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A systematic way of defining variants of a modeling language is useful for adapting the language to domain or project specific needs. Variants can be obtained by adapting the syntax or semantics of the language. In this paper, we take a…

Software Engineering · Computer Science 2014-09-24 Hans Grönninger , Bernhard Rumpe

Dynamical sampling deals with signals that evolve in time under the action of a linear operator. The purpose of the present paper is to analyze the performance of the basic dynamical sampling algorithms in the finite dimensional case and…

Numerical Analysis · Mathematics 2018-10-16 Akram Aldroubi , Longxiu Huang , Ilya Krishtal , Akos Ledeczi , Roy R. Lederman , Peter Volgyesi

Semantics, morphology and syntax are strongly interdependent. However, the majority of computational methods for semantic change detection use distributional word representations which encode mostly semantics. We investigate an alternative…

Computation and Language · Computer Science 2021-09-23 Mario Giulianelli , Andrey Kutuzov , Lidia Pivovarova

We consider two graph models of semantic change. The first is a time-series model that relates embedding vectors from one time period to embedding vectors of previous time periods. In the second, we construct one graph for each word: nodes…

Computation and Language · Computer Science 2017-04-11 Steffen Eger , Alexander Mehler

Finding features that disentangle the different causes of variation in real data is a difficult task, that has nonetheless received considerable attention in static domains like natural images. Interactive environments, in which an agent…

Machine Learning · Computer Science 2017-03-23 Emmanuel Bengio , Valentin Thomas , Joelle Pineau , Doina Precup , Yoshua Bengio

When modeling an application of practical relevance as an instance of a combinatorial problem X, we are often interested not merely in finding one optimal solution for that instance, but in finding a sufficiently diverse collection of good…

Data Structures and Algorithms · Computer Science 2026-02-19 Julien Baste , Michael R. Fellows , Lars Jaffke , Tomáš Masařík , Mateus de Oliveira Oliveira , Geevarghese Philip , Frances A. Rosamond

Syntactic structures used to play a vital role in natural language processing (NLP), but since the deep learning revolution, NLP has been gradually dominated by neural models that do not consider syntactic structures in their design. One…

Computation and Language · Computer Science 2023-11-28 Haoyi Wu , Kewei Tu

This paper is a preliminary work to address the problem of dynamical systems with parameters varying in time. An idea to predict their behaviour is proposed. These systems are called \emph{transient systems}, and are distinguished from…

Dynamical Systems · Mathematics 2014-11-04 Ugo Galvanetto , Luca Magri

Context-free graph grammars have shown a remarkable ability to model structures in real-world relational data. However, graph grammars lack the ability to capture time-changing phenomena since the left-to-right transitions of a production…

Machine Learning · Computer Science 2023-03-23 Daniel Gonzalez Cedre , Justus Isaiah Hibshman , Timothy La Fond , Grant Boquet , Tim Weninger

The Folksodriven framework makes it possible for data scientists to define an ontology environment where searching for buried patterns that have some kind of predictive power to build predictive models more effectively. It accomplishes this…

Information Retrieval · Computer Science 2017-01-02 Massimiliano Dal Mas

In this paper, a new approach to string dynamics is proposed. String coordinates are identified with a non-commuting set of operators familiar from free string quantization, and the dynamics follows from the Virasoro algebra. There is a…

High Energy Physics - Theory · Physics 2014-11-18 Korkut Bardakci

In some contexts, well-formed natural language cannot be expected as input to information or communication systems. In these contexts, the use of grammar-independent input (sequences of uninflected semantic units like e.g.…

Computation and Language · Computer Science 2007-05-23 Pascal Vaillant

Disentangling the encodings of neural models is a fundamental aspect for improving interpretability, semantic control and downstream task performance in Natural Language Processing. Currently, most disentanglement methods are unsupervised…

Computation and Language · Computer Science 2023-02-17 Danilo S. Carvalho , Giangiacomo Mercatali , Yingji Zhang , Andre Freitas

Dynamic treatment regimes or policies are a sequence of decision functions over multiple stages that are tailored to individual features. One important class of treatment policies in practice, namely multi-stage stationary treatment…

Machine Learning · Statistics 2025-01-09 Daiqi Gao , Yufeng Liu , Donglin Zeng

Traditional sentiment analysis has long been a unimodal task, relying solely on text. This approach overlooks non-verbal cues such as vocal tone and prosody that are essential for capturing true emotional intent. We introduce Dynamic…

Computation and Language · Computer Science 2025-09-30 Sadia Abdulhalim , Muaz Albaghdadi , Moshiur Farazi

Despite the surging demands for multilingual task-oriented dialog systems (e.g., Alexa, Google Home), there has been less research done in multilingual or cross-lingual scenarios. Hence, we propose a zero-shot adaptation of task-oriented…

Computation and Language · Computer Science 2019-11-12 Zihan Liu , Jamin Shin , Yan Xu , Genta Indra Winata , Peng Xu , Andrea Madotto , Pascale Fung

There is much interest in providing probabilistic semantics for defaults but most approaches seem to suffer from one of two problems: either they require numbers, a problem defaults were intended to avoid, or they generate peculiar side…

Artificial Intelligence · Computer Science 2013-04-10 Eric Neufeld , David L Poole

We study existence and uniqueness of the fixed points solutions of a large class of non-linear variable discounted transfer operators associated to a sequential decision-making process. We establish regularity properties of these solutions,…

Dynamical Systems · Mathematics 2019-02-20 L. Cioletti , Elismar R. Oliveira

Tracking and collecting fast-evolving online discussions provides vast data for studying social media usage and its role in people's public lives. However, collecting social media data using a static set of keywords fails to satisfy the…

Social and Information Networks · Computer Science 2021-02-26 Maya Srikanth , Anqi Liu , Nicholas Adams-Cohen , Jian Cao , R. Michael Alvarez , Anima Anandkumar

Dynamic topic modeling is widely used to analyze evolving trends in scientific literature, medical records, and social media. Traditional topic models represent each topic through a single probability vector on the multinomial simplex and…

Machine Learning · Computer Science 2026-05-28 Hanjia Gao , Hanwen Ye , Qing Nie , Annie Qu