Related publications (35)

Modeling Structured Data in Attention-based Models

Alireza Mohammadshahi

Natural language processing has experienced significant improvements with the development of Transformer-based models, which employ self-attention mechanism and pre-training strategies. However, these models still present several obstacles. A notable issue ...
EPFL2023

Interpreting Rhythm as Parsing: Syntactic-Processing Operations Predict the Migration of Visual Flashes as Perceived During Listening to Musical Rhythms

Martin Alois Rohrmeier, Steffen Alexander Herff, Gabriele Cecchetti

Music can be interpreted by attributing syntactic relationships to sequential musical events, and, computationally, such musical interpretation represents an analogous combinatorial task to syntactic processing in language. While this perspective has been ...
Hoboken2023

Fast Adversarial Training With Adaptive Step Size

Sabine Süsstrunk, Mathieu Salzmann, Chen Liu, Zhuoyi Huang, Yong Zhang, Jue Wang

While adversarial training and its variants have shown to be the most effective algorithms to defend against adversarial attacks, their extremely slow training process makes it hard to scale to large datasets like ImageNet. The key idea of recent works to ...
Piscataway2023

Neural substrates of psychosis revealed by altered dependencies between brain activity and white-matter architecture in individuals with 22q11 deletion syndrome

Dimitri Nestor Alice Van De Ville, Maria Giulia Preti, Farnaz Delavari, Karin Bortolin, Emeline Mullier

Background: Dysconnectivity has been consistently proposed as a major key mechanism in psychosis. Indeed, disruptions in large-scale structural and functional brain networks have been associated with psychotic symptoms. However, brain activity is largely c ...
ELSEVIER SCI LTD2022

Dynamic Personalized Ranking

Jérémie Rappaz

Personalized ranking methods are at the core of many systems that learn to produce recommendations from user feedbacks. Their primary objective is to identify relevant items from very large vocabularies and to assist users in discovering new content. These ...
EPFL2022

The influence of chemical composition, aerosol acidity, and metal dissolution on the oxidative potential of fine particulate matter and redox potential of the lung lining fluid

Athanasios Nenes, Andrea Mario Arangio

Air pollution is a major environmental health risk and it contributes to respiratory and cardiovascular diseases and excess mortality worldwide. The adverse health effects have been associated with the inhalation of fine particulate matter (PM2.5) and indu ...
PERGAMON-ELSEVIER SCIENCE LTD2021

Recursive Non-Autoregressive Graph-to-Graph Transformer for Dependency Parsing with Iterative Refinement

James Henderson, Alireza Mohammadshahi

We propose the Recursive Non-autoregressive Graph-to-graph Transformer architecture (RNG-Tr) for the iterative refinement of arbitrary graphs through the recursive application of a non-autoregressive Graph-to-Graph Transformer and apply it to syntactic dep ...
2020

High gamma response tracks different syntactic structures in homophonous phrases

Silvestro Micera, Fiorenzo Artoni

Syntax is a species-specific component of human language combining a finite set of words in a potentially infinite number of sentences. Since words are by definition expressed by sound, factoring out syntactic information is normally impossible. Here, we c ...
NATURE PUBLISHING GROUP2020

Query-driven Repair of Functional Dependency Violations

Anastasia Ailamaki, Manolis Karpathiotakis, Styliani Asimina Giannakopoulou

Data cleaning is a time-consuming process that depends on the data analysis that users perform. Existing solutions treat data cleaning as a separate offline process that takes place before analysis begins. Applying data cleaning before analysis assumes a p ...
IEEE COMPUTER SOC2020

Graph-to-Graph Transformer for Transition-based Dependency Parsing

James Henderson, Alireza Mohammadshahi

We propose the Graph2Graph Transformer architecture for conditioning on and predicting arbitrary graphs, and apply it to the challenging task of transition-based dependency parsing. After proposing two novel Transformer models of transition-based dependenc ...
Association for Computational Linguistics2020

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