14 citations · 51 across the 22 of their papers we have counts for
10 papers · 1 filter
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…
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…
Probing Predictions on OOD Images via Nearest Categories
Yao-Yuan Yang, Cyrus Rashtchian, Ruslan Salakhutdinov +1
We study out-of-distribution (OOD) prediction behavior of neural networks when they classify images from unseen classes or corrupted images. To probe the OOD behavior, we introduce…
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…
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…
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…