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TSP
2010
13 years 3 months ago
Distributed sparse linear regression
The Lasso is a popular technique for joint estimation and continuous variable selection, especially well-suited for sparse and possibly under-determined linear regression problems....
Gonzalo Mateos, Juan Andrés Bazerque, Georg...
PSIVT
2009
Springer
139views Multimedia» more  PSIVT 2009»
14 years 3 months ago
Recognizing Multiple Objects via Regression Incorporating the Co-occurrence of Categories
Abstract. Most previous methods for generic object recognition explicitly or implicitly assume that an image contains objects from a single category, although objects from multiple...
Takahiro Okabe, Yuhi Kondo, Kris M. Kitani, Yoichi...
ICSR
2004
Springer
14 years 1 months ago
Validating Quality of Service for Reusable Software Via Model-Integrated Distributed Continuous Quality Assurance
Quality assurance (QA) tasks, such as testing, profiling, and performance evaluation, have historically been done in-house on developer-generated workloads and regression suites. ...
Arvind S. Krishna, Douglas C. Schmidt, Atif M. Mem...
SDM
2011
SIAM
233views Data Mining» more  SDM 2011»
12 years 11 months ago
Distributed Monitoring of the R2 Statistic for Linear Regression
The problem of monitoring a multivariate linear regression model is relevant in studying the evolving relationship between a set of input variables (features) and one or more depe...
Kanishka Bhaduri, Kamalika Das, Chris Giannella
CHI
2009
ACM
14 years 1 months ago
Stress outsourced: a haptic social network via crowdsourcing
Stress OutSourced (SOS) is a peer-to-peer network that allows anonymous users to send each other therapeutic massages to relieve stress. By applying the emerging concept of crowds...
Keywon Chung, Carnaven Chiu, Xiao Xiao, Pei-Yu (Pe...