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05/18/2023
BELLA: Black box model Explanations by Local Linear Approximations
In recent years, understanding the decision-making process of black-box ...
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02/16/2023
Preventing Discriminatory Decision-making in Evolving Data Streams
Bias in machine learning has rightly received significant attention over...
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09/28/2022
A simple but strong baseline for online continual learning: Repeated Augmented Rehearsal
Online continual learning (OCL) aims to train neural networks incrementa...
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09/16/2022
Linear TreeShap
Decision trees are well-known due to their ease of interpretability. To ...
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05/06/2022
Green Accelerated Hoeffding Tree
State-of-the-art machine learning solutions mainly focus on creating hig...
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04/27/2022
Open challenges for Machine Learning based Early Decision-Making research
More and more applications require early decisions, i.e. taken as soon a...
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01/27/2022
Incremental Mining of Frequent Serial Episodes Considering Multiple Occurrences
The need to analyze information from streams arises in a variety of appl...
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01/12/2022
Proceedings of the 4th Workshop on Online Recommender Systems and User Modeling – ORSUM 2021
Modern online services continuously generate data at very fast rates. Th...
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08/26/2021
Sketches for Time-Dependent Machine Learning
Time series data can be subject to changes in the underlying process tha...
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08/17/2021
FARF: A Fair and Adaptive Random Forests Classifier
As Artificial Intelligence (AI) is used in more applications, the need t...
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06/16/2021
A Survey on Semi-Supervised Learning for Delayed Partially Labelled Data Streams
Unlabelled data appear in many domains and are particularly relevant to ...
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04/05/2021
Model Compression for Dynamic Forecast Combination
The predictive advantage of combining several different predictive model...
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03/17/2021
A Survey on Spatio-temporal Data Analytics Systems
Due to the surge of spatio-temporal data volume, the popularity of locat...
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03/01/2021
STUDD: A Student-Teacher Method for Unsupervised Concept Drift Detection
Concept drift detection is a crucial task in data stream evolving enviro...
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12/08/2020
River: machine learning for streaming data in Python
River is a machine learning library for dynamic data streams and continu...
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10/30/2020
Machine Learning (In) Security: A Stream of Problems
Machine Learning (ML) has been widely applied to cybersecurity, and is c...
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10/20/2020
An Eager Splitting Strategy for Online Decision Trees
We study the effectiveness of replacing the split strategy for the state...
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10/16/2020
Emergent and Unspecified Behaviors in Streaming Decision Trees
Hoeffding trees are the state-of-the-art methods in decision tree learni...
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09/21/2020
CURIE: A Cellular Automaton for Concept Drift Detection
Data stream mining extracts information from large quantities of data fl...
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07/02/2020
S2CE: A Hybrid Cloud and Edge Orchestrator for Mining Exascale Distributed Streams
The explosive increase in volume, velocity, variety, and veracity of dat...
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05/15/2020
Adaptive XGBoost for Evolving Data Streams
Boosting is an ensemble method that combines base models in a sequential...
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11/17/2019
Rebalancing Learning on Evolving Data Streams
Nowadays, every device connected to the Internet generates an ever-growi...
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07/23/2019
Exploiting a Stimuli Encoding Scheme of Spiking Neural Networks for Stream Learning
Stream data processing has gained progressive momentum with the arriving...
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07/23/2019
Spiking Neural Networks and Online Learning: An Overview and Perspectives
Applications that generate huge amounts of data in the form of fast stre...
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05/21/2019
Recurring Concept Meta-learning for Evolving Data Streams
When concept drift is detected during classification in a data stream, a...
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05/14/2019
Resource-aware Elastic Swap Random Forest for Evolving Data Streams
Continual learning based on data stream mining deals with ubiquitous sou...
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10/23/2018
Novel Adaptive Algorithms for Estimating Betweenness, Coverage and k-path Centralities
An important index widely used to analyze social and information network...
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07/12/2018
Scikit-Multiflow: A Multi-output Streaming Framework
Scikit-multiflow is a multi-output/multi-label and stream data mining fr...
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05/26/2018
Large-Scale Learning from Data Streams with Apache SAMOA
Apache SAMOA (Scalable Advanced Massive Online Analysis) is an open-sour...
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07/28/2016
VHT: Vertical Hoeffding Tree
IoT Big Data requires new machine learning methods able to scale to larg...
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11/03/2015
Data Stream Classification using Random Feature Functions and Novel Method Combinations
Big Data streams are being generated in a faster, bigger, and more commo...
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04/23/2015
Use of Ensembles of Fourier Spectra in Capturing Recurrent Concepts in Data Streams
In this research, we apply ensembles of Fourier encoded spectra to captu...
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05/03/2014
