机译:基于非凸罚分的低秩表示和稀疏回归用于eQTL映射
Institute of Machine Learning and Systems Biology, School of Electronics and Information Engineering, Tongji University, Shanghai, China;
Institute of Machine Learning and Systems Biology, School of Electronics and Information Engineering, Tongji University, Shanghai, China;
Institute of Machine Learning and Systems Biology, School of Electronics and Information Engineering, Tongji University, Shanghai, China;
Institute of Machine Learning and Systems Biology, School of Electronics and Information Engineering, Tongji University, Shanghai, China;
School of Information and Computer, Anhui Agricultural University, Hefei, Anhui, China;
Institute of Machine Learning and Systems Biology, School of Electronics and Information Engineering, Tongji University, Shanghai, China;
Institute of Machine Learning and Systems Biology, School of Electronics and Information Engineering, Tongji University, Shanghai, China;
Gene expression; Sparse matrices; Minimization; Convex functions; Optimization; Algorithm design and analysis;
机译:通过低秩表示法和稀疏回归为eQTL映射考虑非遗传因素
机译:/ 重点键入=“斜体”> q = 0.5)定期稀疏表示的图像识别分类]]>
机译:通过组稀疏表示的广义图像压缩感的非凸起的非谐波低秩最小化
机译:基于低秩和稀疏表示的峰值排序
机译:基于稀疏和低秩的多模式聚类和识别的方法
机译:通过e-QTL映射的低秩表示和稀疏回归考虑非遗传因素
机译:通过组稀疏表示的广义图像压缩感的非凸起的非谐波低秩最小化