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SIGIR
2008
ACM
14 years 9 months ago
Learning from labeled features using generalized expectation criteria
It is difficult to apply machine learning to new domains because often we lack labeled problem instances. In this paper, we provide a solution to this problem that leverages domai...
Gregory Druck, Gideon S. Mann, Andrew McCallum
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...
GECCO
2007
Springer
177views Optimization» more  GECCO 2007»
15 years 4 months ago
Evolving problem heuristics with on-line ACGP
Genetic Programming uses trees to represent chromosomes. The user defines the representation space by defining the set of functions and terminals to label the nodes in the trees. ...
Cezary Z. Janikow
COR
2007
108views more  COR 2007»
14 years 9 months ago
New primal-dual algorithms for Steiner tree problems
We present new primal-dual algorithms for several network design problems. The problems considered are the generalized Steiner tree problem (GST), the directed Steiner tree proble...
Vardges Melkonian
CCE
2004
14 years 9 months ago
Continuous reformulations of discrete-continuous optimization problems
This paper treats the solution of nonlinear optimization problems involving discrete decision variables, also known as generalized disjunctive programming (GDP) or mixed-integer n...
Oliver Stein, Jan Oldenburg, Wolfgang Marquardt