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FOCS
2005
IEEE
15 years 3 months ago
How to Pay, Come What May: Approximation Algorithms for Demand-Robust Covering Problems
Robust optimization has traditionally focused on uncertainty in data and costs in optimization problems to formulate models whose solutions will be optimal in the worstcase among ...
Kedar Dhamdhere, Vineet Goyal, R. Ravi, Mohit Sing...
CSDA
2008
128views more  CSDA 2008»
14 years 10 months ago
Classification tree analysis using TARGET
Tree models are valuable tools for predictive modeling and data mining. Traditional tree-growing methodologies such as CART are known to suffer from problems including greediness,...
J. Brian Gray, Guangzhe Fan
ICCAD
1997
IEEE
108views Hardware» more  ICCAD 1997»
15 years 2 months ago
Negative thinking by incremental problem solving: application to unate covering
We introduce a new technique to solve exactly a discrete optimization problem, based on the paradigm of “negative” thinking. The motivation is that when searching the space of...
Evguenii I. Goldberg, Luca P. Carloni, Tiziano Vil...
KBSE
2007
IEEE
15 years 4 months ago
Test suite reduction and prioritization with call trees
This paper presents a tool that (i) constructs tree-based models of a program’s behavior during testing and (ii) employs these trees while reordering and reducing a test suite. ...
Adam M. Smith, Joshua Geiger, Gregory M. Kapfhamme...
AHSWN
2008
92views more  AHSWN 2008»
14 years 10 months ago
The (k, l) Coredian Tree for Ad Hoc Networks
In this paper, we present a new efficient strategy for constructing a wireless tree network containing n nodes of diameter while satisfying the QoS requirements such as bandwidth...
Amit Dvir, Michael Segal