activity
20192021
most citedExKMC: Expanding Explainable -Means Clustering

14 citations · 32 across the 6 of their papers we have counts for

collaborators

14 papers

cs.CC2021

Average-Case Communication Complexity of Statistical Problems

Cyrus Rashtchian, David P. Woodruff, Peng Ye +1

We study statistical problems, such as planted clique, its variants, and sparse principal component analysis in the context of average-case communication complexity. Our motivation…

cs.DS20207 cited

Approximate Trace Reconstruction

Sami Davies, Miklos Z. Racz, Cyrus Rashtchian +1

In the usual trace reconstruction problem, the goal is to exactly reconstruct an unknown string of length after it passes through a deletion channel many times independently, p…

cs.DS2020

Batch Optimization for DNA Synthesis

Konstantin Makarychev, Miklos Z. Racz, Cyrus Rashtchian +1

Large pools of synthetic DNA molecules have been recently used to reliably store significant volumes of digital data. While DNA as a storage medium has enormous potential because o…

cs.LG20203 cited

Unsupervised Embedding of Hierarchical Structure in Euclidean Space

Jinyu Zhao, Yi Hao, Cyrus Rashtchian

Deep embedding methods have influenced many areas of unsupervised learning. However, the best methods for learning hierarchical structure use non-Euclidean representations, whereas…

cs.CC2020

Trace Reconstruction Problems in Computational Biology

Vinnu Bhardwaj, Pavel A. Pevzner, Cyrus Rashtchian +1

The problem of reconstructing a string from its error-prone copies, the trace reconstruction problem, was introduced by Vladimir Levenshtein two decades ago. While there has been c…

cs.LG202014 cited

ExKMC: Expanding Explainable -Means Clustering

Nave Frost, Michal Moshkovitz, Cyrus Rashtchian

Despite the popularity of explainable AI, there is limited work on effective methods for unsupervised learning. We study algorithms for -means clustering, focusing on a trade-of…