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PAMI
2007
176views more  PAMI 2007»
15 years 5 months ago
Approximate Labeling via Graph Cuts Based on Linear Programming
A new framework is presented for both understanding and developing graph-cut based combinatorial algorithms suitable for the approximate optimization of a very wide class of MRFs ...
Nikos Komodakis, Georgios Tziritas
CPM
2006
Springer
145views Combinatorics» more  CPM 2006»
15 years 10 months ago
Approximation of RNA Multiple Structural Alignment
Abstract. In the context of non-coding RNA (ncRNA) multiple structural alignment, Davydov and Batzoglou introduced in [7] the problem of finding the largest nested linear graph tha...
Marcin Kubica, Romeo Rizzi, Stéphane Vialet...
AUSAI
2005
Springer
15 years 12 months ago
Global Versus Local Constructive Function Approximation for On-Line Reinforcement Learning
: In order to scale to problems with large or continuous state-spaces, reinforcement learning algorithms need to be combined with function approximation techniques. The majority of...
Peter Vamplew, Robert Ollington
ICML
1999
IEEE
16 years 7 months ago
Machine-Learning Applications of Algorithmic Randomness
Most machine learning algorithms share the following drawback: they only output bare predictions but not the con dence in those predictions. In the 1960s algorithmic information t...
Volodya Vovk, Alexander Gammerman, Craig Saunders
ICML
1999
IEEE
16 years 7 months ago
Approximation Via Value Unification
: Numerical function approximation over a Boolean domain is a classical problem with wide application to data modeling tasks and various forms of learning. A great many function ap...
Paul E. Utgoff, David J. Stracuzzi