78 citations · 292 across the 31 of their papers we have counts for
33 papers
Generalizations and Extensions to Lifting Constructions for Coded Caching
V. R. Aravind, Pradeep Kiran Sarvepalli, Andrew Thangaraj
Coded caching is a technique for achieving increased throughput in cached networks during peak hours. Placement delivery arrays (PDAs) capture both placement and delivery scheme re…
Capacity Achieving Codes for an Erasure Queue-Channel
Jaswanthi Mandalapu, Krishna Jagannathan, Avhishek Chatterjee +1
We consider a queue-channel model that captures the waiting time-dependent degradation of information bits as they wait to be transmitted. Such a scenario arises naturally in quant…
Missing Mass Estimation from Sticky Channels
Prafulla Chandra, Andrew Thangaraj, Nived Rajaraman
Distribution estimation under error-prone or non-ideal sampling modelled as "sticky" channels have been studied recently motivated by applications such as DNA computing. Missing ma…
Missing -mass: Investigating the Missing Parts of Distributions
Prafulla Chandra, Andrew Thangaraj
Estimating the underlying distribution from \textit{iid} samples is a classical and important problem in statistics. When the alphabet size is large compared to number of samples,…
How good is Good-Turing for Markov samples?
Prafulla Chandra, Andrew Thangaraj, Nived Rajaraman
The Good-Turing (GT) estimator for the missing mass (i.e., total probability of missing symbols) in samples is the number of symbols that appeared exactly once divided by .…
Lifting Constructions of PDAs for Coded Caching with Linear Subpacketization
V R Aravind, Pradeep Kiran Sarvepalli, Andrew Thangaraj
Coded caching is a technique where multicasting and coding opportunities are utilized to achieve better rate-memory tradeoff in cached networks. A crucial parameter in coded cachin…