28 citations · 43 across the 5 of their papers we have counts for
6 papers
Relative Density-Ratio Estimation for Robust Distribution Comparison
Makoto Yamada, Taiji Suzuki, Takafumi Kanamori +2
Divergence estimators based on direct approximation of density-ratios without going through separate approximation of numerator and denominator densities have been successfully app…
Fast Learning Rate of lp-MKL and its Minimax Optimality
Taiji Suzuki
In this paper, we give a new sharp generalization bound of lp-MKL which is a generalized framework of multiple kernel learning (MKL) and imposes lp-mixed-norm regularization instea…
Sharp Convergence Rate and Support Consistency of Multiple Kernel Learning with Sparse and Dense Regularization
Taiji Suzuki, Ryota Tomioka, Masashi Sugiyama
We theoretically investigate the convergence rate and support consistency (i.e., correctly identifying the subset of non-zero coefficients in the large sample limit) of multiple ke…
Fast Convergence Rate of Multiple Kernel Learning with Elastic-net Regularization
Taiji Suzuki, Ryota Tomioka, Masashi Sugiyama
We investigate the learning rate of multiple kernel leaning (MKL) with elastic-net regularization, which consists of an -regularizer for inducing the sparsity and an $\ell_…
Regularization Strategies and Empirical Bayesian Learning for MKL
Ryota Tomioka, Taiji Suzuki
Multiple kernel learning (MKL), structured sparsity, and multi-task learning have recently received considerable attention. In this paper, we show how different MKL algorithms can…
Game theoretic derivation of discrete distributions and discrete pricing formulas
Akimichi Takemura, Taiji Suzuki
In this expository paper we illustrate the generality of game theoretic probability protocols of Shafer and Vovk (2001) in finite-horizon discrete games. By restricting ourselves t…