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ICML
2004
IEEE
14 years 8 months ago
Training conditional random fields via gradient tree boosting
Conditional Random Fields (CRFs; Lafferty, McCallum, & Pereira, 2001) provide a flexible and powerful model for learning to assign labels to elements of sequences in such appl...
Thomas G. Dietterich, Adam Ashenfelter, Yaroslav B...
LATIN
2010
Springer
13 years 5 months ago
On Quadratic Threshold CSPs
A predicate P : {−1, 1}k → {0, 1} can be associated with a constraint satisfaction problem Max CSP(P). P is called “approximation resistant” if Max CSP(P) cannot be approxi...
Per Austrin, Siavosh Benabbas, Avner Magen
DCOSS
2009
Springer
14 years 1 months ago
Cheap or Flexible Sensor Coverage
We consider dual classes of geometric coverage problems, in which disks, corresponding to coverage regions of sensors, are used to cover a region or set of points in the plane. The...
Amotz Bar-Noy, Theodore Brown, Matthew P. Johnson,...
TASE
2010
IEEE
13 years 2 months ago
Coverage of a Planar Point Set With Multiple Robots Subject to Geometric Constraints
This paper focuses on the assignment of discrete points among K robots and determining the order in which the points should be processed by the robots, in the presence of geometric...
Nilanjan Chakraborty, Srinivas Akella, John T. Wen
APPROX
2005
Springer
111views Algorithms» more  APPROX 2005»
14 years 27 days ago
Sampling Bounds for Stochastic Optimization
A large class of stochastic optimization problems can be modeled as minimizing an objective function f that depends on a choice of a vector x ∈ X, as well as on a random external...
Moses Charikar, Chandra Chekuri, Martin Pál