Fast maximum a-posteriori inference on Monte Carlo state spaces
نویسندگان
چکیده
Dual-tree method Assume: K(·) parameterized by a distance function: K(x, y) = K (δ(x, y)). Main idea: build a spatial access tree on the source and target points, and use this to bound the value of the maximum influence and prune candidate nodes which cannot contain a particle that exceeds this bound. The bound tightens as we expand the tree, allowing more nodes to be pruned and leaving but a few to check at the end. Point-node comparison example (left):
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