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We extend an implicit regularization scheme to be applicable in the $n$-dimensional space-time. Within this scheme divergences involving parity violating objects can be consistently treated without recoursing to dimensional continuation.…

High Energy Physics - Theory · Physics 2016-09-06 A. P. B. Scarpelli , M. Sampaio , M. C. Nemes

MDS array codes are widely used in storage systems to protect data against erasures. We address the \emph{rebuilding ratio} problem, namely, in the case of erasures, what is the the fraction of the remaining information that needs to be…

Information Theory · Computer Science 2011-03-22 Itzhak Tamo , Zhiying Wang , Jehoshua Bruck

The vast majority of Dimensionality Reduction (DR) techniques rely on second-order statistics to define their optimization objective. Even though this provides adequate results in most cases, it comes with several shortcomings. The methods…

Computer Vision and Pattern Recognition · Computer Science 2017-08-21 Nikolaos Passalis , Anastasios Tefas

This work continues the study of linear error correcting codes against adversarial insertion deletion errors (insdel errors). Previously, the work of Cheng, Guruswami, Haeupler, and Li \cite{CGHL21} showed the existence of asymptotically…

Information Theory · Computer Science 2023-03-31 Kuan Cheng , Zhengzhong Jin , Xin Li , Zhide Wei , Yu Zheng

In this paper we study error-correcting codes for the storage of data in synthetic deoxyribonucleic acid (DNA). We investigate a storage model where a data set is represented by an unordered set of $M$ sequences, each of length $L$. Errors…

Information Theory · Computer Science 2020-02-13 Andreas Lenz , Paul H. Siegel , Antonia Wachter-Zeh , Eitan Yaakobi

Deep Metric Learning algorithms aim to learn an efficient embedding space to preserve the similarity relationships among the input data. Whilst these algorithms have achieved significant performance gains across a wide plethora of tasks,…

Computer Vision and Pattern Recognition · Computer Science 2022-09-15 Soumava Kumar Roy , Yan Han , Mehrtash Harandi , Lars Petersson

Locally repairable convolutional codes (LRCCs) for distributed storage systems (DSSs) are introduced in this work. They enable local repair, for a single node erasure (or more generally, $ \partial - 1 $ erasures per local group), and…

Information Theory · Computer Science 2020-12-08 Umberto Martínez-Peñas , Diego Napp

For mixed-integer linear programming and linear programming it is well known that symmetries can have a negative impact on the performance of branch-and-bound and linear optimization algorithms. A common strategy to handle symmetries in…

Optimization and Control · Mathematics 2026-03-13 Rolf van der Hulst

Given a $d$-dimensional array $A$, an update operation adds a given constant $C$ to each element within a continuous sub-array of $A$. A query operation computes the sum of all the elements within a continuous sub-array of $A$. The…

Data Structures and Algorithms · Computer Science 2016-08-05 Pushkar Mishra

We introduce a general class of codes which includes several well-known classes of deletion/insertion correcting codes as special cases. For example, the Helberg code, the Levenshtein code, the Varshamov--Tenengolts code, and most variants…

Information Theory · Computer Science 2018-12-27 Khodakhast Bibak , Olgica Milenkovic

Locally decodable codes (LDC's) are error-correcting codes that allow recovery of individual message indices by accessing only a constant number of codeword indices. For substitution errors, it is evident that LDC's exist -- Hadamard codes…

Information Theory · Computer Science 2023-11-15 Meghal Gupta

We consider the problem of constructing deletion correcting codes over a binary alphabet and take a graph theoretic view. An $n$-bit $s$-deletion correcting code is an independent set in a particular graph. We propose constructing such a…

Information Theory · Computer Science 2012-11-20 Daniel Cullina , Ankur A. Kulkarni , Negar Kiyavash

We study codes that are list-decodable under insertions and deletions. Specifically, we consider the setting where a codeword over some finite alphabet of size $q$ may suffer from $\delta$ fraction of adversarial deletions and $\gamma$…

Information Theory · Computer Science 2018-02-26 Bernhard Haeupler , Amirbehshad Shahrasbi , Madhu Sudan

DNA is a leading candidate as the next archival storage media due to its density, durability and sustainability. To read (and write) data DNA storage exploits technology that has been developed over decades to sequence naturally occurring…

Emerging Technologies · Computer Science 2022-05-12 Jasmine Quah , Omer Sella , Thomas Heinis

Denoising diffusion probabilistic models (DDPMs) have shown impressive results on sequence generation by iteratively corrupting each example and then learning to map corrupted versions back to the original. However, previous work has…

Machine Learning · Computer Science 2021-07-19 Daniel D. Johnson , Jacob Austin , Rianne van den Berg , Daniel Tarlow

Consider two or more strings $\mathbf{x}^1,\mathbf{x}^2,\ldots,$ that are concatenated to form $\mathbf{x}=\langle \mathbf{x}^1,\mathbf{x}^2,\ldots \rangle$. Suppose that up to $\delta$ deletions occur in each of the concatenated strings.…

Information Theory · Computer Science 2023-04-20 Serge Kas Hanna

Insdel errors occur in communication systems caused by the loss of positional information of the message. Since the work by Guruswami and Wang, there have been some further investigations on the list decoding of insertion codes, deletion…

Information Theory · Computer Science 2020-09-30 Shu Liu , Ivan Tjuawinata , Chaoping Xing

Due to its high data density and longevity, DNA is considered a promising medium for satisfying ever-increasing data storage needs. However, the diversity of errors that occur in DNA sequences makes efficient error-correction a challenging…

Information Theory · Computer Science 2020-11-12 Yuanyuan Tang , Farzad Farnoud

Deep neural networks are widely used in various domains. However, the nature of computations at each layer of the deep networks is far from being well understood. Increasing the interpretability of deep neural networks is thus important.…

Machine Learning · Computer Science 2018-12-19 Haiping Huang

This paper extends the foundational work of Dollma \emph{et al}. on codes for ordered composite DNA sequences. We consider the general setting with an alphabet of size $q$ and a resolution parameter $k$, moving beyond the binary ($q=2$)…

Information Theory · Computer Science 2026-02-19 Zuo Ye , Yuling Li , Zhaojun Lan , Gennian Ge
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