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文件名称:multi-task_lasso

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    2013-05-05
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MMT is a Matlab toolbox implementing the multi-task Lasso models, including: (i) the Lasso (ii) the standard multi-task Lasso, i.e. the group Lasso (iii) the structured input-output multi-task Lasso, a.k.a. the two-graph guided multi-task Lasso proposed in [1]. The last case (iii) subsumes the special cases: tree-guided and the feature-graph guided multi-task Lasso. The core optimization algorithm for solving this model is developed in C to enhance greater computational efficiency. In particular, current scalability of the coefficient matrix that has been tested for MMT is 104*104! The structured input-output multi-task Lasso model is well-suited for addressing the expression quantitative trait loci (eQTL) mapping problems which are of the intrinsic high-dimensional nature. Details can be found in [1].-MMT is a Matlab toolbox implementing the multi-task Lasso models, including: (i) the Lasso (ii) the standard multi-task Lasso, i.e. the group Lasso (iii) the structured input-output multi-task Lasso, a.k.a. the two-graph guided multi-task Lasso proposed in [1]. The last case (iii) subsumes the special cases: tree-guided and the feature-graph guided multi-task Lasso. The core optimization algorithm for solving this model is developed in C to enhance greater computational efficiency. In particular, current scalability of the coefficient matrix that has been tested for MMT is 104*104! The structured input-output multi-task Lasso model is well-suited for addressing the expression quantitative trait loci (eQTL) mapping problems which are of the intrinsic high-dimensional nature. Details can be found in [1].
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multi-task_lasso/mmt_user_manual.pdf
multi-task_lasso/mmt_v0.12.zip
multi-task_lasso/multi-task_lasso.htm
multi-task_lasso/multi-task_lasso.html
multi-task_lasso/緾=D;O=A.html
multi-task_lasso/緾=D;O=D.html
multi-task_lasso/緾=M;O=A.html
multi-task_lasso/緾=M;O=D.html
multi-task_lasso/緾=N;O=A.html
multi-task_lasso/緾=N;O=D.html
multi-task_lasso/緾=S;O=A.html
multi-task_lasso/緾=S;O=D.html
multi-task_lasso

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