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We propose a new coding scheme, called the delayed coding (DC) scheme, for channels with insertion, deletion, and substitution (IDS) errors. The proposed scheme employs delayed encoding and non-iterative detection and decoding strategies to…

Information Theory · Computer Science 2022-05-25 Ryo Shibata , Hiroyuki Yashima

Inspired by the facts that retinal cells actually segregate the visual scene into different attributes (e.g., spatial details, temporal motion) for respective neuronal processing, we propose to first decompose the input video into…

Computer Vision and Pattern Recognition · Computer Science 2024-01-17 Ming Lu , Tong Chen , Dandan Ding , Fengqing Zhu , Zhan Ma

Many correct-by-construction control synthesis methods suffer from the curse of dimensionality. Motivated by this challenge, we seek to reduce a correct-by-construction control synthesis problem to subproblems of more modest dimension. As a…

Systems and Control · Computer Science 2015-10-13 Petter Nilsson , Necmiye Ozay

Large optimization problems with hard constraints arise in many settings, yet classical solvers are often prohibitively slow, motivating the use of deep networks as cheap "approximate solvers." Unfortunately, naive deep learning approaches…

Machine Learning · Computer Science 2021-04-27 Priya L. Donti , David Rolnick , J. Zico Kolter

Blind source separation, particularly through independent component analysis (ICA), is widely utilized across various signal processing domains for disentangling underlying components from observed mixed signals, owing to its fully…

Methodology · Statistics 2026-01-06 Qiang Li , Shujian Yu , Liang Ma , Chen Ma , Jingyu Liu , Tulay Adali , Vince D. Calhoun

Most existing sequence labelling models rely on a fixed decomposition of a target sequence into a sequence of basic units. These methods suffer from two major drawbacks: 1) the set of basic units is fixed, such as the set of words,…

Computation and Language · Computer Science 2017-08-15 Hairong Liu , Zhenyao Zhu , Xiangang Li , Sanjeev Satheesh

The difficulty of manually specifying reward functions has led to an interest in using linear temporal logic (LTL) to express objectives for reinforcement learning (RL). However, LTL has the downside that it is sensitive to small…

Logic in Computer Science · Computer Science 2023-05-31 Rajeev Alur , Osbert Bastani , Kishor Jothimurugan , Mateo Perez , Fabio Somenzi , Ashutosh Trivedi

Automatic synthesis of hardware components from declarative specifications is an ambitious endeavor in computer aided design. Existing synthesis algorithms are often implemented with Binary Decision Diagrams (BDDs), inheriting their…

Logic in Computer Science · Computer Science 2013-11-15 Roderick Bloem , Robert Koenighofer , Martina Seidl

This paper develops a closed-form spectral decomposition framework for the Gramian matrices of discrete-time linear dynamical systems. The main results provide explicit decompositions of the discrete-time controllability Gramian and its…

Optimization and Control · Mathematics 2026-04-02 Alexey Iskakov

In this paper, we introduce a data-driven framework for synthesis of provably-correct controllers for general nonlinear switched systems under complex specifications. The focus is on systems with unknown disturbances whose effects on the…

Systems and Control · Electrical Eng. & Systems 2024-06-17 Ibon Gracia , Dimitris Boskos , Luca Laurenti , Morteza Lahijanian

This paper provides a formal econometric framework behind the newly developed difference-in-discontinuities design (DiDC). Despite its increasing use in applied research, there are currently limited studies of its properties. We formalize…

Econometrics · Economics 2026-01-28 Pedro Picchetti , Cristine C. X. Pinto , Stephanie T. Shinoki

DC has proved to be a promising tool for the specification and verification of functional requirements on the design of hard real-time systems. Many works were devoted to develop effective techniques for checking the models of hard…

Logic in Computer Science · Computer Science 2012-12-18 Changil Choe , Dang Van Hung , Song Han

Determinantal point processes (DPPs) enable the modeling of repulsion: they provide diverse sets of points. The repulsion is encoded in a kernel $K$ that can be seen as a matrix storing the similarity between points. The diversity comes…

Machine Learning · Statistics 2021-02-24 Claire Launay , Bruno Galerne , Agnès Desolneux

Variance reduction techniques have been successfully applied to temporal-difference (TD) learning and help to improve the sample complexity in policy evaluation. However, the existing work applied variance reduction to either the less…

Machine Learning · Computer Science 2023-05-23 Shaocong Ma , Yi Zhou , Shaofeng Zou

Linear Temporal Logic (LTL) is the standard specification language for reactive systems and is successfully applied in industrial settings. However, many shortcomings of LTL have been identified in the literature, among them the limited…

Logic in Computer Science · Computer Science 2021-04-30 Daniel Neider , Alexander Weinert , Martin Zimmermann

Definite descriptions are expressions of the form "the unique $x$ satisfying property $C$," which allow reference to objects through their distinguishing characteristics. They play a crucial role in ontology and query languages, offering an…

Logic in Computer Science · Computer Science 2025-12-09 Michał Sochański , Przemysław Andrzej Wałęga , Michał Zawidzki

Recently, data collaboration (DC) analysis has been developed for privacy-preserving integrated analysis across multiple institutions. DC analysis centralizes individually constructed dimensionality-reduced intermediate representations and…

Machine Learning · Computer Science 2022-08-29 Akira Imakura , Masateru Kihira , Yukihiko Okada , Tetsuya Sakurai

The verification and validation of cyber-physical systems is known to be a difficult problem due to the different modeling abstractions used for control components and for software components. A recent trend to address this difficulty is to…

Logic in Computer Science · Computer Science 2010-10-28 Pritam Roy , Paulo Tabuada , Rupak Majumdar

When performing reasoning tasks with user-specific requirements, such as strict output formats, large language models (LLMs) often prioritize reasoning over adherence to detailed instructions. Fine-tuning LLMs on supervised datasets to…

Computation and Language · Computer Science 2025-10-21 Yiqi Li , Yusheng Liao , Zhe Chen , Yanfeng Wang , Yu Wang

Text-to-SQL is an important task that helps people obtain information from databases by automatically generating SQL queries. Considering the brilliant performance, approaches based on Large Language Models (LLMs) become the mainstream for…

Computation and Language · Computer Science 2024-08-28 Dingzirui Wang , Longxu Dou , Xuanliang Zhang , Qingfu Zhu , Wanxiang Che