Clustering time-series data poses problems, which do not exist in traditional clustering in Euclidean space. Specifically, cluster prototype needs to be calculated, where common s...
We introduce two new index structures based on the q-gram index. The new structures index substrings of variable length instead of q-grams of fixed length. For both of the new ind...
In this paper, we study the metrics of negative type, which are metrics (V, d) such that d is an Euclidean metric; these metrics are thus also known as " 2-squared" met...
Approximate Nearest Neighbor (ANN) methods such as Locality Sensitive Hashing, Semantic Hashing, and Spectral Hashing, provide computationally ecient procedures for nding objects...
We present metric?? , a provably near-optimal algorithm for reinforcement learning in Markov decision processes in which there is a natural metric on the state space that allows t...