COVID-Twitter-BERT: A natural language processing model to analyse COVID-19 content on Twitter

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This paper investigates the presence of OCR-sensitive neurons within the Transformer architecture and their influence on named entity recognition (NER) performance on historical documents. By analysing neuron activation patterns in response to clean and no ...

The success of self-supervised learning in computer vision and natural language processing has motivated pretraining methods on tabular data. However, most existing tabular self-supervised learning models fail to leverage information across multiple data t ...

We propose two deep learning models that fully automate shape parameterization for aerodynamic shape optimization. Both models are optimized to parameterize via deep geometric learning to embed human prior knowledge into learned geometric patterns, elimina ...

Graphs processing has become an important part of various areas of computing, including machine learning, medical applications, social network analysis, computational sciences, and others. A growing amount of the associated graph processing workloads are d ...

Modular robots (MRs) consist of unique robots which interconnect and work as a collective to perform objectives. Coordinating these robots rely on robust communication, as modules moving independently can lead to damaging behaviour. We present a robust str ...

We consider distributed optimization over several devices, each sending incremental model updates to a central server. This setting is considered, for instance, in federated learning. Various schemes have been designed to compress the model updates in orde ...

Learning how to reach a reward over long series of actions is a remarkable capability of humans, and potentially guided by multiple parallel learning modules. Current brain imaging of learning modules is limited by (i) simple experimental paradigms, (ii) e ...

The defective regimes in metal-based Laser Powder Bed Fusion (LPBF) processes can be minimized by deploying in-situ monitoring strategies comprising Machine learning (ML) algorithms and sensing techniques. So far, algorithms trained for monitoring a partic ...

Many blockchain-based algorithms, such as Bitcoin, implement a decentralized asset transfer system, often referred to as a cryptocurrency. As stated in the original paper by Nakamoto, at the heart of these systems lies the problem of preventing double-spen ...

We present a bootstrapping procedure for the full-RNS variant of the approximate homomorphic-encryption scheme of Cheon et al., CKKS (Asiacrypt 17, SAC 18). Compared to the previously proposed procedures (Eurocrypt 18 & 19, CT-RSA 20), our bootstrapping pr ...

Entity linking is an important problem with many applications. Most previous solutions were designed for settings where annotated training data is available, which is, however, not the case in numerous domains. We propose a light-weight and scalable entity ...

We present a method for making neural network predictions robust to shifts from the training data distribution. The proposed method is based on making predictions via a diverse set of cues (called 'middle domains') and ensembling them into one strong predi ...

Due to its convenience, biometric authentication, especial face authentication, has become increasingly mainstream and thus is now a prime target for attackers. Presentation attacks and face morphing are typical types of attack. Previous research has shown ...

While phi-divergences have been extensively studied in convex analysis, their use in optimization problems often remains challenging. In this regard, one of the main shortcomings of existing methods is that the minimization of phi-divergences is usually pe ...

Humans use a variety of modifiers to enrich communications with one another. While this is a deliberate subtlety in our language, the presence of modifiers can cause problems for emotion analysis by machines. Our research objective is to understand and com ...

COVID-Twitter-BERT: A natural language processing model to analyse COVID-19 content on Twitter

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Investigating OCR-Sensitive Neurons to Improve Entity Recognition in Historical Documents

XTab: Cross-table Pretraining for Tabular Transformers

Automatic Parameterization for Aerodynamic Shape Optimization via Deep Geometric Learning

Practice of Streaming Processing of Dynamic Graphs: Concepts, Models, and Systems

Modular robot networking: a novel schema and its performance assessment

Stochastic distributed learning with gradient quantization and double-variance reduction

Brain signals of a Surprise-Actor-Critic model: Evidence for multiple learning modules in human decision making

Deep transfer learning of additive manufacturing mechanisms across materials in metal-based laser powder bed fusion process

The consensus number of a cryptocurrency (extended version)

Efficient Bootstrapping for Approximate Homomorphic Encryption with Non-sparse Keys

Low-Rank Subspaces for Unsupervised Entity Linking

Robustness via Cross-Domain Ensembles

Generating Master Faces for Use in PerformingWolf Attacks on Face Recognition Systems

Proximity Operators of Discrete Information Divergences

Modeling the Impact of Modifiers on Emotional Statements