Density Ratio Estimation

24 papers with code • 0 benchmarks • 0 datasets

Estimating the ratio of one density function to the other.

Most implemented papers

Sequential Density Ratio Estimation for Simultaneous Optimization of Speed and Accuracy

TaikiMiyagawa/SPRT-TANDEM ICLR 2021

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

JohnYKiyo/density_ratio_estimation 15 Dec 2009

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

anewgithubname/change_detection 2 Mar 2012

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

Trimmed Density Ratio Estimation

anewgithubname/Trimmed-Density-Ratio-Estimation NeurIPS 2017

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

Fisher Efficient Inference of Intractable Models

anewgithubname/Stein-Density-Ratio-Estimation NeurIPS 2019

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

UBCDingXin/DDRE_Sampling_GANs 24 Sep 2019

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

HSE-LAMBDA/roerich 17 Jan 2020

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

MasaKat0/D3RE 12 Jun 2020

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

Telescoping Density-Ratio Estimation

benrhodes26/tre_code NeurIPS 2020

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

BORE: Bayesian Optimization by Density-Ratio Estimation

ltiao/bore 17 Feb 2021

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