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Recent documents in Faculty Worken-usMon, 25 Feb 2019 13:35:40 PST3600Active Set Support Vector Regression
https://digitalcommons.carleton.edu/cs_faculty/3
https://digitalcommons.carleton.edu/cs_faculty/3Sun, 06 Jan 2019 11:37:15 PST
We present ASVR, a new active set strategy to solve a straightforward reformulation of the standard support vector regression problem. This new algorithm is based on the successful ASVM algorithm for classification problems, and consists of solving a finite number of linear equations with a typically large dimensionality equal to the number of points to be approximated. However, by making use of the Sherman-Morrison-Woodbury formula, a much smaller matrix of the order of the original input space is inverted at each step. The algorithm requires no specialized quadratic or linear programming code, but merely a linear equation solver which is publicly available. ASVR is extremely fast, produces comparable generalization error to other popular algorithms, and is available on the web for download.
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David R. Musicant et al.Geographic Routing in Social Networks
https://digitalcommons.carleton.edu/cs_faculty/2
https://digitalcommons.carleton.edu/cs_faculty/2Sun, 06 Jan 2019 11:37:00 PST
We live in a ‘‘small world,’’ where two arbitrary people are likely connected by a short chain of intermediate friends. With scant information about a target individual, people can successively forward a message along such a chain. Experimental studies have verified this property in real social networks, and theoretical models have been advanced to explain it. However, existing theoretical models have not been shown to capture behavior in real-world social networks. Here, we introduce a richer model relating geography and social-network friendship, in which the probability of befriending a particular person is inversely proportional to the number of closer people. In a large social network, we show that one-third of the friendships are independent of geography and the remainder exhibit the proposed relationship. Further, we prove analytically that short chains can be discovered in every network exhibiting the relationship.
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David Liben-Nowell et al.Optimal Scheduling in a Queue with Differentiated Impatient Users
https://digitalcommons.carleton.edu/cs_faculty/1
https://digitalcommons.carleton.edu/cs_faculty/1Sun, 06 Jan 2019 11:36:47 PST
We consider a M/M/1 queue in which the average reward for servicing a job is an exponentially decaying function of the job’s sojourn time. The maximum reward and mean service times of a job are i.i.d. and chosen from arbitrary distributions. The scheduler is assumed to know the maximum reward, service rate, and age of each job. We prove that the scheduling policy that maximizes average reward serves the customer with the highest product of potential reward and service rate.
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Amy Csizmar Dalal et al.