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08/03/2023
Is GPT-4 a reliable rater? Evaluating Consistency in GPT-4 Text Ratings
This study investigates the consistency of feedback ratings generated by...
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07/13/2023
GRAN is superior to GraphRNN: node orderings, kernel- and graph embeddings-based metrics for graph generators
A wide variety of generative models for graphs have been proposed. They ...
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04/26/2023
Impact of Position Bias on Language Models in Token Classification
Language Models (LMs) have shown state-of-the-art performance in Natural...
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03/07/2023
German BERT Model for Legal Named Entity Recognition
The use of BERT, one of the most popular language models, has led to imp...
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09/12/2022
SmartKex: Machine Learning Assisted SSH Keys Extraction From The Heap Dump
Digital forensics is the process of extracting, preserving, and document...
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04/11/2022
The Importance of Future Information in Credit Card Fraud Detection
Fraud detection systems (FDS) mainly perform two tasks: (i) real-time de...
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11/12/2021
deepstruct – linking deep learning and graph theory
deepstruct connects deep learning models and graph theory such that diff...
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07/27/2021
Experiments on Properties of Hidden Structures of Sparse Neural Networks
Sparsity in the structure of Neural Networks can lead to less energy con...
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10/29/2020
Lessons Learned from the 1st ARIEL Machine Learning Challenge: Correcting Transiting Exoplanet Light Curves for Stellar Spots
The last decade has witnessed a rapid growth of the field of exoplanet d...
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10/23/2020
HateBERT: Retraining BERT for Abusive Language Detection in English
In this paper, we introduce HateBERT, a re-trained BERT model for abusiv...
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07/14/2020
ADSAGE: Anomaly Detection in Sequences of Attributed Graph Edges applied to insider threat detection at fine-grained level
Previous works on the CERT insider threat detection case have neglected ...
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06/07/2020
Deep Graph Generators
Learning distributions of graphs can be used for automatic drug discover...
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02/17/2020
Investigating Extensions to Random Walk Based Graph Embedding
Graph embedding has recently gained momentum in the research community, ...
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02/16/2020
Global and Local Feature Learning for Ego-Network Analysis
In an ego-network, an individual (ego) organizes its friends (alters) in...
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02/16/2020
Predicting event attendance exploring social influence
The problem of predicting people's participation in real-world events ha...
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02/12/2020
Shortest path distance approximation using deep learning techniques
Computing shortest path distances between nodes lies at the heart of man...
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12/27/2019
Competitive Influence Maximization: Integrating Budget Allocation and Seed Selection
Today, many companies take advantage of viral marketing to promote their...
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12/09/2019
Parallel Total Variation Distance Estimation with Neural Networks for Merging Over-Clusterings
We consider the initial situation where a dataset has been over-partitio...
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10/20/2019
Policy Learning for Malaria Control
Sequential decision making is a typical problem in reinforcement learnin...
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10/16/2019
Structural Analysis of Sparse Neural Networks
Sparse Neural Networks regained attention due to their potential for mat...
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09/03/2019
Towards automated feature engineering for credit card fraud detection using multi-perspective HMMs
Machine learning and data mining techniques have been used extensively i...
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06/17/2019
Dataset shift quantification for credit card fraud detection
Machine learning and data mining techniques have been used extensively i...
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05/15/2019
Multiple perspectives HMM-based feature engineering for credit card fraud detection
Machine learning and data mining techniques have been used extensively i...
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04/17/2019
