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ICML
2004
IEEE
16 years 2 months ago
Apprenticeship learning via inverse reinforcement learning
We consider learning in a Markov decision process where we are not explicitly given a reward function, but where instead we can observe an expert demonstrating the task that we wa...
Pieter Abbeel, Andrew Y. Ng
87
Voted
CORR
2008
Springer
118views Education» more  CORR 2008»
15 years 2 months ago
Learning Low-Density Separators
Abstract. We define a novel, basic, unsupervised learning problem learning the the lowest density homogeneous hyperplane separator of an unknown probability distribution. This task...
Shai Ben-David, Tyler Lu, Dávid Pál,...
102
Voted
MFCS
2007
Springer
15 years 8 months ago
On the Complexity of Computing Treelength
We resolve the computational complexity of determining the treelength of a graph, thereby solving an open problem of Dourisboure and Gavoille, who introduced this parameter, and a...
Daniel Lokshtanov
118
Voted
CIKM
2009
Springer
15 years 8 months ago
Learning to rank graphs for online similar graph search
Many applications in structure matching require the ability to search for graphs that are similar to a query graph, i.e., similarity graph queries. Prior works, especially in chem...
Bingjun Sun, Prasenjit Mitra, C. Lee Giles
NIPS
2004
15 years 3 months ago
Proximity Graphs for Clustering and Manifold Learning
Many machine learning algorithms for clustering or dimensionality reduction take as input a cloud of points in Euclidean space, and construct a graph with the input data points as...
Miguel Á. Carreira-Perpiñán, ...