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Due to the outstanding capability of capturing underlying data distributions, deep learning techniques have been recently utilized for a series of traditional database problems. In this paper, we investigate the possibilities of utilizing…

Databases · Computer Science 2021-09-27 Yaoshu Wang , Chuan Xiao , Jianbin Qin , Xin Cao , Yifang Sun , Wei Wang , Makoto Onizuka

One major open problem in network coding is to characterize the capacity region of a general multi-source multi-demand network. There are some existing computational tools for bounding the capacity of general networks, but their…

Information Theory · Computer Science 2015-03-17 Michelle Effros , Tracey Ho , Shirin Jalali

The at-most-k constraint is ubiquitous in combinatorial problems, and numerous SAT encodings are available for the constraint. Prior experiments have shown the competitiveness of the sequential-counter encoding for k $>$ 1, and have…

Logic in Computer Science · Computer Science 2020-05-14 Neng-Fa Zhou

Maximum-likelihood (ML) decoding can be used to obtain the optimal performance of error correction codes. However, the size of the search space and consequently the decoding complexity grows exponentially, making it impractical to be…

Information Theory · Computer Science 2022-05-25 Mohammad Rowshan , Jinhong Yuan

Cardinality-constrained diameter partitioning asks for a partition of $n$ items into two classes of prescribed sizes that minimizes the larger of the two class diameters. We give an $O(n^2)$ algorithm and a matching $\Omega(n^2)$ lower…

Data Structures and Algorithms · Computer Science 2026-05-06 Chao Xu , Mingdong Yang

Cardinality constrained bin packing or bin packing with cardinality constraints is a basic bin packing problem. In the online version with the parameter k \geq 2, items having sizes in (0,1] associated with them are presented one by one to…

Data Structures and Algorithms · Computer Science 2016-08-24 János Balogh , József Békési , György Dósa , Leah Epstein , Asaf Levin

The main goal of 1-bit compressive sampling is to decode $n$ dimensional signals with sparsity level $s$ from $m$ binary measurements. This is a challenging task due to the presence of nonlinearity, noises and sign flips. In this paper, the…

Information Theory · Computer Science 2020-06-05 Zhao Ding , Junjun Huang , Yuling Jiao , Xiliang Lu , Zhijian Yang

This article discusses some difficulties in the implementation of combinatorial algorithms associated with the choice of all elements with certain properties among the elements of a set with great cardinality.The problem has been resolved…

Data Structures and Algorithms · Computer Science 2016-01-18 Krasimir Yordzhev

A fundamental problem in computer science is to find all the common zeroes of $m$ quadratic polynomials in $n$ unknowns over $\mathbb{F}_2$. The cryptanalysis of several modern ciphers reduces to this problem. Up to now, the best complexity…

Symbolic Computation · Computer Science 2015-03-19 Magali Bardet , Jean-Charles Faugère , Bruno Salvy , Pierre-Jean Spaenlehauer

The $k$-Maximum Dispersion Problem with Cardinality Constraints ($k$-MDCC) asks for a partition of a given item set with pairwise dissimilarities into $k$ cardinality-constrained groups such that the minimum pairwise intra-group…

Data Structures and Algorithms · Computer Science 2026-04-28 Nguyen Khoa Tran , Lin Mu , Martin Papenberg , Gunnar W. Klau

In this work, we study two types of constraints on two-dimensional binary arrays. In particular, given $p,\epsilon>0$, we study (i) The $p$-bounded constraint: a binary vector of size $m$ is said to be $p$-bounded if its weight is at most…

Information Theory · Computer Science 2022-08-22 Tuan Thanh Nguyen , Kui Cai , Han Mao Kiah , Kees A. Schouhamer Immink , Yeow Meng Chee

In traditional software programs, it is easy to trace program logic from variables back to input, apply assertion statements to block erroneous behavior, and compose programs together. Although deep learning programs have demonstrated…

Machine Learning · Computer Science 2021-10-27 Mike Wu , Noah Goodman , Stefano Ermon

We construct neural network regression models to predict key metrics of complexity for Gr\"obner bases of binomial ideals. This work illustrates why predictions with neural networks from Gr\"obner computations are not a straightforward…

Commutative Algebra · Mathematics 2025-08-28 Shahrzad Jamshidi , Eric Kang , Sonja Petrović

The classical problem in network coding theory considers communication over multicast networks. Multiple transmitters send independent messages to multiple receivers which decode the same set of messages. In this work, computation over…

Information Theory · Computer Science 2016-02-18 Changho Suh , Naveen Goela , Michael Gastpar

We investigate the design of two neural network (NN) architectures recently proposed as decoders for forward error correction: the so-called single-label NN (SLNN) and multi-label NN (MLNN) decoders. These decoders have been reported to…

Signal Processing · Electrical Eng. & Systems 2025-03-25 Yunus Can Gültekin , Péter Scheepers , Yuncheng Yuan , Federico Corradi , Alex Alvarado

Enumerating matchings is a classical problem in the field of enumeration algorithms. There are polynomial-delay enumeration algorithms for several settings, such as enumerating perfect matchings, maximal matchings, and (weighted) matchings…

Data Structures and Algorithms · Computer Science 2022-09-07 Yasuaki Kobayashi , Kazuhiro Kurita , Kunihiro Wasa

Minimal multicast networks are fascinating and efficient combinatorial objects, where the removal of a single link makes it impossible for all receivers to obtain all messages. We study the structure of such networks, and prove some…

Information Theory · Computer Science 2019-09-16 Han Cai , Johan Chrisnata , Tuvi Etzion , Moshe Schwartz , Antonia Wachter-Zeh

In this paper, we prove that with high probability, random Reed-Solomon codes approach the half-Singleton bound - the optimal rate versus error tradeoff for linear insdel codes - with linear-sized alphabets. More precisely, we prove that,…

Information Theory · Computer Science 2024-07-11 Roni Con , Zeyu Guo , Ray Li , Zihan Zhang

We consider the problem of deciding the satisfiability of quantifier-free formulas in the theory of finite sets with cardinality constraints. Sets are a common high-level data structure used in programming; thus, such a theory is useful for…

Logic in Computer Science · Computer Science 2023-06-22 Kshitij Bansal , Clark Barrett , Andrew Reynolds , Cesare Tinelli

Let G be a plane graph of n nodes, m edges, f faces, and no self-loop. G need not be connected or simple (i.e., free of multiple edges). We give three sets of coding schemes for G which all take O(m+n) time for encoding and decoding. Our…

Data Structures and Algorithms · Computer Science 2007-05-23 Richie Chih-Nan Chuang , Ashim Garg , Xin He , Ming-Yang Kao , Hsueh-I Lu