Algorithms with predictions incorporate machine learning predictions
int...
The edit distance is a fundamental measure of sequence similarity, defin...
Given two strings of length n over alphabet Σ, and an upper bound
k on t...
The edit distance between strings classically assigns unit cost to every...
Computing the edit distance of two strings is one of the most basic prob...
To capture inherent geometric features of many community detection probl...
The Dyck language, which consists of well-balanced sequences of parenthe...
Real-world data often comes in compressed form. Analyzing compressed dat...
We study the problem of approximating edit distance in sublinear time. T...
We study the problem of aligning multiple sequences with the goal of fin...
We study edit distance computation with preprocessing: the preprocessing...
Metric based comparison operations such as finding maximum, nearest and
...
In this paper, we design new sublinear-time algorithms for solving the g...
Blocking is a mechanism to improve the efficiency of Entity Resolution (...
The edit distance is a way of quantifying how similar two strings are to...
Several clustering frameworks with interactive (semi-supervised) queries...
Correlation clustering is a fundamental combinatorial optimization probl...
Automatically matching reviewers to papers is a crucial step of the peer...
Random geometric graphs are the simplest, and perhaps the earliest possi...
In this paper, we revisit the unweighted set cover problem in the fully
...
To capture the inherent geometric features of many community detection
p...
Suppose, we are given a set of n elements to be clustered into k
(unknow...
In this paper, we initiate a rigorous theoretical study of clustering wi...
Entity resolution (ER) is the task of identifying all records in a datab...