b'Song Liu'

research

∙ 06/29/2022

Score Matching for Truncated Density Estimation on a Manifold

When observations are truncated, we are limited to an incomplete picture...

Daniel J. Williams, et al. ∙

research

∙ 10/18/2021

The f-divergence and Loss Functions in ROC Curve

Given two data distributions and a test score function, the Receiver Ope...

Song Liu, et al. ∙

research

∙ 03/28/2021

HiT: Hierarchical Transformer with Momentum Contrast for Video-Text Retrieval

Video-Text Retrieval has been a hot research topic with the explosion of...

Song Liu, et al. ∙

research

∙ 02/15/2020

Posterior Ratio Estimation for Latent Variables

Density Ratio Estimation has attracted attention from machine learning c...

Yulong Zhang, et al. ∙

research

∙ 01/20/2020

Model Reuse with Reduced Kernel Mean Embedding Specification

Given a publicly available pool of machine learning models constructed f...

Xi-Zhu Wu, et al. ∙

research

∙ 10/09/2019

Estimating Density Models with Complex Truncation Boundaries

Truncated densities are probability density functions defined on truncat...

Song Liu, et al. ∙

research

∙ 05/01/2019

Two-sample inference for high-dimensional Markov networks

Markov networks are frequently used in sciences to represent conditional...

Byol Kim, et al. ∙

research

∙ 01/28/2019

Personalized Dialogue Generation with Diversified Traits

Endowing a dialogue system with particular personality traits is essenti...

Yinhe Zheng, et al. ∙

research

∙ 05/18/2018

Model Inference with Stein Density Ratio Estimation

The Kullback-Leilber divergence from model to data is a classic goodness...

Song Liu, et al. ∙

research

∙ 09/04/2017

The electromagnetic waves propagation in unmagnetized plasma media using parallelized finite-difference time-domain method

The finite-difference time-domain (FDTD) method has been commonly utiliz...

Lang-lang Xiong, et al. ∙

research

∙ 09/04/2017

GPU-Accelerated Parallel Finite-Difference Time-Domain Method for Electromagnetic Waves Propagation in Unmagnetized Plasma Media

The finite-difference time-domain (FDTD) method has been commonly utiliz...

Xi-min Wang, et al. ∙

research

∙ 03/09/2017

Trimmed Density Ratio Estimation

Density ratio estimation is a vital tool in both machine learning and st...

Song Liu, et al. ∙

research

∙ 02/21/2017

Interpreting Outliers: Localized Logistic Regression for Density Ratio Estimation

We propose an inlier-based outlier detection method capable of both iden...

Makoto Yamada, et al. ∙

research

∙ 01/07/2017

Large-scale Isolated Gesture Recognition Using Convolutional Neural Networks

This paper proposes three simple, compact yet effective representations ...

Pichao Wang, et al. ∙

research

∙ 01/06/2017

Learning Sparse Structural Changes in High-dimensional Markov Networks: A Review on Methodologies and Theories

Recent years have seen an increasing popularity of learning the sparse c...

Song Liu, et al. ∙

research

∙ 08/22/2016

Large-scale Continuous Gesture Recognition Using Convolutional Neural Networks

This paper addresses the problem of continuous gesture recognition from ...

Pichao Wang, et al. ∙

research

∙ 02/22/2016

Planogram Compliance Checking Based on Detection of Recurring Patterns

In this paper, a novel method for automatic planogram compliance checkin...

Song Liu, et al. ∙

research

∙ 02/22/2016

Creating Simplified 3D Models with High Quality Textures

This paper presents an extension to the KinectFusion algorithm which all...

Song Liu, et al. ∙

research

∙ 06/09/2015

Estimating Posterior Ratio for Classification: Transfer Learning from Probabilistic Perspective

Transfer learning assumes classifiers of similar tasks share certain par...

Song Liu, et al. ∙

research

∙ 04/02/2015

Structure Learning of Partitioned Markov Networks

We learn the structure of a Markov Network between two groups of random ...

Song Liu, et al. ∙

research

∙ 07/02/2014

Support Consistency of Direct Sparse-Change Learning in Markov Networks

We study the problem of learning sparse structure changes between two Ma...

Song Liu, et al. ∙

research

∙ 04/25/2013

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

We propose a new method for detecting changes in Markov network structur...

Song Liu, et al. ∙

research

∙ 06/30/2012

Density-Difference Estimation

We address the problem of estimating the difference between two probabil...

Masashi Sugiyama, et al. ∙

research

∙ 03/02/2012

Change-Point Detection in Time-Series Data by Relative Density-Ratio Estimation

The objective of change-point detection is to discover abrupt property c...

Song Liu, et al. ∙

Song Liu

Featured Co-authors

Masashi Sugiyama

Samuel Kaski

Minlie Huang

Taiji Suzuki

Zhi-Hua Zhou

Ichiro Takeuchi

Mladen Kolar

Makoto Yamada

Kenji Fukumizu

Wanqing Li

Nigel Collier

Score Matching for Truncated Density Estimation on a Manifold

The f-divergence and Loss Functions in ROC Curve

HiT: Hierarchical Transformer with Momentum Contrast for Video-Text Retrieval

Posterior Ratio Estimation for Latent Variables

Model Reuse with Reduced Kernel Mean Embedding Specification

Estimating Density Models with Complex Truncation Boundaries

Two-sample inference for high-dimensional Markov networks

Personalized Dialogue Generation with Diversified Traits

Model Inference with Stein Density Ratio Estimation

The electromagnetic waves propagation in unmagnetized plasma media using parallelized finite-difference time-domain method

GPU-Accelerated Parallel Finite-Difference Time-Domain Method for Electromagnetic Waves Propagation in Unmagnetized Plasma Media

Trimmed Density Ratio Estimation

Interpreting Outliers: Localized Logistic Regression for Density Ratio Estimation

Large-scale Isolated Gesture Recognition Using Convolutional Neural Networks

Learning Sparse Structural Changes in High-dimensional Markov Networks: A Review on Methodologies and Theories

Large-scale Continuous Gesture Recognition Using Convolutional Neural Networks

Planogram Compliance Checking Based on Detection of Recurring Patterns

Creating Simplified 3D Models with High Quality Textures

Estimating Posterior Ratio for Classification: Transfer Learning from Probabilistic Perspective

Structure Learning of Partitioned Markov Networks

Support Consistency of Direct Sparse-Change Learning in Markov Networks

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

Density-Difference Estimation

Change-Point Detection in Time-Series Data by Relative Density-Ratio Estimation