17 citations · 42 across the 15 of their papers we have counts for
4 papers · 1 filter
Data driven weak universal consistency
N. Santhanam, V. Anantharam, W. Szpankowski
Many current applications in data science need rich model classes to adequately represent the statistics that may be driving the observations. But rich model classes may be too com…
Universal compression of Gaussian sources with unknown parameters
A. Orlitsky, N. Santhanam
For a collection of distributions over a countable support set, the worst case universal compression formulation by Shtarkov attempts to assign a universal distribution over the su…
Redundancy of Exchangeable Estimators
Narayana P. Santhanam, Anand D. Sarwate, Jae Oh Woo
Exchangeable random partition processes are the basis for Bayesian approaches to statistical inference in large alphabet settings. On the other hand, the notion of the pattern of a…
On redundancy of memoryless sources over countable alphabets
Maryam Hosseini, Narayana Santhanam
The minimum average number of bits need to describe a random variable is its entropy, assuming knowledge of the underlying statistics On the other hand, universal compression suppo…