Cover Image

Towards a Systematic Approach to Design New Ensemble Learning Algorithms

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Mendes-Moreira, João, Mendes-Neves, Tiago
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Neighbor-based Approach to Pitch Ownership Models in Soccer
by: Mendes-Neves, Tiago, et al.
Published: (2025)

Estimating Player Performance in Different Contexts Using Fine-tuned Large Events Models
by: Mendes-Neves, Tiago, et al.
Published: (2024)

Forecasting Events in Soccer Matches Through Language
by: Mendes-Neves, Tiago, et al.
Published: (2024)

Kernel Corrector LSTM
by: Tuna, Rodrigo, et al.
Published: (2024)

Divide, Specialize, and Route: A New Approach to Efficient Ensemble Learning
by: Piwko, Jakub, et al.
Published: (2025)

The Geostrategy of Youth Player Recruitment in Portuguese Clubs
by: Mendes-Neves, Tiago, et al.
Published: (2025)

Constrained Adversarial Learning for Automated Software Testing: a literature review
by: Vitorino, João, et al.
Published: (2023)

Scalable Structure Learning of Bayesian Networks by Learning Algorithm Ensembles
by: Liu, Shengcai, et al.
Published: (2025)

CLUE: Neural Networks Calibration via Learning Uncertainty-Error alignment
by: Mendes, Pedro, et al.
Published: (2025)

Asynchronous Probability Ensembling for Federated Disaster Detection
by: Martins, Emanuel Teixeira, et al.
Published: (2026)

Towards Lifelong Learning Embeddings: An Algorithmic Approach to Dynamically Extend Embeddings
by: Gomes, Miguel Alves, et al.
Published: (2024)

A Hybrid Meta-Learning and Multi-Armed Bandit Approach for Context-Specific Multi-Objective Recommendation Optimization
by: Cunha, Tiago, et al.
Published: (2024)

Forecasting Soccer Matches through Distributions
by: Mendes-Neves, Tiago, et al.
Published: (2025)

Enhancing Customer Churn Prediction in Telecommunications: An Adaptive Ensemble Learning Approach
by: Shaikhsurab, Mohammed Affan, et al.
Published: (2024)

Classy Ensemble: A Novel Ensemble Algorithm for Classification
by: Sipper, Moshe
Published: (2023)

Bayesian Experimental Design for Model Discrepancy Calibration: An Auto-Differentiable Ensemble Kalman Inversion Approach
by: Yang, Huchen, et al.
Published: (2025)

Bridging Algorithmic Information Theory and Machine Learning: A New Approach to Kernel Learning
by: Hamzi, Boumediene, et al.
Published: (2023)

Pitfalls of Unlabeled Disagreement-Based Drift Detection in Streaming Tree Ensembles
by: Neves, Lara Sá, et al.
Published: (2026)

Enhanced Parcel Arrival Forecasting for Logistic Hubs: An Ensemble Deep Learning Approach
by: Pan, Xinyue, et al.
Published: (2026)

A Data Balancing and Ensemble Learning Approach for Credit Card Fraud Detection
by: Wang, Yuhan
Published: (2025)

Hyper-parameter Tuning for Adversarially Robust Models
by: Mendes, Pedro, et al.
Published: (2023)

EnsembleCI: Ensemble Learning for Carbon Intensity Forecasting
by: Yan, Leyi, et al.
Published: (2025)

Advancing Robustness in Deep Reinforcement Learning with an Ensemble Defense Approach
by: Mohan, Adithya, et al.
Published: (2025)

Pulling the Carpet Below the Learner's Feet: Genetic Algorithm To Learn Ensemble Machine Learning Model During Concept Drift
by: Lazebnik, Teddy
Published: (2024)

A New Approach for Evaluating and Improving the Performance of Segmentation Algorithms on Hard-to-Detect Blood Vessels
by: Parella, João Pedro, et al.
Published: (2024)

Intelligent Green Efficiency for Intrusion Detection
by: Pereira, Pedro, et al.
Published: (2024)

Training Diverse Graph Experts for Ensembles: A Systematic Empirical Study
by: Deng, Gangda, et al.
Published: (2025)

Exploiting ID-Text Complementarity via Ensembling for Sequential Recommendation
by: Collins, Liam, et al.
Published: (2025)

Exploring the Design Space of Fair Tree Learning Algorithms
by: Stempel, Kiara, et al.
Published: (2025)

Language Models can Self-Improve at State-Value Estimation for Better Search
by: Mendes, Ethan, et al.
Published: (2025)

DFCA: Decentralized Federated Clustering Algorithm
by: Kirch, Jonas, et al.
Published: (2025)

Meta-Imputation Balanced (MIB): An Ensemble Approach for Handling Missing Data in Biomedical Machine Learning
by: Azad, Fatemeh, et al.
Published: (2025)

Electricity Consumption Forecasting: An Approach Using Cooperative Ensemble Learning with SHapley Additive exPlanations
by: Alba, Eduardo Luiz, et al.
Published: (2026)

Metal Price Spike Prediction via a Neurosymbolic Ensemble Approach
by: Lee, Nathaniel, et al.
Published: (2024)

TRACE: Traceroute-based Internet Route change Analysis with Ensemble Learning
by: Suzuki, Raul, et al.
Published: (2026)

A Systematic Survey on Large Language Models for Algorithm Design
by: Liu, Fei, et al.
Published: (2024)

A Two-Step Concept-Based Approach for Enhanced Interpretability and Trust in Skin Lesion Diagnosis
by: Patrício, Cristiano, et al.
Published: (2024)

Concept Learning in the Wild: Towards Algorithmic Understanding of Neural Networks
by: Shoham, Elad, et al.
Published: (2024)

Local LLM Ensembles for Zero-shot Portuguese Named Entity Recognition
by: Sarcinelli, João Lucas Luz Lima, et al.
Published: (2025)

Generalization Performance of Ensemble Clustering: From Theory to Algorithm
by: Zhang, Xu, et al.
Published: (2025)