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Executing quantum algorithms on a quantum computer requires compilation to representations that conform to all restrictions imposed by the device. Due to devices' limited coherence times and gate fidelities, the compilation process has to…

Quantum Physics · Physics 2025-12-16 Sarah Schneider , Lukas Burgholzer , Robert Wille

In the last decade, the power of the state-of-the-art SAT and Integer Programming solvers has dramatically increased. They implement many new techniques and heuristics and since any NP problem can be converted to SAT or ILP instance, we…

Data Structures and Algorithms · Computer Science 2010-11-25 Rastislav Lenhardt

The SAT attack has shown to be efficient against most combinational logic encryption methods. It can be extended to attack sequential logic encryption techniques by leveraging circuit unrolling and model checking methods. However, with no…

Cryptography and Security · Computer Science 2022-02-18 Yinghua Hu , Yuke Zhang , Kaixin Yang , Dake Chen , Peter A. Beerel , Pierluigi Nuzzo

Low-rank matrix factorization (MF) is an important technique in data science. The key idea of MF is that there exists latent structures in the data, by uncovering which we could obtain a compressed representation of the data. By factorizing…

Numerical Analysis · Computer Science 2016-05-09 Yuan Lu , Jie Yang

Nonnegative matrix factorization (NMF) is widely used for clustering with strong interpretability. Among general NMF problems, symmetric NMF is a special one that plays an important role in graph clustering where each element measures the…

Machine Learning · Computer Science 2023-11-07 Mengyuan Zhang , Kai Liu

A previously developed quantum search algorithm for solving 1-SAT problems in a single step is generalized to apply to a range of highly constrained k-SAT problems. We identify a bound on the number of clauses in satisfiability problems for…

Artificial Intelligence · Computer Science 2011-05-30 T. Hogg

Applying deep learning to solve real-life instances of hard combinatorial problems has tremendous potential. Research in this direction has focused on the Boolean satisfiability (SAT) problem, both because of its theoretical centrality and…

Artificial Intelligence · Computer Science 2023-06-06 Dimitris Achlioptas , Amrit Daswaney , Periklis A. Papakonstantinou

Logic locking is used to protect integrated circuits (ICs) from piracy and counterfeiting. An encrypted IC implements the correct function only when the right key is input. Many existing logic-locking methods are subject to the powerful…

Cryptography and Security · Computer Science 2021-03-30 Jingbo Zhou , Xinmiao Zhang

Although Path-Relinking is an effective local search method for many combinatorial optimization problems, its application is not straightforward in solving the MAX-SAT, an optimization variant of the satisfiability problem (SAT) that has…

Artificial Intelligence · Computer Science 2018-08-13 Zhen-Xing Xu , Kun He , Chu-Min Li

The boolean satisfiability (SAT) problem asks whether there exists an assignment of boolean values to the variables of an arbitrary boolean formula making the formula evaluate to True. It is well-known that all NP-problems can be coded as…

Machine Learning · Computer Science 2024-10-22 Christopher R. Serrano , Jonathan Gallagher , Kenji Yamada , Alexei Kopylov , Michael A. Warren

We propose a relax-and-round approach combined with a greedy search strategy for performing complex lattice basis reduction. Taking an optimization perspective, we introduce a relaxed version of the problem that, while still nonconvex, has…

Signal Processing · Electrical Eng. & Systems 2018-08-16 Marius Arvinte , Ahmed H. Tewfik

Cutting rectangular items from stock sheets to satisfy demands while minimizing waste is a central manufacturing task. The Two-Dimensional Single Stock Size Cutting Stock Problem (2D-CSSP) generalizes bin packing by requiring multiple…

Artificial Intelligence · Computer Science 2026-04-06 Tuyen Van Kieu , Chi Linh Hoang , Khanh Van To

RSA is one of the most popular Public Key Cryptography based algorithm mainly used for digital signatures, encryption/decryption etc. It is based on the mathematical scheme of factorization of very large integers which is a…

Cryptography and Security · Computer Science 2015-03-13 Sapna Saxena , Bhanu Kapoor

The classical branch-and-bound algorithm for the integer feasibility problem has exponential worst case complexity. We prove that it is surprisingly efficient on reformulated problems, in which the columns of the constraint matrix are…

Optimization and Control · Mathematics 2009-08-06 Gabor Pataki , Mustafa Tural

Considering its relevance in the field of cryptography, integer factorization is a prominent application where Quantum computers are expected to have a substantial impact. Thanks to Shor's algorithm this peculiar problem can be solved in…

Rank regularized minimization problem is an ideal model for the low-rank matrix completion/recovery problem. The matrix factorization approach can transform the high-dimensional rank regularized problem to a low-dimensional factorized…

Optimization and Control · Mathematics 2024-05-21 Wenjing Li , Wei Bian , Kim-Chuan Toh

We offer multiplication method for factoring big natural numbers which extends the group of the Fermat's and Lehman's factorization algorithms and has run-time complexity $O(n^{1/3})$. This paper is argued the finiteness of proposed…

Data Structures and Algorithms · Computer Science 2019-04-01 Igor Nesiolovskiy , Artem Nesiolovskiy

We give a public key encryption scheme with plausible quasi-exponential security based on the conjectured intractability of two constraint satisfaction problems (CSPs), both of which are instantiated with a corruption rate of $1 - o(1)$.…

Cryptography and Security · Computer Science 2026-04-14 Isaac M Hair , Amit Sahai

In this paper, we present an approach to integer factorization using distributed representations formed with Vector Symbolic Architectures. The approach formulates integer factorization in a manner such that it can be solved using neural…

Neural and Evolutionary Computing · Computer Science 2022-09-02 Denis Kleyko , Connor Bybee , Christopher J. Kymn , Bruno A. Olshausen , Amir Khosrowshahi , Dmitri E. Nikonov , Friedrich T. Sommer , E. Paxon Frady

Sparse coding is a core building block in many data analysis and machine learning pipelines. Typically it is solved by relying on generic optimization techniques, such as the Iterative Soft Thresholding Algorithm and its accelerated version…

Machine Learning · Statistics 2017-06-06 Thomas Moreau , Joan Bruna
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