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20192024
most citedRobust Indexing for the Sliced Channel: Almost Optimal Codes for Substitutions and Deletions

1 citations · 2 across the 7 of their papers we have counts for

collaborators

8 papers

cs.CC2024

Nearest Neighbor Representations of Neural Circuits

Kordag Mehmet Kilic, Jin Sima, Jehoshua Bruck

Neural networks successfully capture the computational power of the human brain for many tasks. Similarly inspired by the brain architecture, Nearest Neighbor (NN) representations…

cs.CC2024★ 1 cited

Nearest Neighbor Representations of Neurons

Kordag Mehmet Kilic, Jin Sima, Jehoshua Bruck

The Nearest Neighbor (NN) Representation is an emerging computational model that is inspired by the brain. We study the complexity of representing a neuron (threshold function) usi…

cs.IT2023

Error Correction for DNA Storage

Jin Sima, Netanel Raviv, Moshe Schwartz +1

DNA-based storage is an emerging storage technology that provides high information density and long duration. Due to the physical constraints in the reading and writing processes,…

cs.IT2023★ 1 cited

Robust Indexing for the Sliced Channel: Almost Optimal Codes for Substitutions and Deletions

Jin Sima, Netanel Raviv, Jehoshua Bruck

Encoding data as a set of unordered strings is receiving great attention as it captures one of the basic features of DNA storage systems. However, the challenge of constructing opt…

cs.CC2023

On the Information Capacity of Nearest Neighbor Representations

Kordag Mehmet Kilic, Jin Sima, Jehoshua Bruck

The has a distinction between computation and memory. In contrast, the brain has an integrated architecture where computation and memor…

cs.IT2022

Correcting Deletions and Insertions in Racetrack Memory

Jin Sima, Jehoshua Bruck

One of the main challenges in developing racetrack memory systems is the limited precision in controlling the track shifts, that in turn affects the reliability of reading and writ…

cs.CC2022

On Algebraic Constructions of Neural Networks with Small Weights

Kordag Mehmet Kilic, Jin Sima, Jehoshua Bruck

Neural gates compute functions based on weighted sums of the input variables. The expressive power of neural gates (number of distinct functions it can compute) depends on the weig…

cs.IT2019

Iterative Programming of Noisy Memory Cells

Michal Horovitz, Eitan Yaakobi, Eyal En Gad +1

In this paper, we study a model, which was first presented by Bunte and Lapidoth, that mimics the programming operation of memory cells. Under this paradigm we assume that cells ar…