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» Approximate Learning of Dynamic Models
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FOCS
2008
IEEE
15 years 11 months ago
What Can We Learn Privately?
Learning problems form an important category of computational tasks that generalizes many of the computations researchers apply to large real-life data sets. We ask: what concept ...
Shiva Prasad Kasiviswanathan, Homin K. Lee, Kobbi ...
146
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JAIR
2006
137views more  JAIR 2006»
15 years 5 months ago
Learning Sentence-internal Temporal Relations
In this paper we propose a data intensive approach for inferring sentence-internal temporal relations. Temporal inference is relevant for practical NLP applications which either e...
Maria Lapata, Alex Lascarides
137
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IPL
2007
94views more  IPL 2007»
15 years 5 months ago
The finite horizon investor problem with a budget constraint
We study a model that incorporates a budget constraint in a decision making problem. Our goal is to maximize the expected wealth, where in each time period we can either stop the ...
Asaf Levin
ICML
2005
IEEE
16 years 5 months ago
Bayesian hierarchical clustering
We present a novel algorithm for agglomerative hierarchical clustering based on evaluating marginal likelihoods of a probabilistic model. This algorithm has several advantages ove...
Katherine A. Heller, Zoubin Ghahramani
IEEECIT
2010
IEEE
15 years 3 months ago
Predictive and Dynamic Resource Allocation for Enterprise Applications
—Dynamic resource allocation has the potential to provide significant increases in total revenue in enterprise systems through the reallocation of available resources as the dem...
M. Al-Ghamdi, Adam P. Chester, Stephen A. Jarvis