activity
20122022
most citedNon-binary Codes for Correcting a Burst of at Most t Deletions

5 citations · 9 across the 6 of their papers we have counts for

collaborators

12 papers

cs.IT20225 cited

Non-binary Codes for Correcting a Burst of at Most t Deletions

Shuche Wang, Yuanyuan Tang, Jin Sima +2

The problem of correcting deletions has received significant attention, partly because of the prevalence of these errors in DNA data storage. In this paper, we study the problem of…

cs.LG2021

Adaptive Sampling for Heterogeneous Rank Aggregation from Noisy Pairwise Comparisons

Yue Wu, Tao Jin, Hao Lou +3

In heterogeneous rank aggregation problems, users often exhibit various accuracy levels when comparing pairs of items. Thus a uniform querying strategy over users may not be optima…

cs.IT2020

Error-correcting Codes for Short Tandem Duplication and Substitution Errors

Yuanyuan Tang, Farzad Farnoud

Due to its high data density and longevity, DNA is considered a promising medium for satisfying ever-increasing data storage needs. However, the diversity of errors that occur in D…

cs.IT20201 cited

Error-correcting Codes for Noisy Duplication Channels

Yuanyuan Tang, Farzad Farnoud

Because of its high data density and longevity, DNA is emerging as a promising candidate for satisfying increasing data storage needs. Compared to conventional storage media, howev…

cs.IT2020

Coding for Optimized Writing Rate in DNA Storage

Siddharth Jain, Farzad Farnoud, Moshe Schwartz +1

A method for encoding information in DNA sequences is described. The method is based on the precision-resolution framework, and is aimed to work in conjunction with a recently sugg…

cs.LG2019

Rank Aggregation via Heterogeneous Thurstone Preference Models

Tao Jin, Pan Xu, Quanquan Gu +1

We propose the Heterogeneous Thurstone Model (HTM) for aggregating ranked data, which can take the accuracy levels of different users into account. By allowing different noise dist…