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» Random sampling and approximation of MAX-CSP problems
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ICCV
2005
IEEE
14 years 1 months ago
KALMANSAC: Robust Filtering by Consensus
We propose an algorithm to perform causal inference of the state of a dynamical model when the measurements are corrupted by outliers. While the optimal (maximumlikelihood) soluti...
Andrea Vedaldi, Hailin Jin, Paolo Favaro, Stefano ...
VLDB
2005
ACM
149views Database» more  VLDB 2005»
14 years 7 months ago
Selectivity estimators for multidimensional range queries over real attributes
Estimating the selectivity of multidimensional range queries over real valued attributes has significant applications in data exploration and database query optimization. In this p...
Dimitrios Gunopulos, George Kollios, Vassilis J. T...
SIGMOD
2001
ACM
200views Database» more  SIGMOD 2001»
14 years 7 months ago
Data Bubbles: Quality Preserving Performance Boosting for Hierarchical Clustering
In this paper, we investigate how to scale hierarchical clustering methods (such as OPTICS) to extremely large databases by utilizing data compression methods (such as BIRCH or ra...
Markus M. Breunig, Hans-Peter Kriegel, Peer Kr&oum...
ICML
2008
IEEE
14 years 8 months ago
Fast incremental proximity search in large graphs
In this paper we investigate two aspects of ranking problems on large graphs. First, we augment the deterministic pruning algorithm in Sarkar and Moore (2007) with sampling techni...
Purnamrita Sarkar, Andrew W. Moore, Amit Prakash
AAAI
2007
13 years 10 months ago
Combining Multiple Heuristics Online
We present black-box techniques for learning how to interleave the execution of multiple heuristics in order to improve average-case performance. In our model, a user is given a s...
Matthew J. Streeter, Daniel Golovin, Stephen F. Sm...