"Yamada, M.,Suzuki, T.,Kanamori, T.,Hachiya, H.,Sugiyama, M.","Relatiive density-ratio estimationfor robust distribution comparision",,"Neural Computation",,"vol. 25","no. 5","pp. 1324-1370",2013, "Kanamori,Suzuki, T.,Sugiyama, M.","Computational complexity of kernel-based density-ratio estimation:A condition number analysis",,"Machine Learning",,"vol. 90","no. 3","pp. 431-460",2013, "Suzuki, T.,Sugiyama, M.","Fast learning rate of multiple kernel learning:Trade-off between sparsity and smoothness.",,"The Annals of Statistics",,"vol. 41","no. 3","pp. 1381-1405",2013, "Suzuki, T.,& Sugiyama, M.","Sufficient dimension reduction via squared-loss mutual information estimation",,"Neural Computation",,"vol. 25","no. 3","pp. 725-758",2013, "Sugiyama, M.,Liu, S.,Du Plessis, M.C.,Yamanaka, M.,Yamada, M.,Suzuki, T.,& Kanamori, T.","Direct divergence approximationbetween probability distributions and its applications inmachine learning",,"Journal of Computing Science and Engineering",,"vol. 7","no. 2","pp. 99-111",2013, "Kanamori, T.,Suzuki, T.,Sugiyama, M.","Statistical analisis of kernel-based least-squares density-ratio estimation",,"Machine Learning",,"vol. 86","no. 3","pp. 335-367",2012,Mar. "Kanamori, T.,Suzuki, T.,Sugiyama, M.","F-divergence estimation and two-sample homogeneity test under semiparametric density-ratio models",,"IEEE Transactions on Information Theory",,"vol. 58","no. 2","pp. 708-720",2012, "Sugiyama, M.,Suzuki, T.,Kanamori, T.","Density Ratio Estimation in Machine Learning",,"Cambridge University Press,Cambridge,UK,",,,,"page 344",2012, "Sugiyama, M.,Suzuki, T.,Kanamori, T.,Du Plessis, M.C.,Liu, S.,Takeuchi, I.","Density-difference estimation","Neural Information Processing Systems(NIPS2012)","Advances in Neural Information Processing Systems 25","P.Bartlett,F.C.N.Pereira,C.J.Burges,L.Bottou,and K.Q.Weinberger",,,"pp. 692-700",2012, "Sugiyama, M.,Suzuki, T.,Kanamori, T","Density ratio matching under the Bregman divergence:A unified framework of density ratio estimation",,"Annals of the Institlute of Statistical Mathematics",,"vol. 64","no. 5","pp. 1009-1044",2012,