Sparse regression and marginal testing using cluster prototypes
نویسندگان
چکیده
منابع مشابه
Sparse regression and marginal testing using cluster prototypes.
We propose a new approach for sparse regression and marginal testing, for data with correlated features. Our procedure first clusters the features, and then chooses as the cluster prototype the most informative feature in that cluster. Then we apply either sparse regression (lasso) or marginal significance testing to these prototypes. While this kind of strategy is not entirely new, a key featu...
متن کاملRegression Testing of Virtual Prototypes Using Symbolic Execution
Recently virtual platforms and virtual prototyping techniques have been widely applied for accelerating software development in electronics companies. It has been proved that these techniques can greatly shorten time-to-market and improve product quality. One challenge is how to test and validate a virtual prototype. In this paper, we present how to conduct regression testing of virtual prototy...
متن کاملSmooth Sparse Coding via Marginal Regression
The face recognition experiment was conducted on the CMU Multi-PIE dataset. The dataset is challenging due to the large number of subjects and is one of the standard data sets used for face recognition experiments. The data set contains 337 subjects across simultaneous variations in pose, expression, and illumination. We ignore the 88 subjects that were considered as outliers in (Yang et al., 2...
متن کاملSmooth Sparse Coding via Marginal Regression for Learning Sparse Representations
We propose and analyze a novel framework for learning sparse representations, based on two statistical techniques: kernel smoothing and marginal regression. The proposed approach provides a flexible framework for incorporating feature similarity or temporal information present in data sets, via non-parametric kernel smoothing. We provide generalization bounds for dictionary learning using smoot...
متن کاملDocument clustering using synthetic cluster prototypes
Article history: Received 17 December 2009 Received in revised form 11 December 2010 Accepted 13 December 2010 Available online 24 December 2010 The use of centroids as prototypes for clustering text documents with the k-means family of methods isnot always thebest choice for representing text clusters due to thehighdimensionality, sparsity, and low quality of text data. Especially for the case...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Biostatistics
سال: 2015
ISSN: 1465-4644,1468-4357
DOI: 10.1093/biostatistics/kxv049