Author: Kshirsagar, Meghana; Carbonell, Jaime; Klein-Seetharaman, Judith
Title: Multitask learning for host–pathogen protein interactions Document date: 2013_7_1
ID: sdgt2ms5_40
Snippet: Yuille and Rangarajan (2003) show that such a CCCP-based algorithm is guaranteed to decrease the objective function at every iteration and to converge to a local minimum or saddle point. We observe a similar behavior in our experiments. Computationally, this algorithm is efficient Fig. 3 . The exponential function e z=C for different values of C i220 because the regularizer works on a subset of the data-only the positive examples, which are a sma.....
Document: Yuille and Rangarajan (2003) show that such a CCCP-based algorithm is guaranteed to decrease the objective function at every iteration and to converge to a local minimum or saddle point. We observe a similar behavior in our experiments. Computationally, this algorithm is efficient Fig. 3 . The exponential function e z=C for different values of C i220 because the regularizer works on a subset of the data-only the positive examples, which are a small fraction of the complete training data.
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