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We consider the problem of computing exact sums of squares (SOS) decompositions for certain classes of non-negative multivariate polynomials, relying on semidefinite programming (SDP) solvers. We provide a hybrid numeric-symbolic algorithm…

Symbolic Computation · Computer Science 2026-02-24 Victor Magron , Mohab Safey El Din

In this work, we consider the list-decodability and list-recoverability of codes in the zero-rate regime. Briefly, a code $\mathcal{C} \subseteq [q]^n$ is $(p,\ell,L)$-list-recoverable if for all tuples of input lists $(Y_1,\dots,Y_n)$ with…

Information Theory · Computer Science 2023-09-06 Nicolas Resch , Chen Yuan , Yihan Zhang

We analyze the list-decodability, and related notions, of random linear codes. This has been studied extensively before: there are many different parameter regimes and many different variants. Previous works have used complementary styles…

Information Theory · Computer Science 2017-04-11 Atri Rudra , Mary Wootters

The design of decoding algorithms is a significant technological component in the development of fault-tolerant quantum computers. Often design of quantum decoders is inspired by classical decoding algorithms, but there are no general…

Quantum Physics · Physics 2022-07-14 Armanda O. Quintavalle , Earl T. Campbell

We present a general framework for constructing high rate error correcting codes that are locally correctable (and hence locally decodable if linear) with a sublinear number of queries, based on lifting codes with respect to functions on…

Information Theory · Computer Science 2014-02-06 Alan Guo

In recent years, copositive programming has received significant attention for its ability to model hard problems in both discrete and continuous optimization. Several relaxations of copositive programs based on semidefinite programming…

Optimization and Control · Mathematics 2025-01-08 Marilena Palomba , Lucas Slot , Luis Felipe Vargas , Monaldo Mastrolilli

We give new constructions of two classes of algebraic code families which are efficiently list decodable with small output list size from a fraction $1-R-\epsilon$ of adversarial errors where $R$ is the rate of the code, for any desired…

Computational Complexity · Computer Science 2020-11-17 Venkatesan Guruswami , Chaoping Xing

We give a new approach to the dictionary learning (also known as "sparse coding") problem of recovering an unknown $n\times m$ matrix $A$ (for $m \geq n$) from examples of the form \[ y = Ax + e, \] where $x$ is a random vector in $\mathbb…

Data Structures and Algorithms · Computer Science 2014-11-11 Boaz Barak , Jonathan A. Kelner , David Steurer

Code retrieval helps developers reuse the code snippet in the open-source projects. Given a natural language description, code retrieval aims to search for the most relevant code among a set of code. Existing state-of-the-art approaches…

Computation and Language · Computer Science 2020-08-21 Qihao Zhu , Zeyu Sun , Xiran Liang , Yingfei Xiong , Lu Zhang

Understanding the limits of list-decoding and list-recovery of Reed-Solomon (RS) codes is of prime interest in coding theory and has attracted a lot of attention in recent decades. However, the best possible parameters for these problems…

Information Theory · Computer Science 2021-06-01 Eitan Goldberg , Chong Shangguan , Itzhak Tamo

In this paper, we establish the list-decoding capacity theorem for sum-rank metric codes. This theorem implies the list-decodability theorem for random general sum-rank metric codes: Any random general sum-rank metric code with a rate not…

Information Theory · Computer Science 2025-03-14 Yang Liu , Anna Baumeister , Antonia Wachter-Zeh

In the dynamic Single-Source Shortest Paths (SSSP) problem, we are given a graph $G=(V,E)$ subject to edge insertions and deletions and a source vertex $s\in V$, and the goal is to maintain the distance $d(s,t)$ for all $t\in V$.…

Data Structures and Algorithms · Computer Science 2020-01-30 Maximilian Probst Gutenberg , Virginia Vassilevska Williams , Nicole Wein

We construct an explicit family of linear rank-metric codes over any field ${\mathbb F}_h$ that enables efficient list decoding up to a fraction $\rho$ of errors in the rank metric with a rate of $1-\rho-\epsilon$, for any desired $\rho \in…

Information Theory · Computer Science 2013-12-03 Venkatesan Guruswami , Carol Wang

Both horizontal interleaving as well as the sum-rank metric are currently attractive topics in the field of code-based cryptography, as they could mitigate the problem of large key sizes. In contrast to vertical interleaving, where…

Information Theory · Computer Science 2023-08-23 Felicitas Hörmann , Hannes Bartz

Chvatal-Gomory (CG) cuts and the Bienstock-Zuckerberg hierarchy capture useful linear programs that the standard bounded degree Lasserre/Sum-of-Squares SOS hierarchy fails to capture. In this paper we present a novel polynomial time SOS…

Optimization and Control · Mathematics 2019-12-24 Monaldo Mastrolilli

Core decomposition is a classic technique for discovering densely connected regions in a graph with large range of applications. Formally, a $k$-core is a maximal subgraph where each vertex has at least $k$ neighbors. A natural extension of…

Data Structures and Algorithms · Computer Science 2023-01-31 Nikolaj Tatti

The sum-rank metric generalizes the Hamming and rank metric by partitioning vectors into blocks and defining the total weight as the sum of the rank weights of these blocks, based on their matrix representation. In this work, we explore…

Information Theory · Computer Science 2024-10-22 Thomas Jerkovits , Hannes Bartz , Antonia Wachter-Zeh

In this work, we show new and improved error-correcting properties of folded Reed-Solomon codes and multiplicity codes. Both of these families of codes are based on polynomials over finite fields, and both have been the sources of recent…

Information Theory · Computer Science 2018-05-07 Swastik Kopparty , Noga Ron-Zewi , Shubhangi Saraf , Mary Wootters

The sparsity of natural signals and images in a transform domain or dictionary has been extensively exploited in several applications such as compression, denoising and inverse problems. More recently, data-driven adaptation of synthesis…

Machine Learning · Computer Science 2017-04-24 Saiprasad Ravishankar , Raj Rao Nadakuditi , Jeffrey A. Fessler

Quantum error correction, which utilizes logical qubits that are encoded as redundant multiple physical qubits to find and correct errors in physical qubits, is indispensable for practical quantum computing. Surface code is considered to be…

Machine Learning · Computer Science 2025-09-15 Hoshitaro Ohnishi , Hideo Mukai
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