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CIARP
2006
Springer
15 years 8 months ago
A New Approach to Multi-class Linear Dimensionality Reduction
Linear dimensionality reduction (LDR) is quite important in pattern recognition due to its efficiency and low computational complexity. In this paper, we extend the two-class Chern...
Luis Rueda, Myriam Herrera
ICALP
1999
Springer
15 years 8 months ago
New Upper Bounds for MaxSat
We describe exact algorithms that provide new upper bounds for the Maximum Satisfiability problem (MaxSat). We prove
Rolf Niedermeier, Peter Rossmanith
IJCAI
2007
15 years 5 months ago
Constructing New and Better Evaluation Measures for Machine Learning
Evaluation measures play an important role in machine learning because they are used not only to compare different learning algorithms, but also often as goals to optimize in cons...
Jin Huang, Charles X. Ling
AMC
2005
125views more  AMC 2005»
15 years 4 months ago
A new symbolic computation for formal integration with exact power series
This paper describes a new symbolic algorithm for formal integration of a class of functions in the context of exact power series by using generalized hypergeometric series and co...
Onur Kiymaz, Seref Mirasyedioglu
STOC
2006
ACM
166views Algorithms» more  STOC 2006»
16 years 4 months ago
New upper and lower bounds for randomized and quantum local search
Local Search problem, which finds a local minimum of a black-box function on a given graph, is of both practical and theoretical importance to combinatorial optimization, complexi...
Shengyu Zhang