20 citations · 49 across the 13 of their papers we have counts for
4 papers · 1 filter
Unified Perspective on Probability Divergence via Maximum Likelihood Density Ratio Estimation: Bridging KL-Divergence and Integral Probability Metrics
Masahiro Kato, Masaaki Imaizumi, Kentaro Minami
This paper provides a unified perspective for the Kullback-Leibler (KL)-divergence and the integral probability metrics (IPMs) from the perspective of maximum likelihood density-ra…
Theoretically Motivated Data Augmentation and Regularization for Portfolio Construction
Liu Ziyin, Kentaro Minami, Kentaro Imajo
The task we consider is portfolio construction in a speculative market, a fundamental problem in modern finance. While various empirical works now exist to explore deep learning in…
The equivalence between Stein variational gradient descent and black-box variational inference
Casey Chu, Kentaro Minami, Kenji Fukumizu
We formalize an equivalence between two popular methods for Bayesian inference: Stein variational gradient descent (SVGD) and black-box variational inference (BBVI). In particular,…
Smoothness and Stability in GANs
Casey Chu, Kentaro Minami, Kenji Fukumizu
Generative adversarial networks, or GANs, commonly display unstable behavior during training. In this work, we develop a principled theoretical framework for understanding the stab…