# Density Ratio Estimation

24 papers with code • 0 benchmarks • 0 datasets

Estimating the ratio of one density function to the other.

## Benchmarks

These leaderboards are used to track progress in Density Ratio Estimation
## Most implemented papers

# Sequential Density Ratio Estimation for Simultaneous Optimization of Speed and Accuracy

Classifying sequential data as early and as accurately as possible is a challenging yet critical problem, especially when a sampling cost is high.

# Condition Number Analysis of Kernel-based Density Ratio Estimation

We show that the kernel least-squares method has a smaller condition number than a version of kernel mean matching and other M-estimators, implying that the kernel least-squares method has preferable numerical properties.

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

The objective of change-point detection is to discover abrupt property changes lying behind time-series data.

# Trimmed Density Ratio Estimation

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

# Fisher Efficient Inference of Intractable Models

For example, the asymptotic variance of MLE solution attains equality of the asymptotic Cram{\'e}r-Rao lower bound (efficiency bound), which is the minimum possible variance for an unbiased estimator.

# Subsampling Generative Adversarial Networks: Density Ratio Estimation in Feature Space with Softplus Loss

Our subsampling methods do not rely on the optimality of the discriminator and are suitable for all types of GANs.

# Generalization of Change-Point Detection in Time Series Data Based on Direct Density Ratio Estimation

The goal of the change-point detection is to discover changes of time series distribution.

# Non-Negative Bregman Divergence Minimization for Deep Direct Density Ratio Estimation

Density ratio estimation (DRE) is at the core of various machine learning tasks such as anomaly detection and domain adaptation.

# Telescoping Density-Ratio Estimation

Density-ratio estimation via classification is a cornerstone of unsupervised learning.

# BORE: Bayesian Optimization by Density-Ratio Estimation

Bayesian optimization (BO) is among the most effective and widely-used blackbox optimization methods.