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STOC
2010
ACM
244views Algorithms» more  STOC 2010»
16 years 3 months ago
Improving Exhaustive Search Implies Superpolynomial Lower Bounds
The P vs NP problem arose from the question of whether exhaustive search is necessary for problems with short verifiable solutions. We do not know if even a slight algorithmic imp...
Ryan Williams
TIP
2002
116views more  TIP 2002»
15 years 6 months ago
Adaptive approximate nearest neighbor search for fractal image compression
Fractal image encoding is a computationally intensive method of compression due to its need to find the best match between image sub-blocks by repeatedly searching a large virtual...
Chong Sze Tong, Man Wong
ICML
1994
IEEE
15 years 10 months ago
Prototype and Feature Selection by Sampling and Random Mutation Hill Climbing Algorithms
With the goal of reducing computational costs without sacrificing accuracy, we describe two algorithms to find sets of prototypes for nearest neighbor classification. Here, the te...
David B. Skalak
STOC
2002
ACM
177views Algorithms» more  STOC 2002»
16 years 6 months ago
Similarity estimation techniques from rounding algorithms
A locality sensitive hashing scheme is a distribution on a family F of hash functions operating on a collection of objects, such that for two objects x, y, PrhF [h(x) = h(y)] = si...
Moses Charikar
GECCO
2004
Springer
131views Optimization» more  GECCO 2004»
15 years 11 months ago
PolyEDA: Combining Estimation of Distribution Algorithms and Linear Inequality Constraints
Estimation of distribution algorithms (EDAs) are population-based heuristic search methods that use probabilistic models of good solutions to guide their search. When applied to co...
Jörn Grahl, Franz Rothlauf