Multi-task Online Learning for Probabilistic Load Forecasting
Fuente:
arXiv
Saved in:
| Main Authors: | Zaballa, Onintze, Álvarez, Verónica, Mazuelas, Santiago |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Adaptive Multi-task Learning for Probabilistic Load Forecasting
by: Zaballa, Onintze, et al.
Published: (2025)
by: Zaballa, Onintze, et al.
Published: (2025)
Probabilistic Load Forecasting Based on Adaptive Online Learning
by: Álvarez, Verónica, et al.
Published: (2020)
by: Álvarez, Verónica, et al.
Published: (2020)
Robust Minimax Boosting with Performance Guarantees
by: Mazuelas, Santiago, et al.
Published: (2025)
by: Mazuelas, Santiago, et al.
Published: (2025)
Supervised Learning with Evolving Tasks and Performance Guarantees
by: Álvarez, Verónica, et al.
Published: (2025)
by: Álvarez, Verónica, et al.
Published: (2025)
Reliable Programmatic Weak Supervision with Confidence Intervals for Label Probabilities
by: Álvarez, Verónica, et al.
Published: (2025)
by: Álvarez, Verónica, et al.
Published: (2025)
Split Conformal Classification with Unsupervised Calibration
by: Mazuelas, Santiago
Published: (2025)
by: Mazuelas, Santiago
Published: (2025)
Efficient Large-Scale Learning of Minimax Risk Classifiers
by: Bondugula, Kartheek, et al.
Published: (2025)
by: Bondugula, Kartheek, et al.
Published: (2025)
MRCpy: A Library for Minimax Risk Classifiers
by: Bondugula, Kartheek, et al.
Published: (2021)
by: Bondugula, Kartheek, et al.
Published: (2021)
On the Optimality of the Median-of-Means Estimator under Adversarial Contamination
by: de Juan, Xabier, et al.
Published: (2025)
by: de Juan, Xabier, et al.
Published: (2025)
Minimax Generalized Cross-Entropy
by: Bondugula, Kartheek, et al.
Published: (2026)
by: Bondugula, Kartheek, et al.
Published: (2026)
Bayesian Transformer for Probabilistic Load Forecasting in Smart Grids
by: Debnath, Sajib, et al.
Published: (2026)
by: Debnath, Sajib, et al.
Published: (2026)
Stacking for Probabilistic Short-term Load Forecasting
by: Dudek, Grzegorz
Published: (2024)
by: Dudek, Grzegorz
Published: (2024)
Learnability with Partial Labels and Adaptive Nearest Neighbors
by: Errandonea, Nicolas A., et al.
Published: (2026)
by: Errandonea, Nicolas A., et al.
Published: (2026)
Safe Fairness Guarantees Without Demographics in Classification: Spectral Uncertainty Set Perspective
by: Barrainkua, Ainhize, et al.
Published: (2026)
by: Barrainkua, Ainhize, et al.
Published: (2026)
Zero-shot Load Forecasting for Integrated Energy Systems: A Large Language Model-based Framework with Multi-task Learning
by: Li, Jiaheng, et al.
Published: (2025)
by: Li, Jiaheng, et al.
Published: (2025)
External Data-Enhanced Meta-Representation for Adaptive Probabilistic Load Forecasting
by: Li, Haoran, et al.
Published: (2025)
by: Li, Haoran, et al.
Published: (2025)
Multi-task Offline Reinforcement Learning for Online Advertising in Recommender Systems
by: Liu, Langming, et al.
Published: (2025)
by: Liu, Langming, et al.
Published: (2025)
DiffPLF: A Conditional Diffusion Model for Probabilistic Forecasting of EV Charging Load
by: Li, Siyang, et al.
Published: (2024)
by: Li, Siyang, et al.
Published: (2024)
Mixability of Integral Losses: a Key to Efficient Online Aggregation of Functional and Probabilistic Forecasts
by: Korotin, Alexander, et al.
Published: (2019)
by: Korotin, Alexander, et al.
Published: (2019)
Online Decentralized Federated Multi-task Learning With Trustworthiness in Cyber-Physical Systems
by: Odeyomi, Olusola, et al.
Published: (2025)
by: Odeyomi, Olusola, et al.
Published: (2025)
Adaptive Ensemble Learning with Gaussian Copula for Load Forecasting
by: Yang, Junying, et al.
Published: (2025)
by: Yang, Junying, et al.
Published: (2025)
Optimizing Likelihoods via Mutual Information: Bridging Simulation-Based Inference and Bayesian Optimal Experimental Design
by: Zaballa, Vincent D., et al.
Published: (2025)
by: Zaballa, Vincent D., et al.
Published: (2025)
Probabilistic Hash Embeddings for Online Learning of Categorical Features
by: Li, Aodong, et al.
Published: (2025)
by: Li, Aodong, et al.
Published: (2025)
M$^2$OE$^2$-GL: A Family of Probabilistic Load Forecasters That Scales to Massive Customers
by: Li, Haoran, et al.
Published: (2025)
by: Li, Haoran, et al.
Published: (2025)
Monotonic Transformation Invariant Multi-task Learning
by: Murthy, Surya, et al.
Published: (2025)
by: Murthy, Surya, et al.
Published: (2025)
Online Data Augmentation for Forecasting with Deep Learning
by: Cerqueira, Vitor, et al.
Published: (2024)
by: Cerqueira, Vitor, et al.
Published: (2024)
Calibrated Probabilistic Forecasts for Arbitrary Sequences
by: Marx, Charles, et al.
Published: (2024)
by: Marx, Charles, et al.
Published: (2024)
Probabilistic Traffic Forecasting with Dynamic Regression
by: Zheng, Vincent Zhihao, et al.
Published: (2023)
by: Zheng, Vincent Zhihao, et al.
Published: (2023)
TriForecaster: A Mixture of Experts Framework for Multi-Region Electric Load Forecasting with Tri-dimensional Specialization
by: Zhu, Zhaoyang, et al.
Published: (2025)
by: Zhu, Zhaoyang, et al.
Published: (2025)
GRAFT: Grid-Aware Load Forecasting with Multi-Source Textual Alignment and Fusion
by: Lin, Fangzhou, et al.
Published: (2025)
by: Lin, Fangzhou, et al.
Published: (2025)
ProbRes: Volatility Learning for Probabilistic Time-Series Forecasting
by: Wang, Tingting, et al.
Published: (2026)
by: Wang, Tingting, et al.
Published: (2026)
Exploring Lightweight Federated Learning for Distributed Load Forecasting
by: Duttagupta, Abhishek, et al.
Published: (2024)
by: Duttagupta, Abhishek, et al.
Published: (2024)
Dynamic Multi-period Experts for Online Time Series Forecasting
by: Hong, Seungha, et al.
Published: (2026)
by: Hong, Seungha, et al.
Published: (2026)
Automated Deep Learning for Load Forecasting
by: Keisler, Julie, et al.
Published: (2024)
by: Keisler, Julie, et al.
Published: (2024)
Probabilistic Wind Power Forecasting with Tree-Based Machine Learning and Weather Ensembles
by: Bruninx, Max, et al.
Published: (2026)
by: Bruninx, Max, et al.
Published: (2026)
Characterization of Transfer Using Multi-task Learning Curves
by: Millinghoffer, András, et al.
Published: (2025)
by: Millinghoffer, András, et al.
Published: (2025)
Interpretable Multi-task Learning with Shared Variable Embeddings
by: Żelaszczyk, Maciej, et al.
Published: (2024)
by: Żelaszczyk, Maciej, et al.
Published: (2024)
Distributed Networked Multi-task Learning
by: Hong, Lingzhou, et al.
Published: (2024)
by: Hong, Lingzhou, et al.
Published: (2024)
Unveiling Stochasticity: Universal Multi-modal Probabilistic Modeling for Traffic Forecasting
by: Xiong, Weijiang, et al.
Published: (2026)
by: Xiong, Weijiang, et al.
Published: (2026)
Probabilistic Forecasting via Autoregressive Flow Matching
by: ElGazzar, Ahmed, et al.
Published: (2025)
by: ElGazzar, Ahmed, et al.
Published: (2025)
Similar Items
-
Adaptive Multi-task Learning for Probabilistic Load Forecasting
by: Zaballa, Onintze, et al.
Published: (2025) -
Probabilistic Load Forecasting Based on Adaptive Online Learning
by: Álvarez, Verónica, et al.
Published: (2020) -
Robust Minimax Boosting with Performance Guarantees
by: Mazuelas, Santiago, et al.
Published: (2025) -
Supervised Learning with Evolving Tasks and Performance Guarantees
by: Álvarez, Verónica, et al.
Published: (2025) -
Reliable Programmatic Weak Supervision with Confidence Intervals for Label Probabilities
by: Álvarez, Verónica, et al.
Published: (2025)