Song Liu

According to our database, Song Liu authored at least 18 papers between 2013 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

Approximate Stein Classes for Truncated Density Estimation.

Daniel J. Williams, Song Liu

Proceedings of the International Conference on Machine Learning, 2023

2022

Estimating Density Models with Truncation Boundaries using Score Matching.

Song Liu, Takafumi Kanamori, Daniel J. Williams

J. Mach. Learn. Res., 2022

2021

A General Class of Transfer Learning Regression without Implementation Cost.

Shunya Minami, Song Liu, Stephen Wu, Kenji Fukumizu, Ryo Yoshida

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2019

Estimating Density Models with Complex Truncation Boundaries.

Song Liu, Takafumi Kanamori

CoRR, 2019

Fisher Efficient Inference of Intractable Models.

Song Liu, Takafumi Kanamori, Wittawat Jitkrittum, Yu Chen

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

Bias Reduction and Metric Learning for Nearest-Neighbor Estimation of Kullback-Leibler Divergence.

Yung-Kyun Noh, Masashi Sugiyama, Song Liu, Marthinus Christoffel du Plessis, Frank Chongwoo Park, Daniel D. Lee

Neural Comput., 2018

Model Inference with Stein Density Ratio Estimation.

Song Liu, Wittawat Jitkrittum, Carl Henrik Ek

CoRR, 2018

2017

Interpreting Outliers: Localized Logistic Regression for Density Ratio Estimation.

Makoto Yamada, Song Liu, Samuel Kaski

CoRR, 2017

Trimmed Density Ratio Estimation.

Song Liu, Akiko Takeda, Taiji Suzuki, Kenji Fukumizu

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016

Estimating Posterior Ratio for Classification: Transfer Learning from Probabilistic Perspective.

Song Liu, Kenji Fukumizu

Proceedings of the 2016 SIAM International Conference on Data Mining, 2016

Structure Learning of Partitioned Markov Networks.

Song Liu, Taiji Suzuki, Masashi Sugiyama, Kenji Fukumizu

Proceedings of the 33nd International Conference on Machine Learning, 2016

2015

Lazy Transfer Learning.

Song Liu, Kenji Fukumizu

CoRR, 2015

Support Consistency of Direct Sparse-Change Learning in Markov Networks.

Song Liu, Taiji Suzuki, Masashi Sugiyama

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014

Direct Learning of Sparse Changes in Markov Networks by Density Ratio Estimation.

Song Liu, John A. Quinn, Michael U. Gutmann, Taiji Suzuki, Masashi Sugiyama

Neural Comput., 2014

2013

Change-point detection in time-series data by relative density-ratio estimation.

Song Liu, Makoto Yamada, Nigel Collier, Masashi Sugiyama

Neural Networks, 2013

Density-Difference Estimation.

Masashi Sugiyama, Takafumi Kanamori, Taiji Suzuki, Marthinus Christoffel du Plessis, Song Liu, Ichiro Takeuchi

Neural Comput., 2013

Direct Divergence Approximation between Probability Distributions and Its Applications in Machine Learning.

Masashi Sugiyama, Song Liu, Marthinus Christoffel du Plessis, Masao Yamanaka, Makoto Yamada, Taiji Suzuki, Takafumi Kanamori

J. Comput. Sci. Eng., 2013

Direct Learning of Sparse Changes in Markov Networks by Density Ratio Estimation.

Song Liu, John A. Quinn, Michael U. Gutmann, Masashi Sugiyama

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013