Jesse Read | DeepAI

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Luca Martino
23 publications
Fragkiskos D. Malliaros
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Antoine J. -P. Tixier
11 publications

∙ 05/02/2023

Uncovering the Spatial and Temporal Variability of Wind Resources in Europe: A Web-Based Data-Mining Tool

We introduce REmap-eu.app, a web-based data-mining visualization tool of...

0 Alban Puech, et al. ∙

∙ 05/02/2023

An Improved Yaw Control Algorithm for Wind Turbines via Reinforcement Learning

Yaw misalignment, measured as the difference between the wind direction ...

0 Alban Puech, et al. ∙

∙ 03/30/2023

Shapley Chains: Extending Shapley Values to Classifier Chains

In spite of increased attention on explainable machine learning models, ...

0 Célia Wafa Ayad, et al. ∙

∙ 02/13/2023

Transferable Deep Metric Learning for Clustering

Clustering in high dimension spaces is a difficult task; the usual dista...

0 Simo Alami. C, et al. ∙

∙ 01/02/2023

Chains of Autoreplicative Random Forests for missing value imputation in high-dimensional datasets

Missing values are a common problem in data science and machine learning...

0 Ekaterina Antonenko, et al. ∙

∙ 12/30/2022

Learning from Data Streams: An Overview and Update

The literature on machine learning in the context of data streams is vas...

0 Jesse Read, et al. ∙

∙ 09/16/2022

Linear TreeShap

Decision trees are well-known due to their ease of interpretability. To ...

0 Peng Yu, et al. ∙

∙ 09/09/2022

Estimating Multi-label Accuracy using Labelset Distributions

A multi-label classifier estimates the binary label state (relevant vs i...

0 Laurence A. F. Park, et al. ∙

∙ 08/03/2022

Conv-NILM-Net, a causal and multi-appliance model for energy source separation

Non-Intrusive Load Monitoring (NILM) seeks to save energy by estimating ...

0 Mohamed Alami C., et al. ∙

∙ 07/24/2022

From Multi-label Learning to Cross-Domain Transfer: A Model-Agnostic Approach

In multi-label learning, a particular case of multi-task learning where ...

0 Jesse Read, et al. ∙

∙ 07/13/2022

On Merging Feature Engineering and Deep Learning for Diagnosis, Risk-Prediction and Age Estimation Based on the 12-Lead ECG

Objective: Machine learning techniques have been used extensively for 12...

0 Eran Zvuloni, et al. ∙

∙ 05/19/2022

CAMEO: Curiosity Augmented Metropolis for Exploratory Optimal Policies

Reinforcement Learning has drawn huge interest as a tool for solving opt...

0 Mohamed Alami Chehboune, et al. ∙

∙ 03/28/2022

Isomorphic Cross-lingual Embeddings for Low-Resource Languages

Cross-Lingual Word Embeddings (CLWEs) are a key component to transfer li...

0 Sonal Sannigrahi, et al. ∙

∙ 01/07/2022

Optimality in Noisy Importance Sampling

In this work, we analyze the noisy importance sampling (IS), i.e., IS wo...

0 Fernando Llorente, et al. ∙

∙ 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 ...

0 Heitor Murilo Gomes, et al. ∙

∙ 12/08/2020

River: machine learning for streaming data in Python

River is a machine learning library for dynamic data streams and continu...

0 Jacob Montiel, et al. ∙

∙ 09/19/2020

Joint introduction to Gaussian Processes and Relevance Vector Machines with Connections to Kalman filtering and other Kernel Smoothers

The expressive power of Bayesian kernel-based methods has led them to be...

0 Luca Martino, et al. ∙

∙ 12/26/2019

Classifier Chains: A Review and Perspectives

The family of methods collectively known as classifier chains has become...

0 Jesse Read, et al. ∙

∙ 07/18/2019

Probabilistic Regressor Chains with Monte Carlo Methods

A large number and diversity of techniques have been offered in the lite...

0 Jesse Read, et al. ∙

∙ 10/04/2018

Concept-drifting Data Streams are Time Series; The Case for Continuous Adaptation

Learning from data streams is an increasingly important topic in data mi...

0 Jesse Read, et al. ∙

∙ 07/13/2018

Perturb and Combine to Identify Influential Spreaders in Real-World Networks

Recent research has shown that graph degeneracy algorithms, which decomp...

0 Antoine J. -P. Tixier, et al. ∙

∙ 07/12/2018

Scikit-Multiflow: A Multi-output Streaming Framework

Scikit-multiflow is a multi-output/multi-label and stream data mining fr...

0 Jacob Montiel, et al. ∙

∙ 09/27/2016

Multi-label Methods for Prediction with Sequential Data

The number of methods available for classification of multi-label data h...

0 Jesse Read, et al. ∙

∙ 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...

0 Diego Marrón, et al. ∙

∙ 03/31/2015

Multi-label Classification using Labels as Hidden Nodes

Competitive methods for multi-label classification typically invest in l...

0 Jesse Read, et al. ∙

∙ 12/17/2014

Deep Learning for Multi-label Classification

In multi-label classification, the main focus has been to develop ways o...

0 Jesse Read, et al. ∙

∙ 05/03/2014

Kaggle LSHTC4 Winning Solution

Our winning submission to the 2014 Kaggle competition for Large Scale Hi...

0 Antti Puurula, et al. ∙

∙ 11/09/2012

Efficient Monte Carlo Methods for Multi-Dimensional Learning with Classifier Chains

Multi-dimensional classification (MDC) is the supervised learning proble...

0 Jesse Read, et al. ∙

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