Incremental 2-D Nearest-Point Search with Evenly Populated Strips

An Incremental Nearest Neighbor Algorithm with Queries

We consider the general problem of learning multi-category classification from labeled examples. We present experimental results for a nearest neighbor algorithm which actively selects samples from different pattern classes according to a querying rule instead of the a priori class probabilities. The amount of improvement of this query-based approach over the passive batch approach depends on t...

Excluded Middle Vantage Point Forests for Nearest Neighbor Search

K-Nearest Neighbor Search for Moving Query Point

This paper addresses the problem of finding k nearest neighbors for moving query point (we call it k-NNMP). It is an important issue in both mobile computing research and real-life applications. The problem assumes that the query point is not static, as in k-nearest neighbor problem, but varies its position over time. In this paper, four different methods are proposed for solving the problem. D...

Fast Approximate Nearest-Neighbor Search with k-Nearest Neighbor Graph

We introduce a new nearest neighbor search algorithm. The algorithm builds a nearest neighbor graph in an offline phase and when queried with a new point, performs hill-climbing starting from a randomly sampled node of the graph. We provide theoretical guarantees for the accuracy and the computational complexity and empirically show the effectiveness of this algorithm.

Graph Search and Strips Planning

AI is founded upon that belief that intelligence is based on computation. It seems likely that a deep understanding of computation will prove useful in the investigation of intelligence. In any computational process eeciency is desirable. This chapter continues the investigation of techniques for improving the eeciency of computations that search. The theory of computation provides a framework ...