Skip to search form
Skip to main content
Skip to account menu
Semantic Scholar
Semantic Scholar's Logo
Search 234,974,876 papers from all fields of science
Search
Sign In
Create Free Account
Variance reduction
Known as:
Reduction
In mathematics, more specifically in the theory of Monte Carlo methods, variance reduction is a procedure used to increase the precision of the…
Expand
Wikipedia
(opens in a new tab)
Create Alert
Alert
Related topics
Related topics
10 relations
Antithetic variates
Control variates
Importance sampling
List of numerical analysis topics
Expand
Papers overview
Semantic Scholar uses AI to extract papers important to this topic.
2017
2017
Variance reduction via empirical variance minimization: convergence and complexity
D. Belomestny
,
L. Iosipoi
,
Nikita Zhivotovskiy
2017
Corpus ID: 88517582
In this paper we propose and study a generic variance reduction approach. The proposed method is based on minimization of the…
Expand
2016
2016
Katyusha: The First Truly Accelerated Stochastic Gradient Method
Zeyuan Allen-Zhu
2016
Corpus ID: 18961637
We introduce $\mathtt{Katyusha}$, the first direct stochastic gradient method that has an accelerated convergence rate. Given an…
Expand
2015
2015
Iterative Refinement of Approximate Posterior for Training Directed Belief Networks
R. Devon Hjelm
,
Kyunghyun Cho
,
Junyoung Chung
,
R. Salakhutdinov
,
V. Calhoun
,
N. Jojic
arXiv.org
2015
Corpus ID: 3417301
Recent advances in variational inference that make use of an inference or recognition network for training and evaluating deep…
Expand
2009
2009
Quantitative Laser Doppler Flowmetry
Ingemar Fredriksson
2009
Corpus ID: 9485546
Laser Doppler flowmetry (LDF) is virtually the only non-invasive technique, except for other laser speckle based techniques, that…
Expand
2007
2007
Ultrafast Monte Carlo for Statistical Summations
Michael P. Holmes
,
Alexander G. Gray
,
C. Isbell
Neural Information Processing Systems
2007
Corpus ID: 9399029
Machine learning contains many computational bottlenecks in the form of nested summations over datasets. Computation of these…
Expand
2003
2003
Non-Linear Variance Reduction Techniques in Biometric Authentication
N. Poh
,
Samy Bengio
2003
Corpus ID: 2701931
In this paper, several approaches that can be used to improve biometric authentication applications are proposed. The idea is…
Expand
2002
2002
Cycle to Cycle Manufacturing Process Control
D. Hardt
,
Tsz-Sin Siu
2002
Corpus ID: 15517814
Most manufacturing processes produce parts that can only be correctly measured after the process cycle has been completed. Even…
Expand
2000
2000
Three-Dimensional a Priori Model Constraints and Uncertainties for Improving Seismic Location
M. Flanagan
,
S. Myers
,
C. Schultz
,
M. Pasyanos
,
J. Bhattacharyya
2000
Corpus ID: 43599801
Abstract : Accurate seismic event location is key to monitoring the Comprehensive Nuclear-Test-Ban Treaty (CTBT) and is largely…
Expand
2000
2000
Combining Multiple Classifiers to Improve Part of Speech Tagging : A Case Study for Brazilian Portuguese
R. Aires
,
S. Aluísio
,
D. Kuhn
,
B. MarcioL.
,
Andreeta
,
O. N. Oliveira
2000
Corpus ID: 14144835
Four taggers have been trained on a 100,000-word corpus of Brazilian Portuguese, namely Unigram (Treetagger), N-gram (Treetagger…
Expand
1993
1993
Applying the EM Algorithm to Calculating ML and REML Estimates of Variance Components
S. R. Searle
1993
Corpus ID: 117166381
July 1993 Maximum likelihood (ML) is a firmly established estimation technique, and the estimation maximization (EM) algorithm…
Expand