Cfrgtkky

up vote 0 down vote favorite For 2 months I have been studying sparse recovery and its applications for image classification and I have found that it's a broad area in mathematics which gives rise to a wide variety of regularization techniques. However, I am struggling to understand and implement the sparse recovery of the sparse vector by $L_1$ shrinkage iteration based on prior knowledge of labels. Actually, I have a dictionary size $200 times 58000$ (fat matrix) which constructed by a prior knowledge of classes (which needs to be redundant), and I have the knowledge of labels and I try to find the $L^1$ optimal solution using soft-shrinkage iteration which is as follows: We have the linear combination. $$y = Dx$$ and we use the least squares method to minimize $x$ $$|y - Dx|^2 + lambda|x|_1tomin_x$$ My question i...

up vote 0 down vote favorite 1 I am using book class and I want to create a part in TOC in the following way: I want the part centred in the middle of the page and the chapters on the other page. Here is my code: documentclass[12pt]{book} makeatletter def@part[#1]#2{% ifnum c@secnumdepth >-2relax refstepcounter{part}% addcontentsline{toc}{part}{protectnumberline{thepart}#1} else addcontentsline{toc}{part}{#1}% fi markboth{}{}% {centering interlinepenalty @M normalfont ifnum c@secnumdepth >-2relax hugebfseries partnamenobreakspacethepart par vskip 20p@ fi Huge bfseries #2par}% @endpart} renewcommandl@part[2]{% thispagestyle{empty} newpage vspace*{fill} begin{center} defnumberlin...