Moscow Institute of Physics and Technology, Dorodnicyn Computing Centre of RAS, National Research University Higher School of Economics, Moscow, Russia;
National Research University Higher School of Economics, Moscow, Russia;
Moscow Institute of Physics and Technology, Moscow, Russia;
Probabilistic topic modeling; Regularization; Probabilistic latent sematic analysis; Topic selection; EM-algorithm;
机译:终身主题建模的亲和力正则非负矩阵分解
机译:马尔可夫随机游动结构近似和稀疏正则化的局部加权嵌入主题建模
机译:主题模型的可加正则化
机译:主题选择和稀疏因子的主题模型的添加性正常化
机译:正则化单一索引模型中的主题。
机译:稀疏图正规化非负矩阵分解基于Huber损失模型的癌症数据分析
机译:概率主题建模教程:随机矩阵分解的加法正则化