A Review on Optimal Subsampling Methods for Massive Datasets
- Computer Science, MathematicsJournal of Data Science
The optimal subsampling methods have been investigated to include logistic regression models, softmax regression model, generalized linear models, quantile regression Models, and quasi-likelihood estimation.
Maximum sampled conditional likelihood for informative subsampling
The asymptotic normality of the MSCLE is established and it is proved that its asymPTotic variance covariance matrix is the smallest among a class of asymptonically unbiased estimators, including the inverse probability weighted estimator.
SHOWING 1-10 OF 43 REFERENCES
A Space-Efficient Recursive Procedure for Estimating a Quantile of an Unknown Distribution
Consider the problem of computing an estimate of a percentile or quantile of an unknown population based on a random sample of n observations. By viewing this problem as a problem in stochastic…
Optimal design with bounded density: optimization algorithms of the exchange type
- Computer Science
Bayesian Estimation and Experimental Design in Linear Regression Models, volume 55. Teubner-Texte zur Mathematik, Leipzig
Analysis of recursive stochastic algorithms
- Computer Science, Mathematics
It is shown how a deterministic differential equation can be associated with the algorithm and examples of applications of the results to problems in identification and adaptive control.
Finite Sample Analysis of Two-Timescale Stochastic Approximation with Applications to Reinforcement Learning
- Mathematics, Computer ScienceCOLT
This work develops a novel recipe for their finite sample analysis, and provides a concentration bound, which is the first such result for a two-timescale SA, and introduces a new projection scheme, in which the time between successive projections increases exponentially.
Theory and Practice of Recursive Identification
- Computer Science
Methods of recursive identification deal with the problem of building mathematical models of signals and systems on-line, at the same time as data is being collected. Such methods, which are also k…
Theory and Practice of Recursive Identi cation
Information-Based Optimal Subdata Selection for Big Data Linear Regression
- Computer ScienceJournal of the American Statistical Association
Theoretical results and extensive simulations demonstrate that the IBOSS approach is superior to subsampling-based methods, sometimes by orders of magnitude, and the advantages of the new approach are also illustrated through analysis of real data.