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» Approximation algorithms for budgeted learning problems
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SODA
2012
ACM
226views Algorithms» more  SODA 2012»
11 years 11 months ago
On the hardness of pricing loss-leaders
Consider the problem of pricing n items under an unlimited supply with m buyers. Each buyer is interested in a bundle of at most k of the items. These buyers are single minded, wh...
Preyas Popat, Yi Wu
ICML
2005
IEEE
14 years 9 months ago
Learning as search optimization: approximate large margin methods for structured prediction
Mappings to structured output spaces (strings, trees, partitions, etc.) are typically learned using extensions of classification algorithms to simple graphical structures (eg., li...
Daniel Marcu, Hal Daumé III
ESA
2005
Springer
114views Algorithms» more  ESA 2005»
14 years 2 months ago
Unbalanced Graph Cuts
We introduce the Minimum-size bounded-capacity cut (MinSBCC) problem, in which we are given a graph with an identified source and seek to find a cut minimizing the number of node...
Ara Hayrapetyan, David Kempe, Martin Pál, Z...
COLT
2010
Springer
13 years 6 months ago
Open Loop Optimistic Planning
We consider the problem of planning in a stochastic and discounted environment with a limited numerical budget. More precisely, we investigate strategies exploring the set of poss...
Sébastien Bubeck, Rémi Munos
NIPS
2007
13 years 10 months ago
Structured Learning with Approximate Inference
In many structured prediction problems, the highest-scoring labeling is hard to compute exactly, leading to the use of approximate inference methods. However, when inference is us...
Alex Kulesza, Fernando Pereira