English
Related papers

Related papers: Structured d-DNNF Is Not Closed Under Negation

200 papers

Dynamic Fault Trees (DFTs) are a prominent model in reliability engineering. They are strictly more expressive than static fault trees, but this comes at a price: their interpretation is non-trivial and leaves quite some freedom. This paper…

Software Engineering · Computer Science 2019-03-13 Sebastian Junges , Joost-Pieter Katoen , Marielle Stoelinga , Matthias Volk

Linear discriminant analysis (LDA) is a popular tool for classification and dimension reduction. Limited by its linear form and the underlying Gaussian assumption, however, LDA is not applicable in situations where the data distribution is…

Machine Learning · Computer Science 2020-11-02 Yunqi Cai , Dong Wang

This paper explains the generalization power of a deep neural network (DNN) from the perspective of interactions. Although there is no universally accepted definition of the concepts encoded by a DNN, the sparsity of interactions in a DNN…

Machine Learning · Computer Science 2024-09-16 Huilin Zhou , Hao Zhang , Huiqi Deng , Dongrui Liu , Wen Shen , Shih-Han Chan , Quanshi Zhang

The operad of moulds is realized in terms of an operational calculus of formal integrals (continuous formal power series). This leads to many simplifications and to the discovery of various suboperads. In particular, we prove a conjecture…

Quantum Algebra · Mathematics 2007-10-18 Frédéric Chapoton , Florent Hivert , Jean-Christophe Novelli , Jean-Yves Thibon

The ubiquity of neural networks (NNs) in real-world applications, from healthcare to natural language processing, underscores their immense utility in capturing complex relationships within high-dimensional data. However, NNs come with…

Machine Learning · Computer Science 2024-07-08 Chang Yue , Niraj K. Jha

Spiking neural networks (SNNs) have closer dynamics to the brain than current deep neural networks. Their low power consumption and sample efficiency make these networks interesting. Recently, several deep convolutional spiking neural…

Computer Vision and Pattern Recognition · Computer Science 2022-11-01 Shahriar Rezghi Shirsavar , Mohammad-Reza A. Dehaqani

Monotonic neural networks have recently been proposed as a way to define invertible transformations. These transformations can be combined into powerful autoregressive flows that have been shown to be universal approximators of continuous…

Machine Learning · Computer Science 2021-04-01 Antoine Wehenkel , Gilles Louppe

In this paper we systematically explore questions of succinctness in modal logics employed in spatial reasoning. We show that the closure operator, despite being less expressive, is exponentially more succinct than the limit-point operator,…

Logic · Mathematics 2017-08-15 David Fernández-Duque , Petar Iliev

Tunable mechanics and fracture resistance are hallmarks of biological tissues and highly desired in engineered materials. To elucidate the underlying mechanisms, we study a rigidly percolating double network (DN) made of a stiff and a…

Soft Condensed Matter · Physics 2020-08-25 Pancy Lwin , Andrew Sindermann , Leo Sutter , Thomas Wyse Jackson , Lawrence Bonassar , Itai Cohen , Moumita Das

Despite multiple efforts made towards adopting complex-valued deep neural networks (DNNs), it remains an open question whether complex-valued DNNs are generally more effective than real-valued DNNs for monaural speech enhancement. This work…

Sound · Computer Science 2023-01-12 Haibin Wu , Ke Tan , Buye Xu , Anurag Kumar , Daniel Wong

I shall describe a general model-theoretic task to construct expansions of pseudofinite structures and discuss several examples of particular relevance to computational complexity. Then I will present one specific situation where finding a…

Logic · Mathematics 2017-02-10 Jan Krajicek

Children possess the ability to learn multiple cognitive tasks sequentially, which is a major challenge toward the long-term goal of artificial general intelligence. Existing continual learning frameworks are usually applicable to Deep…

Artificial Intelligence · Computer Science 2023-08-10 Bing Han , Feifei Zhao , Yi Zeng , Wenxuan Pan , Guobin Shen

We define a pair of simple combinatorial operations on subshifts, called existential and universal extensions, and study their basic properties. We prove that the existential extension of a sofic shift by another sofic shift is always…

Dynamical Systems · Mathematics 2014-07-24 Ilkka Törmä

Logics closed under classes of substitutions broader than class of uniform substitutions are known as hyperformal logics. This paper extends known results about hyperformal logics in two ways. First: we examine a very powerful form of…

Logic · Mathematics 2026-04-28 Shay Allen Logan , Blane Worley

Spiking neural networks (SNNs) can be used in low-power and embedded systems (such as emerging neuromorphic chips) due to their event-based nature. Also, they have the advantage of low computation cost in contrast to conventional artificial…

Computer Vision and Pattern Recognition · Computer Science 2021-01-20 Ali Samadzadeh , Fatemeh Sadat Tabatabaei Far , Ali Javadi , Ahmad Nickabadi , Morteza Haghir Chehreghani

The paper proposes the use of structured neural networks for reinforcement learning based nonlinear adaptive control. The focus is on partially observable systems, with separate neural networks for the state and feedforward observer and the…

Systems and Control · Electrical Eng. & Systems 2023-04-21 Ruoqi Zhang , Per Mattson , Torbjörn Wigren

Structured State-Space Duality (SSD) [Dao & Gu, ICML 2024] is an equivalence between a simple Structured State-Space Model (SSM) and a masked attention mechanism. In particular, a state-space model with a scalar-times-identity state matrix…

Machine Learning · Computer Science 2025-12-24 Jerry Yao-Chieh Hu , Xiwen Zhang , Ali ElSheikh , Weimin Wu , Han Liu

Differentiable Neural Computers (DNCs) were introduced as recurrent architectures equipped with an addressable external memory supporting differentiable read and write operations. Transformers, in contrast, are nominally feedforward…

Computation and Language · Computer Science 2026-03-23 Bo Tang , Weiwei Xie

Emergence of deep neural networks (DNNs) has raised enormous attention towards artificial neural networks (ANNs) once again. They have become the state-of-the-art models and have won different machine learning challenges. Although these…

Neural and Evolutionary Computing · Computer Science 2022-12-09 Shahriar Rezghi Shirsavar , Abdol-Hossein Vahabie , Mohammad-Reza A. Dehaqani

The best current methods for exactly computing the number of satisfying assignments, or the satisfying probability, of Boolean formulas can be seen, either directly or indirectly, as building 'decision-DNNF' (decision decomposable negation…

Databases · Computer Science 2013-09-27 Paul Beame , Jerry Li , Sudeepa Roy , Dan Suciu