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ICASSP
2011
IEEE
14 years 10 months ago
Worst-case based robust adaptive beamforming for general-rank signal models using positive semi-definite covariance constraint
In this paper, we develop a new approach to the robust beamforming for general-rank signal models. Our method is based on the worst-case performance optimization using a semi-de n...
Haihua Chen, Alex B. Gershman
OL
2011
217views Neural Networks» more  OL 2011»
15 years 1 months ago
Privacy-preserving linear programming
Abstract. We propose a privacy-preserving formulation of a linear program whose constraint matrix is partitioned into groups of columns where each group of columns and its correspo...
O. L. Mangasarian
VL
2002
IEEE
110views Visual Languages» more  VL 2002»
15 years 11 months ago
Empirical Evidence that Algorithm Animation Promotes Understanding of Distributed Algorithms
Previous studies of program visualization have generally failed to provide convincing support for the benefits of algorithm animation in promoting the understanding of computatio...
Mihail Eduard Tudoreanu, Rong Wu, Ashley Hamilton-...
SSPR
2004
Springer
16 years 3 days ago
Learning from General Label Constraints
Most machine learning algorithms are designed either for supervised or for unsupervised learning, notably classification and clustering. Practical problems in bioinformatics and i...
Tijl De Bie, Johan A. K. Suykens, Bart De Moor
AAAI
2007
15 years 9 months ago
Propagating Knapsack Constraints in Sublinear Time
We develop an efficient incremental version of an existing cost-based filtering algorithm for the knapsack constraint. On a universe of n elements, m invocations of the algorith...
Irit Katriel, Meinolf Sellmann, Eli Upfal, Pascal ...