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Squeezing the Arimoto-Blahut algorithm for faster convergence

Squeezing the Arimoto-Blahut algorithm for faster convergence

21 June 2009
Yaming Yu
ArXiv (abs)PDFHTML

Papers citing "Squeezing the Arimoto-Blahut algorithm for faster convergence"

4 / 4 papers shown
Title
The Value of Information When Deciding What to Learn
The Value of Information When Deciding What to Learn
Dilip Arumugam
Benjamin Van Roy
70
12
0
26 Oct 2021
Deciding What to Learn: A Rate-Distortion Approach
Deciding What to Learn: A Rate-Distortion Approach
Dilip Arumugam
Benjamin Van Roy
66
24
0
15 Jan 2021
Improved EM for Mixture Proportions with Applications to Nonparametric
  ML Estimation for Censored Data
Improved EM for Mixture Proportions with Applications to Nonparametric ML Estimation for Censored Data
Yaming Yu
68
3
0
18 Feb 2010
Strict Monotonicity and Convergence Rate of Titterington's Algorithm for
  Computing D-optimal Designs
Strict Monotonicity and Convergence Rate of Titterington's Algorithm for Computing D-optimal Designs
Yaming Yu
121
18
0
21 Jan 2010
1