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Most state-of-the-art satisfiability algorithms today are variants of the DPLL procedure augmented with clause learning. The main bottleneck for such algorithms, other than the obvious one of time, is the amount of memory used. In the field…

Computational Complexity · Computer Science 2009-09-29 Jakob Nordström , Johan Håstad

We give a characterization of deterministic polynomial time computation based on an algebraic structure called the resolution semiring, whose elements can be understood as logic programs or sets of rewriting rules over first-order terms.…

Logic in Computer Science · Computer Science 2015-02-05 Clément Aubert , Marc Bagnol , Thomas Seiller

Multithreaded programs generally leverage efficient and thread-safe concurrent objects like sets, key-value maps, and queues. While some concurrent-object operations are designed to behave atomically, each witnessing the atomic effects of…

Logic in Computer Science · Computer Science 2019-11-06 Siddharth Krishna , Michael Emmi , Constantin Enea , Dejan Jovanovic

A weight normalization procedure, commonly called pushing, is introduced for weighted tree automata (wta) over commutative semifields. The normalization preserves the recognized weighted tree language even for nondeterministic wta, but it…

Formal Languages and Automata Theory · Computer Science 2023-06-22 Thomas Hanneforth , Andreas Maletti , Daniel Quernheim

In this article, we study the computational complexity of counting weighted Eulerian orientations, denoted as \#\textsf{EO}. This problem is considered a pivotal scenario in the complexity classification for \textsf{Holant}, a counting…

Computational Complexity · Computer Science 2025-04-28 Boning Meng , Juqiu Wang , Mingji Xia

The CSP (constraint satisfaction problems) is a class of problems deciding whether there exists a homomorphism from an instance relational structure to a target one. The CSP dichotomy is a profound result recently proved by Zhuk (2020, J.…

Logic · Mathematics 2023-01-13 Azza Gaysin

To guarantee that machine learning models yield outputs that are not only accurate, but also robust, recent works propose formally verifying robustness properties of machine learning models. To be applicable to realistic safety-critical…

Machine Learning · Computer Science 2021-05-07 John Törnblom , Simin Nadjm-Tehrani

The matching of multiple objects (e.g. shapes or images) is a fundamental problem in vision and graphics. In order to robustly handle ambiguities, noise and repetitive patterns in challenging real-world settings, it is essential to take…

Computer Vision and Pattern Recognition · Computer Science 2019-03-15 Florian Bernard , Johan Thunberg , Paul Swoboda , Christian Theobalt

The principal component analysis (PCA) is a staple statistical and unsupervised machine learning technique in finance. The application of PCA in a financial setting is associated with several technical difficulties, such as numerical…

Statistical Finance · Quantitative Finance 2021-08-31 Paul Bilokon , David Finkelstein

We establish a fundamental theorem of orders (FTO) which allows us to express all orders uniquely as an intersection of `irreducible orders' along which the index and the conductor distributes multiplicatively. We define a subclass of…

Number Theory · Mathematics 2024-11-19 Gaurav Digambar Patil

Since the first termination competition in 2004 it is of great interest, whether a proof that has been automatically generated by a termination tool, is indeed correct. The increasing number of termination proving techniques as well as the…

Logic in Computer Science · Computer Science 2012-08-09 Christian Sternagel , René Thiemann , Sarah Winkler , Harald Zankl

On the one hand, ordered completion is a fundamental technique in equational theorem proving that is employed by automated tools. On the other hand, their complexity makes such tools inherently error prone. As a remedy to this situation we…

Logic in Computer Science · Computer Science 2018-05-28 Christian Sternagel , Sarah Winkler

In neural combinatorial optimization (CO), reinforcement learning (RL) can turn a deep neural net into a fast, powerful heuristic solver of NP-hard problems. This approach has a great potential in practical applications because it allows…

Machine Learning · Computer Science 2021-07-14 Yeong-Dae Kwon , Jinho Choo , Byoungjip Kim , Iljoo Yoon , Youngjune Gwon , Seungjai Min

Remote direct memory access (RDMA) allows a machine to directly read from and write to the memory of remote machine, enabling high-throughput, low-latency data transfer. Ensuring correctness of RDMA programs has only recently become…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-01-28 Guillaume Ambal , Max Stupple , Brijesh Dongol , Azalea Raad

While deep reinforcement learning has successfully solved many challenging control tasks, its real-world applicability has been limited by the inability to ensure the safety of learned policies. We propose an approach to verifiable…

Machine Learning · Computer Science 2019-01-25 Osbert Bastani , Yewen Pu , Armando Solar-Lezama

Checkpoint merging is a technique for combining multiple model snapshots into a single superior model, potentially reducing training time for large language models. This paper explores checkpoint merging in the context of…

Machine Learning · Computer Science 2025-04-29 Shi Jie Yu , Sehyun Choi

Systems Theoretic Process Analysis (STPA) is a widely recommended method for analysing complex system safety. STPA can identify numerous Unsafe Control Actions (UCAs) and requirements depending on the level of granularity of the analysis…

Systems and Control · Electrical Eng. & Systems 2025-08-15 Halima El Badaoui

Cyber-physical systems (CPSes), such as autonomous vehicles, use sophisticated components like ML-based controllers. It is difficult to provide evidence about the safe functioning of such components. To overcome this problem, Runtime…

Logic in Computer Science · Computer Science 2023-04-25 Vivek Nigam , Carolyn Talcott

We give an algorithm to enumerate the results on trees of monadic second-order (MSO) queries represented by nondeterministic tree automata. After linear time preprocessing (in the input tree), we can enumerate answers with linear delay (in…

Databases · Computer Science 2019-08-28 Antoine Amarilli , Pierre Bourhis , Stefan Mengel , Matthias Niewerth

Balancing helpfulness and safety (harmlessness) is a critical challenge in aligning large language models (LLMs). Current approaches often decouple these two objectives, training separate preference models for helpfulness and safety, while…

Machine Learning · Computer Science 2025-02-28 Xiyue Peng , Hengquan Guo , Jiawei Zhang , Dongqing Zou , Ziyu Shao , Honghao Wei , Xin Liu
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