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TSP
2010
14 years 6 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»
15 years 6 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
15 years 5 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...
105
Voted
SDM
2011
SIAM
233views Data Mining» more  SDM 2011»
14 years 2 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
85
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CHI
2009
ACM
15 years 4 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...