Vector Quantization is useful for data compression. Competitive Learning which minimizes reconstruction error is an appropriate algorithm for vector quantization of unlabelled dat...
This paper describes the adaption and application of an algorithm called Feudal Reinforcement Learning to a complex gridworld navigation problem. The algorithm proved to be not ea...
We present a new algorithm for topological feature mapping. It is compared to other known feature mapping algorithmslike that proposed by Kohonen or Bertsch. The main difference t...
A new high speed word matching algorithm for handwritten Chinese character recomition is presented. Acontinuous string without delimiting space is recognized in real time by using...
The real di culty in development of practical NLP systems comes from the fact that we do not have e ective means for gathering \knowledge". In this paper, we propose an algor...
Satoshi Sekine, Jeremy J. Carroll, Sophia Ananiado...
An algorithm is proposed to determine antecedents for VP ellipsis. The algorithm eliminates impossible antecedents, and then imposes a preference ordering on possible antecedents....
We present an algorithm for the generation of sentences from the semantic representations of Unification Categorial Grammar. We discuss a variant of Shieber's semantic monoto...
Given a convex polygon P with m vertices and a set S of n points in the plane, we consider the problem of nding a placement of P that contains the maximum number of points in S. W...
We describe a new technique that can be used to derandomize a number of randomized algorithms for routing and sorting on meshes. We demonstrate the power of this technique by deri...
We present a new algorithm that can be used for solving the model−checking problem for linear−time temporal logic. This algorithm can be viewed as the combination of two exist...