Add to ORKGAbstract: While k-d trees have been widely studied and used, their theoretical advantages are often not realized due to ineffective search strategies and generally poor performance in high dimensional spaces. In this paper we outline an effective search algorithm for k-d trees that combines an optimal depth-first branch and bound (DFBB) strategy with a unique method for path ordering and pruning. Our initial method was developed for improving nearest neighbor (NN) search, but has also proven effective for k-NN search and approximate k-NN classification
We propose a simple variant of kd-trees, called rank-based kd-trees, for sets of points in Rd. We sh...
We propose a simple variant of kd-trees, called rank-based kd-trees, for sets of points in Rd. We sh...
International audienceWe present a progressive algorithm for approximate k-nearest neighbor search. ...
Affordable, fast computers with large memories have lessened the demand for program efficiency, but ...
Nearest neighbor search is a basic primitive method used for machine learning and information retrie...
Nearest neighbor search is a basic primitive method used for machine learning and information retrie...
We consider the task of nearest-neighbor search with the class of binary-space-partitioning trees, w...
We consider the task of nearest-neighbor search with the class of binary-space-partitioning trees, w...
Tree search is a common technique for solving constraint satisfaction and combinatorial optimization...
A simplified k nearest neighbour (knn) search for the R-tree family is proposed in this paper. This ...
Searching is one of the most fundamental operations in many complex systems. However, the complexity...
[[abstract]]The problem of k-nearest neighbors (kNN) is to find the nearest k neighbors for a query ...
Best-first search (BFS) expands the fewest nodes among all admissible algorithms us-ing the same cos...
We propose a simple variant of kd-trees, called rank-based kd-trees, for sets of points in Rd. We sh...
We propose a simple variant of kd-trees, called rank-based kd-trees, for sets of points in Rd. We sh...
We propose a simple variant of kd-trees, called rank-based kd-trees, for sets of points in Rd. We sh...
We propose a simple variant of kd-trees, called rank-based kd-trees, for sets of points in Rd. We sh...
International audienceWe present a progressive algorithm for approximate k-nearest neighbor search. ...
Affordable, fast computers with large memories have lessened the demand for program efficiency, but ...
Nearest neighbor search is a basic primitive method used for machine learning and information retrie...
Nearest neighbor search is a basic primitive method used for machine learning and information retrie...
We consider the task of nearest-neighbor search with the class of binary-space-partitioning trees, w...
We consider the task of nearest-neighbor search with the class of binary-space-partitioning trees, w...
Tree search is a common technique for solving constraint satisfaction and combinatorial optimization...
A simplified k nearest neighbour (knn) search for the R-tree family is proposed in this paper. This ...
Searching is one of the most fundamental operations in many complex systems. However, the complexity...
[[abstract]]The problem of k-nearest neighbors (kNN) is to find the nearest k neighbors for a query ...
Best-first search (BFS) expands the fewest nodes among all admissible algorithms us-ing the same cos...
We propose a simple variant of kd-trees, called rank-based kd-trees, for sets of points in Rd. We sh...
We propose a simple variant of kd-trees, called rank-based kd-trees, for sets of points in Rd. We sh...
We propose a simple variant of kd-trees, called rank-based kd-trees, for sets of points in Rd. We sh...
We propose a simple variant of kd-trees, called rank-based kd-trees, for sets of points in Rd. We sh...
International audienceWe present a progressive algorithm for approximate k-nearest neighbor search. ...