Looking at the papers from this summer's machine learning conferences
(AAAI, UAI, IJCAI, ICML,COLT) it seems like there have been a lot of papers on L1 regularization this year. There are at least 3 papers on L1 regularization for structure learning by Koller, Wainwright, Murphy, several papers on minimizing l1 regularized log likelihood by Keerthi, Boyd, Gallen Andrew. A couple of groups are working on "Bayesian Logistic Regression" turns out to be "l1 regularized logistic regression" on closer look (surely Thomas Minka wouldn't approve of such term usage). This year's COLT has one.