67 citations · 262 across the 80 of their papers we have counts for
113 papers
On the Average List Size of VT Codes under Two Insertions or Two Deletions
Anisha Banerjee, Roni Con, Antonia Wachter-Zeh +1
Levenshtein's classical theorem shows that any code that can uniquely decode from \(t\) deletions can also uniquely decode from \(t\) insertions. This symmetry, however, does not g…
SynDe: Syndrome-guided Decoding of Raw Nanopore Reads
Anisha Banerjee, Roman Sokolovskii, Thomas Heinis +3
Nanopore sequencing technology remains highly error-prone, making efficient error correction essential in DNA-based data storage. Prior work addressed high error rates using convol…
Sequence Reconstruction over Coloring Channels for Protein Identification
Jessica Bariffi, Antonia Wachter-Zeh, Eitan Yaakobi
This paper studies the sequence reconstruction problem for a channel inspired by protein identification. We introduce a coloring channel, where a sequence is transmitted through a…
Decoding Insertions/Deletions via List Recovery
Anisha Banerjee, Roni Con, Antonia Wachter-Zeh +1
In this work, we consider the problem of efficient decoding of codes from insertions and deletions. Most of the known efficient codes are codes with synchronization strings which a…
Correcting Multiple Substitutions in Nanopore-Sequencing Reads
Anisha Banerjee, Yonatan Yehezkeally, Antonia Wachter-Zeh +1
Despite their significant advantages over competing technologies, nanopore sequencers are plagued by high error rates, due to physical characteristics of the nanopore and inherent…
BICompFL: Stochastic Federated Learning with Bi-Directional Compression
Maximilian Egger, Rawad Bitar, Antonia Wachter-Zeh +2
We address the prominent communication bottleneck in federated learning (FL). We specifically consider stochastic FL, in which models or compressed model updates are specified by d…
CAT and DOG: Improved Codes for Private Distributed Matrix Multiplication
Christoph Hofmeister, Rawad Bitar, Antonia Wachter-Zeh
We present novel constructions of polynomial codes for private distributed matrix multiplication (PDMM/SDMM) using outer product partitioning (OPP). We extend the degree table fram…
Sequential Decoding of Multiple Traces Over the Syndrome Trellis for Synchronization Errors
Anisha Banerjee, Lorenz Welter, Alexandre Graell i Amat +2
Standard decoding approaches for convolutional codes, such as the Viterbi and BCJR algorithms, entail significant complexity when correcting synchronization errors. The situation w…
Scalable and Reliable Over-the-Air Federated Edge Learning
Maximilian Egger, Christoph Hofmeister, Cem Kaya +2
Federated edge learning (FEEL) has emerged as a core paradigm for large-scale optimization. However, FEEL still suffers from a communication bottleneck due to the transmission of h…
Self-Regulating Random Walks for Resilient Decentralized Learning on Graphs
Maximilian Egger, Rawad Bitar, Ghadir Ayache +2
Consider the setting of multiple random walks (RWs) on a graph executing a certain computational task. For instance, in decentralized learning via RWs, a model is updated at each i…
Capacity-Maximizing Input Symbol Selection for Discrete Memoryless Channels
Maximilian Egger, Rawad Bitar, Antonia Wachter-Zeh +2
Motivated by communication systems with constrained complexity, we consider the problem of input symbol selection for discrete memoryless channels (DMCs). Given a DMC, the goal is…
An End-to-End Coding Scheme for DNA-Based Data Storage With Nanopore-Sequenced Reads
Lorenz Welter, Roman Sokolovskii, Thomas Heinis +3
We consider error-correcting coding for deoxyribonucleic acid (DNA)-based storage using nanopore sequencing. We model the DNA storage channel as a sampling noise channel where the…
Coding for Composite DNA to Correct Substitutions, Strand Losses, and Deletions
Frederik Walter, Omer Sabary, Antonia Wachter-Zeh +1
Composite DNA is a recent method to increase the base alphabet size in DNA-based data storage.This paper models synthesizing and sequencing of composite DNA and introduces coding t…
Maximal-Capacity Discrete Memoryless Channel Identification
Maximilian Egger, Rawad Bitar, Antonia Wachter-Zeh +2
The problem of identifying the channel with the highest capacity among several discrete memoryless channels (DMCs) is considered. The problem is cast as a pure-exploration multi-ar…
Correcting a Single Deletion in Reads from a Nanopore Sequencer
Anisha Banerjee, Yonatan Yehezkeally, Antonia Wachter-Zeh +1
Owing to its several merits over other DNA sequencing technologies, nanopore sequencers hold an immense potential to revolutionize the efficiency of DNA storage systems. However, t…
Sparsity and Privacy in Secret Sharing: A Fundamental Trade-Off
Rawad Bitar, Maximilian Egger, Antonia Wachter-Zeh +1
This work investigates the design of sparse secret sharing schemes that encode a sparse private matrix into sparse shares. This investigation is motivated by distributed computing,…
Sparse and Private Distributed Matrix Multiplication with Straggler Tolerance
Maximilian Egger, Marvin Xhemrishi, Antonia Wachter-Zeh +1
This paper considers the problem of outsourcing the multiplication of two private and sparse matrices to untrusted workers. Secret sharing schemes can be used to tolerate straggler…
Randomized Decoding of Linearized Reed-Solomon Codes Beyond the Unique Decoding Radius
Thomas Jerkovits, Hannes Bartz, Antonia Wachter-Zeh
In this paper we address the problem of decoding linearized Reed-Solomon (LRS) codes beyond their unique decoding radius. We analyze the complexity in order to evaluate if the cons…
Private Aggregation in Hierarchical Wireless Federated Learning with Partial and Full Collusion
Maximilian Egger, Christoph Hofmeister, Antonia Wachter-Zeh +1
In federated learning, a federator coordinates the training of a model, e.g., a neural network, on privately owned data held by several participating clients. The gradient descent…
Error-Correcting Codes for Nanopore Sequencing
Anisha Banerjee, Yonatan Yehezkeally, Antonia Wachter-Zeh +1
Nanopore sequencing, superior to other sequencing technologies for DNA storage in multiple aspects, has recently attracted considerable attention. Its high error rates, however, de…
FedGT: Identification of Malicious Clients in Federated Learning with Secure Aggregation
Marvin Xhemrishi, Johan Östman, Antonia Wachter-Zeh +1
We propose FedGT, a novel framework for identifying malicious clients in federated learning with secure aggregation. Inspired by group testing, the framework leverages overlapping…
Geometrical Properties of Balls in Sum-Rank Metric
Cornelia Ott, Hedongliang Liu, Antonia Wachter-Zeh
The sum-rank metric arises as an algebraic approach for coding in MIMO block-fading channels and multishot network coding. Codes designed in the sum-rank metric have raised interes…
Generic Decoding of Restricted Errors
Marco Baldi, Sebastian Bitzer, Alessio Pavoni +3
Several recently proposed code-based cryptosystems base their security on a slightly generalized version of the classical (syndrome) decoding problem. Namely, in the so-called rest…
Codes Correcting Burst and Arbitrary Erasures for Reliable and Low-Latency Communication
Serge Kas Hanna, Zhiyuan Tan, Wen Xu +1
Motivated by modern network communication applications which require low latency, we study codes that correct erasures with low decoding delay. We provide a simple explicit constru…