Song Liu

Publication Activity (10 Years)

Years Active: 2012-2023
Publications (10 Years): 12

Top Topics

Markov Networks

Transfer Learning

Density Ratio Estimation

Kullback Leibler

Top Venues

Publications

Daniel J. Williams, Song Liu
Approximate Stein Classes for Truncated Density Estimation. CoRR (2023)
Song Liu, Takafumi Kanamori, Daniel J. Williams
Estimating Density Models with Truncation Boundaries using Score Matching. J. Mach. Learn. Res. 23 (2022)
Shunya Minami, Song Liu, Stephen Wu, Kenji Fukumizu, Ryo Yoshida
A General Class of Transfer Learning Regression without Implementation Cost. AAAI (2021)
Shunya Minami, Song Liu, Stephen Wu, Kenji Fukumizu, Ryo Yoshida
A General Class of Transfer Learning Regression without Implementation Cost. CoRR (2020)
Song Liu, Takafumi Kanamori, Wittawat Jitkrittum, Yu Chen
Fisher Efficient Inference of Intractable Models. NeurIPS (2019)
Song Liu, Takafumi Kanamori
Estimating Density Models with Complex Truncation Boundaries. CoRR (2019)
Yung-Kyun Noh, Masashi Sugiyama, Song Liu, Marthinus Christoffel du Plessis, Frank Chongwoo Park, Daniel D. Lee
Bias Reduction and Metric Learning for Nearest-Neighbor Estimation of Kullback-Leibler Divergence. Neural Comput. 30 (7) (2018)
Song Liu, Wittawat Jitkrittum, Carl Henrik Ek
Model Inference with Stein Density Ratio Estimation. CoRR (2018)
Song Liu, Akiko Takeda, Taiji Suzuki, Kenji Fukumizu
Trimmed Density Ratio Estimation. NIPS (2017)
Makoto Yamada, Song Liu, Samuel Kaski
Interpreting Outliers: Localized Logistic Regression for Density Ratio Estimation. CoRR (2017)
Song Liu, Kenji Fukumizu
Estimating Posterior Ratio for Classification: Transfer Learning from Probabilistic Perspective. SDM (2016)
Song Liu, Taiji Suzuki, Masashi Sugiyama, Kenji Fukumizu
Structure Learning of Partitioned Markov Networks. ICML (2016)
Song Liu, Kenji Fukumizu
Lazy Transfer Learning. CoRR (2015)
Song Liu, Taiji Suzuki, Masashi Sugiyama
Support Consistency of Direct Sparse-Change Learning in Markov Networks. AAAI (2015)
Song Liu, John A. Quinn, Michael U. Gutmann, Taiji Suzuki, Masashi Sugiyama
Direct Learning of Sparse Changes in Markov Networks by Density Ratio Estimation. Neural Comput. 26 (6) (2014)
Yung-Kyun Noh, Masashi Sugiyama, Song Liu, Marthinus Christoffel du Plessis, Frank Chongwoo Park, Daniel D. Lee
Bias Reduction and Metric Learning for Nearest-Neighbor Estimation of Kullback-Leibler Divergence. AISTATS (2014)
Masashi Sugiyama, Takafumi Kanamori, Taiji Suzuki, Marthinus Christoffel du Plessis, Song Liu, Ichiro Takeuchi
Density-Difference Estimation. Neural Comput. 25 (10) (2013)
Song Liu, John A. Quinn, Michael U. Gutmann, Masashi Sugiyama
Direct Learning of Sparse Changes in Markov Networks by Density Ratio Estimation. ECML/PKDD (2) (2013)
Masashi Sugiyama, Song Liu, Marthinus Christoffel du Plessis, Masao Yamanaka, Makoto Yamada, Taiji Suzuki, Takafumi Kanamori
Direct Divergence Approximation between Probability Distributions and Its Applications in Machine Learning. J. Comput. Sci. Eng. 7 (2) (2013)
Song Liu, Makoto Yamada, Nigel Collier, Masashi Sugiyama
Change-point detection in time-series data by relative density-ratio estimation. Neural Networks 43 (2013)
Masashi Sugiyama, Takafumi Kanamori, Taiji Suzuki, Marthinus Christoffel du Plessis, Song Liu, Ichiro Takeuchi
Density-Difference Estimation CoRR (2012)
Masashi Sugiyama, Takafumi Kanamori, Taiji Suzuki, Marthinus Christoffel du Plessis, Song Liu, Ichiro Takeuchi
Density-Difference Estimation. NIPS (2012)
Song Liu, Makoto Yamada, Nigel Collier, Masashi Sugiyama
Change-Point Detection in Time-Series Data by Relative Density-Ratio Estimation CoRR (2012)
Song Liu, Makoto Yamada, Nigel Collier, Masashi Sugiyama
Change-Point Detection in Time-Series Data by Relative Density-Ratio Estimation. SSPR/SPR (2012)