Scheme (mathematics)
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Adversarial Examples for Evaluating Reading Comprehension Systems Open
Standard accuracy metrics indicate that reading comprehension systems are making rapid progress, but the extent to which these systems truly understand language remains unclear. To reward systems with real language understanding abilities,…
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Co-Occurrence Feature Learning for Skeleton Based Action Recognition Using Regularized Deep LSTM Networks Open
Skeleton based action recognition distinguishes human actions using the trajectories of skeleton joints, which provide a very good representation for describing actions. Considering that recurrent neural networks (RNNs) with Long Short-Ter…
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ProteinBERT: a universal deep-learning model of protein sequence and function Open
Summary Self-supervised deep language modeling has shown unprecedented success across natural language tasks, and has recently been repurposed to biological sequences. However, existing models and pretraining methods are designed and optim…
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Joint Extraction of Entities and Relations Based on a Novel Tagging Scheme Open
Joint extraction of entities and relations is an important task in information extraction. To tackle this problem, we firstly propose a novel tagging scheme that can convert the joint extraction task to a tagging problem.. Then, based on o…
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Privacy-Preserving Traffic Flow Prediction: A Federated Learning Approach Open
Existing traffic flow forecasting approaches by deep learning models achieve excellent success based on a large volume of datasets gathered by governments and organizations. However, these datasets may contain lots of user's private data, …
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Kramers–Kronig coherent receiver Open
The interest for short-reach links of the kind needed for inter-data-center communications has fueled in recent years the search for transmission schemes that are simultaneously highly performing and cost effective. In this work we propose…
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Few-Shot Unsupervised Image-to-Image Translation Open
Unsupervised image-to-image translation methods learn to map images in a given class to an analogous image in a different class, drawing on unstructured (non-registered) datasets of images. While remarkably successful, current methods requ…
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Toward Secure Blockchain-Enabled Internet of Vehicles: Optimizing Consensus Management Using Reputation and Contract Theory Open
In the Internet of Vehicles (IoV), data sharing among vehicles is critical for improving driving safety and enhancing vehicular services. To ensure security and traceability of data sharing, existing studies utilize efficient delegated pro…
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Simple and Accurate Dependency Parsing Using Bidirectional LSTM Feature Representations Open
We present a simple and effective scheme for dependency parsing which is based on bidirectional-LSTMs (BiLSTMs). Each sentence token is associated with a BiLSTM vector representing the token in its sentential context, and feature vectors a…
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MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks on Corrupted Labels Open
Recent deep networks are capable of memorizing the entire data even when the labels are completely random. To overcome the overfitting on corrupted labels, we propose a novel technique of learning another neural network, called MentorNet, …
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Secure Attribute-Based Signature Scheme With Multiple Authorities for Blockchain in Electronic Health Records Systems Open
Electronic Health Records (EHRs) are entirely controlled by hospitals instead of patients, which complicates seeking medical advices from different hospitals. Patients face a critical need to focus on the details of their own healthcare an…
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Decision Tree and SVM-Based Data Analytics for Theft Detection in Smart Grid Open
Nontechnical losses, particularly due to electrical theft, have been a major concern in power system industries for a long time. Large-scale consumption of electricity in a fraudulent manner may imbalance the demand-supply gap to a great e…
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A climate model projection weighting scheme accounting for performance and interdependence Open
Uncertainties of climate projections are routinely assessed by considering simulations from different models. Observations are used to evaluate models, yet there is a debate about whether and how to explicitly weight model projections by a…
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Z‐Scheme Photocatalytic Systems for Solar Water Splitting Open
As the world decides on the next giant step for the renewable energy revolution, scientists have begun to reinforce their headlong dives into the exploitation of solar energy. Hitherto, numerous attempts are made to imitate the natural pho…
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Communication-Efficient On-Device Machine Learning: Federated Distillation and Augmentation under Non-IID Private Data Open
On-device machine learning (ML) enables the training process to exploit a massive amount of user-generated private data samples. To enjoy this benefit, inter-device communication overhead should be minimized. With this end, we propose fede…
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Secure Signature-Based Authenticated Key Establishment Scheme for Future IoT Applications Open
Internet of Things (IoT) is a network of all devices that can be accessed through the Internet. These devices can be remotely accessed and controlled using existing network infrastructure, thus allowing a direct integration of computing sy…
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Predict then Propagate: Graph Neural Networks meet Personalized PageRank Open
Neural message passing algorithms for semi-supervised classification on graphs have recently achieved great success. However, for classifying a node these methods only consider nodes that are a few propagation steps away and the size of th…
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Private federated learning on vertically partitioned data via entity resolution and additively homomorphic encryption Open
Consider two data providers, each maintaining private records of different feature sets about common entities. They aim to learn a linear model jointly in a federated setting, namely, data is local and a shared model is trained from locall…
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TPLinker: Single-stage Joint Extraction of Entities and Relations Through Token Pair Linking Open
Extracting entities and relations from unstructured text has attracted increasing attention in recent years but remains challenging, due to the intrinsic difficulty in identifying overlapping relations with shared entities. Prior works sho…
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Battery State Estimation for a Single Particle Model With Electrolyte Dynamics Open
International audience
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Detecting Ponzi Schemes on Ethereum Open
Blockchain technology becomes increasingly popular. It also attracts scams, for example, Ponzi scheme, a classic fraud, has been found making a notable amount of money on Blockchain, which has a very negative impact. To help dealing with t…
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Voronoi-Based Multi-Robot Autonomous Exploration in Unknown Environments via Deep Reinforcement Learning Open
Autonomous exploration is an important application of multi-vehicle systems, where a team of networked robots are coordinated to explore an unknown environment collaboratively. This technique has earned significant research interest due to…
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From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic Review on Evaluating Explainable AI Open
The rising popularity of explainable artificial intelligence (XAI) to understand high-performing black boxes raised the question of how to evaluate explanations of machine learning (ML) models. While interpretability and explainability are…
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Parsing Argumentation Structures in Persuasive Essays Open
In this article, we present a novel approach for parsing argumentation structures. We identify argument components using sequence labeling at the token level and apply a new joint model for detecting argumentation structures. The proposed …
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Hierarchical federated learning across heterogeneous cellular networks Open
We consider federated edge learning (FEEL), where mobile users (MUs) collaboratively learn a global model by sharing local updates on the model parameters rather than their datasets, with the help of a mobile base station (MBS). We optimiz…
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Automatic Target Recognition in Synthetic Aperture Radar Imagery: A State-of-the-Art Review Open
The purpose of this paper is to survey and assess the state-of-the-art in automatic target recognition for synthetic aperture radar imagery (SAR-ATR). The aim is not to develop an exhaustive survey of the voluminous literature, but rather …
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A motivational game-theoretic approach for peer-to-peer energy trading in the smart grid Open
Peer-to-peer trading in energy networks is expected to be exclusively conducted by the prosumers of the network with negligible influence from the grid. This raises the critical question: how can enough prosumers be encouraged to participa…
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Generalizing to Unseen Domains via Adversarial Data Augmentation Open
We are concerned with learning models that generalize well to different \emph{unseen} domains. We consider a worst-case formulation over data distributions that are near the source domain in the feature space. Only using training data from…
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Lightweight and Privacy-Preserving Two-Factor Authentication Scheme for IoT Devices Open
Device authentication is an essential security feature for Internet of Things (IoT). Many IoT devices are deployed in the open and public places, which makes them vulnerable to physical and cloning attacks. Therefore, any authentication pr…
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Measuring Fairness in Ranked Outputs Open
Ranking and scoring are ubiquitous. We consider the setting in which an institution, called a ranker, evaluates a set of individuals based on demographic, behavioral or other characteristics. The final output is a ranking that represents t…