This paper approaches the relation classification problem in information extraction framework with different machine learning strategies, from strictly supervised to weakly superv...
This paper presents a method for learning the parameters of rhythmic walking to generate purposive humanoid motions. The controller consists of the two layers: rhythmic walking is...
Following Tesauro’s work on TD-Gammon, we used a 4000 parameter feed-forward neural network to develop a competitive backgammon evaluation function. Play proceeds by a roll of t...
— In this paper, we present a novel approach to partitioning pattern spaces using a multiobjective genetic algorithm for identifying (near-)optimal subspaces for hierarchical lea...
We present a new approach to multiple instance learning (MIL) that is particularly effective when the positive bags are sparse (i.e. contain few positive instances). Unlike other ...