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Event extraction involves the detection and extraction of both the event triggers and corresponding event arguments. Existing systems often decompose event extraction into multiple subtasks, without considering their possible interactions.…

Computation and Language · Computer Science 2022-10-18 Huiling You , David Samuel , Samia Touileb , Lilja Øvrelid

This volume contains selected papers presented at the 9th International Workshop on Reduction Strategies in Rewriting and Programming, WRS2009, which was held in Brasilia on the 28th June 2009, associated to RTA 2009 (the 20th International…

Programming Languages · Computer Science 2010-01-27 Maribel Fernández

This volume contains the proceedings of the 7th Workshop on Security Issues in Concurrency (SecCo'09). The workshop was held in Bologna, Italy on September 5th 2009, as a satellite workshop of CONCUR'09. The aim of the SecCo workshop series…

Cryptography and Security · Computer Science 2009-10-26 Michele Boreale , Steve Kremer

The proceedings of the 7th International Workshop on Symbolic-Numeric Methods for Reasoning about CPS and IoT (SNR 2021) feature five peer-reviewed contributions and three invited talks. SNR focuses on the combination of symbolic and…

Symbolic Computation · Computer Science 2022-07-12 Anne Remke , Dung Hoang Tran

This volume contains the proceedings of DCM 2015, the 11th International Workshop on Developments in Computational Models held on October 28, 2015 in Cali, Colombia. DCM 2015 was organized as a one-day satellite event of the 12th…

Logic in Computer Science · Computer Science 2016-03-03 César A. Muñoz , Jorge A. Pérez

Graph representation learning (also known as network embedding) has been extensively researched with varying levels of granularity, ranging from nodes to graphs. While most prior work in this area focuses on node-level representation,…

Machine Learning · Computer Science 2023-06-05 Lili Wang , Chenghan Huang , Weicheng Ma , Xinyuan Cao , Soroush Vosoughi

In this extended abstract, we present a simple approach to convergence on term graphs that allows us to unify term graph rewriting and infinitary term rewriting. This approach is based on a partial order and a metric on term graphs. These…

Logic in Computer Science · Computer Science 2013-02-27 Patrick Bahr

The notion of continuation is ubiquitous in many different areas of computer science, including systems programming, programming languages, algorithmics, semantics, logic, and constructive mathematics. In fact the concept of continuation…

Programming Languages · Computer Science 2016-06-21 Olivier Danvy , Ugo de'Liguoro

This volume contains the proceedings of MARS 2022, the fifth workshop on Models for Formal Analysis of Real Systems, held as part of ETAPS 2022, the European Joint Conferences on Theory and Practice of Software. The MARS workshops bring…

Logic in Computer Science · Computer Science 2022-03-18 Clemens Dubslaff , Bas Luttik

Skip-gram (word2vec) is a recent method for creating vector representations of words ("distributed word representations") using a neural network. The representation gained popularity in various areas of natural language processing, because…

Computation and Language · Computer Science 2020-07-09 Tom Kocmi , Ondřej Bojar

This volume contains the proceedings of MARS 2020, the fourth workshop on Models for Formal Analysis of Real Systems held as part of ETAPS 2020, the European Joint Conferences on Theory and Practice of Software. The MARS workshop brings…

Logic in Computer Science · Computer Science 2020-04-28 Ansgar Fehnker , Hubert Garavel

This volume contains the formal proceedings of the 4th International Workshop on Rewriting Techniques for Program Transformations and Evaluation (WPTE 2017), held on 8th September 2017 in Oxford, United Kingdom, and affiliated with the…

Logic in Computer Science · Computer Science 2018-02-19 Horatiu Cirstea , David Sabel

Graph neural networks have emerged as a powerful tool for graph representation learning, but their performance heavily relies on abundant task-specific supervision. To reduce labeling requirement, the "pre-train, prompt" paradigms have…

Machine Learning · Computer Science 2024-08-27 Xingtong Yu , Zhenghao Liu , Yuan Fang , Zemin Liu , Sihong Chen , Xinming Zhang

Recomputation algorithms collectively refer to a family of methods that aims to reduce the memory consumption of the backpropagation by selectively discarding the intermediate results of the forward propagation and recomputing the discarded…

Machine Learning · Computer Science 2019-05-29 Mitsuru Kusumoto , Takuya Inoue , Gentaro Watanabe , Takuya Akiba , Masanori Koyama

Graph reordering is a powerful technique to increase the locality of the representations of graphs, which can be helpful in several applications. We study how the technique can be used to improve compression of graphs and inverted indexes.…

Data Structures and Algorithms · Computer Science 2017-09-04 Laxman Dhulipala , Igor Kabiljo , Brian Karrer , Giuseppe Ottaviano , Sergey Pupyrev , Alon Shalita

This volume contains the proceedings of FOCLASA 2014, the 13th International Workshop on the Foundations of Coordination Languages and Self-Adaptive Systems. FOCLASA 2014 was held in Rome, Italy, on September 9, 2014 as a satellite event of…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-02-12 Javier Cámara , José Proença

This volume contains the proceedings of the International Workshop on Developments in Implicit Computational complExity (DICE 2010), which took place on March 27-28 2010 in Paphos, Cyprus, as a satellite event of the Joint European…

Logic in Computer Science · Computer Science 2010-05-20 Patrick Baillot

Machine learning on graphs is an important and ubiquitous task with applications ranging from drug design to friendship recommendation in social networks. The primary challenge in this domain is finding a way to represent, or encode, graph…

Social and Information Networks · Computer Science 2018-04-11 William L. Hamilton , Rex Ying , Jure Leskovec

The aim of the workshop series Developments in Computational Models (DCM) is to bring together researchers who are currently developing new computational models or new features for traditional computational models, in order to foster their…

Logic in Computer Science · Computer Science 2014-04-01 Benedikt Löwe , Glynn Winskel

Recent work has utilised knowledge-aware approaches to natural language understanding, question answering, recommendation systems, and other tasks. These approaches rely on well-constructed and large-scale knowledge graphs that can be…

Computation and Language · Computer Science 2023-03-09 Tin Kuculo
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