Strassen Asymptotics

Strassen Asymptotics is a theoretical framework in finite blocklength information theory that characterizes the asymptotic behavior of coding performance limits by refining central limit theorem approximations with higher-order statistical terms, specifically through the use of moderate deviations and Berry-Esseen-type bounds to capture non-Gaussian effects in finite-length regimes.

24

Publications

929

Citations

31

Authors

24

Institutions

Publications per year

2017–2026

2

Authors

31

  1. KG
    Karl Grill

    Statistics Austria, Austria

    3 publications · 63 citations

    3

    h-index

  2. MC
    Miklós Csörgő

    Carleton University, Canada

    2 publications · 46 citations

    2

    h-index

  3. PR
    Pál Révész

    Hungarian Academy of Sciences, Hungary

    2 publications · 46 citations

    2

    h-index

  4. VY
    Victor Y. Pan

    Lehman College, United States

    1 publications · 79 citations

    1

    h-index

  5. MN
    Michael Neumann

    University of Connecticut, United States

    1 publications · 14 citations

    1

    h-index

1–5 of 31

Venues

  1. The Annals of Probability

    6 publications · 296 citations

    6

    h-index

  2. Stochastic Processes and their Applications

    4 publications · 138 citations

    4

    h-index

  3. Journal of Theoretical Probability

    2 publications · 38 citations

    2

    h-index

  4. Journal of Multivariate Analysis

    2 publications · 33 citations

    2

    h-index

  5. SIAM Journal on Computing

    1 publications · 79 citations

    1

    h-index

1–5