Stochastic Approximation Algorithms

By Shalabh Bhatnagar, H. Prasad, L. A. Prashanth. 2013

17 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics, Statistics and Probability

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. David M. Blei
2. Alp Kucukelbir
3. Jon D. McAuliffe
4. Stephan Mandt
5. Rajesh Ranganath
6. Michael I. Jordan
7. Dustin Tran
8. Matthew D. Hoffman

In Computational Theory and Mathematics

1. David M. Blei
2. Alp Kucukelbir
3. Jon D. McAuliffe

In Statistics and Probability

1. Alp Kucukelbir
2. Jon D. McAuliffe
3. David M. Blei
4. Rajesh Ranganath
5. Qiang Liu
6. Stephan Mandt
7. Michalis K. Titsias
8. Dustin Tran

Citations in the corpus

• Variational Inference: A Review for Statisticians (2016, methodology): “Because it rests on optimization, variational inference easily takes advantage of methods like stochastic optimization (Robbins and Monro 1951; Kushner and Yin 1997) and distributed optimization.”