional cube complement problem. Specifically, it is supposed that x-axis, y-axis and z-axis of R represent users, pages and ads respectively(Fig.
E. dist(A,B)≠dist(B,A). We consider the larger one between dist(A,B) and dist(B,A) as the last similarity. The reason is that larger distance means smaller similarity and from our experience we have the lower risk to compare two object’s resemblance with choosing the smaller similarity measurement. It also accords with the fuzzy set theory. 1 Image Databases and Performance Measures Corel Database(DB) composed of 1000 color images with 10 classes are used to evaluate WMCF measurement. Our Brodatz-based texture database including 1776 texture images, is used to evaluate the retrieval performance of textures using unitlinking PCNN.