We describe fully retroactive dynamic data structures for approximate range report-ing and approximate nearest neighbor reporting. We show how to maintain, for any positive constant d, a set of n points in Rd indexed by time such that we can perform insertions or deletions at any point in the timeline in O(log n) amortized time. We support, for any small constant > 0, (1 + )-approximate range reporting queries at any point in the timeline in O(log n+k) time, where k is the output size. We also show how to answer (1 + )-approximate nearest neighbor queries for any point in the past or present in O(log n) time.
We present an insertion-only data structure that supports k-nearest neighbors queries for a set of n...
Given a set of n points in d-dimensional Euclidean space, S ⊂ E d, and a query point q ∈ E d, we wis...
For any epsilon in (0,1), a (1+epsilon)-approximate range mode query asks for the position of an ele...
Let $S$ be a set of $n$ points in $\IR^{D}$. It is shown that a range tree can be used to find an $L...
. Let S be a set of n points in IR D . It is shown that a range tree can be used to find an L1-neare...
Consider a set S of n data points in real d-dimensional space, R d , where distances are measured ...
We describe a dynamic data structure for approximate nearest neighbor (ANN) queries with respect to ...
Nearest neighbor searching is the problem of preprocessing a set of n point points in d-dimensional ...
Consider a set S of n data points in real d-dimensional space, R-d, where distances are measured usi...
Given an initial rectangular range or k nearest neighbor (k-nn) query (using the L1 metric) , we con...
AbstractGiven an initial rectangular range or k nearest neighbor (k-nn) query (using the L∞ metric),...
Abstract Several types of nearest neighbor (NN) search have been proposed and studied in the context...
The nearest neighbor problem is the following: Given a set of n points P = fp1�:::�p ng in some metr...
Nearest-neighbor search is a very natural and universal problem in computer science. Often times, th...
We present space-time tradeoffs for approximate spherical range counting queries. Given a set S of n...
We present an insertion-only data structure that supports k-nearest neighbors queries for a set of n...
Given a set of n points in d-dimensional Euclidean space, S ⊂ E d, and a query point q ∈ E d, we wis...
For any epsilon in (0,1), a (1+epsilon)-approximate range mode query asks for the position of an ele...
Let $S$ be a set of $n$ points in $\IR^{D}$. It is shown that a range tree can be used to find an $L...
. Let S be a set of n points in IR D . It is shown that a range tree can be used to find an L1-neare...
Consider a set S of n data points in real d-dimensional space, R d , where distances are measured ...
We describe a dynamic data structure for approximate nearest neighbor (ANN) queries with respect to ...
Nearest neighbor searching is the problem of preprocessing a set of n point points in d-dimensional ...
Consider a set S of n data points in real d-dimensional space, R-d, where distances are measured usi...
Given an initial rectangular range or k nearest neighbor (k-nn) query (using the L1 metric) , we con...
AbstractGiven an initial rectangular range or k nearest neighbor (k-nn) query (using the L∞ metric),...
Abstract Several types of nearest neighbor (NN) search have been proposed and studied in the context...
The nearest neighbor problem is the following: Given a set of n points P = fp1�:::�p ng in some metr...
Nearest-neighbor search is a very natural and universal problem in computer science. Often times, th...
We present space-time tradeoffs for approximate spherical range counting queries. Given a set S of n...
We present an insertion-only data structure that supports k-nearest neighbors queries for a set of n...
Given a set of n points in d-dimensional Euclidean space, S ⊂ E d, and a query point q ∈ E d, we wis...
For any epsilon in (0,1), a (1+epsilon)-approximate range mode query asks for the position of an ele...