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Lasso-type feature selection has been demonstrated to be effective in handling high dimensional data. Most existing Lasso-type models over emphasize the sparsityandoverlooktheinteractionsamongcovariates. Here on the other hand, we devise a new regularization term in the Lasso regression model to impose high order interactions between covariates and responses. SpeciÞcally, we Þrst construct a feature hypergraph to model the high-order relations among covariates, in which each node corresponds to a covariate and each hyperedge has a weight corresponding to the interaction information among covariates connected by that hyperedge. For the hyperedge weight, we use multidimensional interaction information (MII) to measure the signiÞcance of different covariate combinations with respect to response. Secondly, we use the feature hypergraph as a regularizer on the covariate coefÞcients which can automatically adjust the relevance measure between a covariate and the response by the interaction weights obtained from hypergraph. Finally, an efÞcientalternatingdirectionmethodofmultipliers (ADMM) is presented to solve the resulting sparse optimization problem. Extensive experiments on different data sets show that although our proposed model is not a convex problem, it outperforms both its approximately convex counterparts and a number of state-of-the-art feature selection methods.

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This paper presents an education framework to effectively develop crucial software engineering skills in students of software Engineering major at National Exemplary Software School (NESS), Xiamen University. The goal is to describe a systematic approach towards integrating project based learning in software engineering major, both inside and outside the classroom. An essential part of Software Engineering Education is practical training in principles, methods and procedures under conditions similar to developing real software products. This paper describes the different conventional and traditional approaches at length for Software Engineering Education and proposes integrated project based learning approach is more effective and interesting for teaching and learning SE as compared to the lecture based approach.

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