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Private computation is a generalization of private information retrieval, in which a user is able to compute a function on a distributed dataset without revealing the identity of that function to the servers. In this paper it is shown that…

Information Theory · Computer Science 2019-06-27 Netanel Raviv , David A. Karpuk

We show that any Algebraic Branching Program (ABP) computing the polynomial $\sum_{i = 1}^n x_i^n$ has at least $\Omega(n^2)$ vertices. This improves upon the lower bound of $\Omega(n\log n)$, which follows from the classical result of Baur…

Computational Complexity · Computer Science 2020-03-19 Prerona Chatterjee , Mrinal Kumar , Adrian She , Ben Lee Volk

We consider $(n,k)$ MDS-coded distributed storage over $\mathbb{F}_q$ with per-node storage $\alpha$ symbols. For the oblivious update problem, where a single message symbol changes and neither helpers nor the stale node know which, the…

Quantum Physics · Physics 2026-05-20 Sagar Dubey

Quantum communication technologies will play an important role in quantum information processing in the near future as we network devices together. However, their implementation is still a challenging task due to both loss and gate errors.…

Quantum Physics · Physics 2023-04-12 Shin Nishio , Nicolò Lo Piparo , Michael Hanks , William John Munro , Kae Nemoto

High-dimensional models often have a large memory footprint and must be quantized after training before being deployed on resource-constrained edge devices for inference tasks. In this work, we develop an information-theoretic framework for…

Information Theory · Computer Science 2022-09-01 Rajarshi Saha , Mert Pilanci , Andrea J. Goldsmith

Let $\mathcal{R} = \mathbb{K}[x_1, \dots, x_n]$ be a multivariate polynomial ring over a field $\mathbb{K}$ of characteristic 0. Consider $n$ algebraically independent elements $g_1, \dots, g_n$ in $\mathcal{R}$. Let $\mathcal{S}$ denote…

Symbolic Computation · Computer Science 2025-05-01 Thi Xuan Vu

Fast encoding and decoding of codes have been always an important topic in code theory as well as complexity theory. Although encoding is easier than decoding in general, designing an encoding algorithm of codes of length $N$ with…

Computational Complexity · Computer Science 2024-07-08 Songsong Li , Shu Liu , Liming Ma , Yunqi Wan , Chaoping Xing

Reed-Solomon codes are a classic family of error-correcting codes consisting of evaluations of low-degree polynomials over a finite field on some sequence of distinct field elements. They are widely known for their optimal unique-decoding…

Information Theory · Computer Science 2025-09-01 Omar Alrabiah , Zeyu Guo , Venkatesan Guruswami , Ray Li , Zihan Zhang

Range minimum queries (RMQs) are fundamental operations with widespread applications in database management, text indexing and computational biology. While many space-efficient data structures have been designed for RMQs on arrays with…

Data Structures and Algorithms · Computer Science 2026-04-16 Seungbum Jo , Srinivasa Rao Satti

We consider private polynomial computation (PPC) over noncolluding coded databases. In such a setting a user wishes to compute a multivariate polynomial of degree at most $g$ over $f$ variables (or messages) stored in multiple databases…

Information Theory · Computer Science 2021-06-29 Sarah A. Obead , Hsuan-Yin Lin , Eirik Rosnes , Jörg Kliewer

Modern distributed computation infrastructures are often plagued by unavailabilities such as failing or slow servers. These unavailabilities adversely affect the tail latency of computation in distributed infrastructures. The simple…

Information Theory · Computer Science 2020-02-07 Michael Rudow , K. V. Rashmi , Venkatesan Guruswami

The sum-rank metric is the mixture of the Hamming and rank metrics. The sum-rank metric found its application in network coding, locally repairable codes, space-time coding, and quantum-resistant cryptography. Linearized Reed-Solomon (LRS)…

Information Theory · Computer Science 2026-02-10 Kuo Shang , Chen Yuan , Ruiqi Zhu

Polynomial remainder codes are a large class of codes derived from the Chinese remainder theorem that includes Reed-Solomon codes as a special case. In this paper, we revisit these codes and study them more carefully than in previous work.…

Information Theory · Computer Science 2012-01-10 Jiun-Hung Yu , Hans-Andrea Loeliger

We consider minimization of composite functions of the form $f(g(x))+h(x)$, where $f$ and $h$ are convex functions (which can be nonsmooth) and $g$ is a smooth vector mapping. In addition, we assume that $g$ is the average of finite number…

Optimization and Control · Mathematics 2021-05-17 Junyu Zhang , Lin Xiao

We investigate the decoding region for Algebraic Soft-Decision Decoding (ASD) of Reed-Solomon codes in a discrete, memoryless, additive-noise channel. An expression is derived for the error correction radius within which the soft-decision…

Information Theory · Computer Science 2007-07-13 Andrew Duggan , Alexander Barg

In this paper, we study the use of GF(q)-quantized LDGM codes for binary source coding. By employing quantization, it is possible to obtain binary codewords with a non-uniform distribution. The obtained statistics is hence suitable for…

Information Theory · Computer Science 2010-07-09 Lorenzo Cappellari

A general class of polynomial remainder codes is considered. Such codes are very flexible in rate and length and include Reed-Solomon codes as a special case. As an extension of previous work, two joint error-and-erasure decoding approaches…

Information Theory · Computer Science 2012-02-27 Jiun-Hung Yu

We investigate linear network coding in the context of robust function computation, where a sink node is tasked with computing a target function of messages generated at multiple source nodes. In a previous work, a new distance measure was…

Information Theory · Computer Science 2024-09-18 Hengjia Wei , Min Xu , Gennian Ge

Lifted Reed-Solomon codes, a subclass of lifted affine-invariant codes, have been shown to be of high rate while preserving locality properties similar to generalized Reed-Muller codes, which they contain as subcodes. This work introduces a…

Information Theory · Computer Science 2021-04-22 Lukas Holzbaur , Nikita Polyanskii

The hardness of learning a function that attains a target task relates to its input-sensitivity. For example, image classification tasks are input-insensitive as minor corruptions should not affect the classification results, whereas…

Machine Learning · Computer Science 2025-06-26 Kazuki Yoda , Kazuhiko Kawamoto , Hiroshi Kera