Cover Image

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Liang, Daojun, Zhang, Haixia, Wang, Jing, Yuan, Dongfeng, Zhang, Minggao
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

Minusformer: Improving Time Series Forecasting by Progressively Learning Residuals
by: Liang, Daojun, et al.
Published: (2024)

Progressive Supervision via Label Decomposition: An Long-Term and Large-Scale Wireless Traffic Forecasting Method
by: Liang, Daojun, et al.
Published: (2025)

Multi-Head Encoding for Extreme Label Classification
by: Liang, Daojun, et al.
Published: (2024)

Does Long-Term Series Forecasting Need Complex Attention and Extra Long Inputs?
by: Liang, Daojun, et al.
Published: (2023)

DistPred: A Distribution-Free Probabilistic Inference Method for Regression and Forecasting
by: Liang, Daojun, et al.
Published: (2024)

DeepBooTS: Dual-Stream Residual Boosting for Drift-Resilient Time-Series Forecasting
by: Liang, Daojun, et al.
Published: (2025)

Joint Service Caching, Communication and Computing Resource Allocation in Collaborative MEC Systems: A DRL-based Two-timescale Approach
by: Liu, Qianqian, et al.
Published: (2023)

The Forecast After the Forecast: A Post-Processing Shift in Time Series
by: Liang, Daojun, et al.
Published: (2026)

Reason for Future, Act for Now: A Principled Framework for Autonomous LLM Agents with Provable Sample Efficiency
by: Liu, Zhihan, et al.
Published: (2023)

Online Estimation with Rolling Validation: Adaptive Nonparametric Estimation with Streaming Data
by: Zhang, Tianyu, et al.
Published: (2023)

R$^2$Energy: A Large-Scale Benchmark for Robust Renewable Energy Forecasting under Diverse and Extreme Conditions
by: Sheng, Zhi, et al.
Published: (2026)

ODEStream: A Buffer-Free Online Learning Framework with ODE-based Adaptor for Streaming Time Series Forecasting
by: Abushaqra, Futoon M., et al.
Published: (2024)

Addressing Concept Shift in Online Time Series Forecasting: Detect-then-Adapt
by: Zhang, YiFan, et al.
Published: (2024)

Online-BLS: An Accurate and Efficient Online Broad Learning System for Data Stream Classification
by: Lei, Chunyu, et al.
Published: (2025)

A Novel Hyperdimensional Computing Framework for Online Time Series Forecasting on the Edge
by: Mejri, Mohamed, et al.
Published: (2024)

Teaching RL Agents to Act Better: VLM as Action Advisor for Online Reinforcement Learning
by: Wu, Xiefeng, et al.
Published: (2025)

L^2M^3OF: A Large Language Multimodal Model for Metal-Organic Frameworks
by: Cui, Jiyu, et al.
Published: (2025)

Efficient Large-Scale Traffic Forecasting with Transformers: A Spatial Data Management Perspective
by: Fang, Yuchen, et al.
Published: (2024)

Online Ensemble Transformer for Accurate Cloud Workload Forecasting in Predictive Auto-Scaling
by: Chen, Jiadong, et al.
Published: (2025)

Skillful High-Resolution Ensemble Precipitation Forecasting with an Integrated Deep Learning Framework
by: He, Shuangshuang, et al.
Published: (2025)

Online Kernel Dynamic Mode Decomposition for Streaming Time Series Forecasting with Adaptive Windowing
by: Salazar, Christopher, et al.
Published: (2025)

Improving Online Bagging for Complex Imbalanced Data Stream
by: Przybyl, Bartosz, et al.
Published: (2024)

Federated Online Learning for Heterogeneous Multisource Streaming Data
by: Li, Jingmao, et al.
Published: (2025)

ROSFD: Robust Online Streaming Fraud Detection with Resilience to Concept Drift in Data Streams
by: Yelleti, Vivek
Published: (2025)

BlockRR: A Unified Framework of RR-type Algorithms for Label Differential Privacy
by: Liu, Haixia, et al.
Published: (2026)

Monitoring Machine Learning Forecasts for Platform Data Streams
by: Rombouts, Jeroen, et al.
Published: (2024)

A Novel Framework for Online Supervised Learning with Feature Selection
by: Sun, Lizhe, et al.
Published: (2018)

A Spatio-Temporal Online Robust Tensor Recovery Approach for Streaming Traffic Data Imputation
by: Yang, Yiyang, et al.
Published: (2025)

Online Data Augmentation for Forecasting with Deep Learning
by: Cerqueira, Vitor, et al.
Published: (2024)

HSTMixer: A Hierarchical MLP-Mixer for Large-Scale Traffic Forecasting
by: Wang, Yongyao, et al.
Published: (2025)

LLMs Know When They Know, but Do Not Act on It: A Metacognitive Harness for Test-time Scaling
by: Cao, Qi, et al.
Published: (2026)

SimSort: A Data-Driven Framework for Spike Sorting by Large-Scale Electrophysiology Simulation
by: Zhang, Yimu, et al.
Published: (2025)

Fairness via Independence: A (Conditional) Distance Covariance Framework
by: Huang, Ruifan, et al.
Published: (2024)

AdaMixT: Adaptive Weighted Mixture of Multi-Scale Expert Transformers for Time Series Forecasting
by: Zhang, Huanyao, et al.
Published: (2025)

Forecasting with Guidance: Representation-Level Supervision for Time Series Forecasting
by: Wang, Jiacheng, et al.
Published: (2026)

Harmonized Gradient Descent for Class Imbalanced Data Stream Online Learning
by: Zhou, Han, et al.
Published: (2025)

AGILE: A Novel Reinforcement Learning Framework of LLM Agents
by: Feng, Peiyuan, et al.
Published: (2024)

Local Truncation Error-Guided Neural ODEs for Large Scale Traffic Forecasting
by: Zhang, Xiao, et al.
Published: (2026)

DSAT-HD: Dual-Stream Adaptive Transformer with Hybrid Decomposition for Multivariate Time Series Forecasting
by: Wang, Zixu, et al.
Published: (2025)

DSPR: Dual-Stream Physics-Residual Networks for Trustworthy Industrial Time Series Forecasting
by: Zhang, Yeran, et al.
Published: (2026)