Slides
Recently, I gave a summer course in AT&T on Nearest Neighbor Search and Other Problems in High Dimensional Computational Geometry. Here are the slides:

Lecture 1: Introduction

Lecture 2: Nearest Neighbor in Euclidean norm (JohnsonLindenstrauss Lemma, Locality Sensitive Hashing)

Lecture 3: Nearest Neighbor in l_infty norm

Lecture 4: Embeddings into l_infty (arbitrary metrics, Hausdorff metrics)

Lecture 5: Algorithmic reductions to nearest neighbor (closest pair, diameter,MST,matching); revised 7/21/99

Lecture 6: Sublinear time algorithms for general metrics (1median, MAXCUT, clustering)

Conclusions and Open Problems
I also prepared a bibliography (with links to PS files, when possible) containing all references appearing in the above slides.