Cover Image

The surprising efficiency of temporal difference learning for rare event prediction

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Cheng, Xiaoou, Weare, Jonathan
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Improved Active Learning via Dependent Leverage Score Sampling
by: Shimizu, Atsushi, et al.
Published: (2023)

VARMA-Enhanced Transformer for Time Series Forecasting
by: Song, Jiajun, et al.
Published: (2025)

Convergence of Unadjusted Langevin in High Dimensions: Delocalization of Bias
by: Chen, Yifan, et al.
Published: (2024)

Is Your Explanation Reliable: Confidence-Aware Explanation on Graph Neural Networks
by: Zhang, Jiaxing, et al.
Published: (2025)

PROTECT: Protein circadian time prediction using unsupervised learning
by: Ogholbake, Aram Ansary, et al.
Published: (2025)

A federated learning framework with knowledge graph and temporal transformer for early sepsis prediction in multi-center ICUs
by: Chang, Yue, et al.
Published: (2026)

Conformal Feedback Alignment: Quantifying Answer-Level Reliability for Robust LLM Alignment
by: Chen, Tiejin, et al.
Published: (2026)

BLEUBERI: BLEU is a surprisingly effective reward for instruction following
by: Chang, Yapei, et al.
Published: (2025)

Deep learning surrogate models of JULES-INFERNO for wildfire prediction on a global scale
by: Cheng, Sibo, et al.
Published: (2024)

Towards efficient representation identification in supervised learning
by: Ahuja, Kartik, et al.
Published: (2022)

Static and multivariate-temporal attentive fusion transformer for readmission risk prediction
by: Sun, Zhe, et al.
Published: (2024)

Collapsing ROC approach for risk prediction research on both common and rare variants
by: Wei, Changshuai, et al.
Published: (2025)

Multiplicative learning from observation-prediction ratios
by: Kim, Han, et al.
Published: (2025)

Finite time analysis of temporal difference learning with linear function approximation: Tail averaging and regularisation
by: Patil, Gandharv, et al.
Published: (2022)

Toward efficient resource utilization at edge nodes in federated learning
by: Alawadi, Sadi, et al.
Published: (2023)

Not all tokens are needed(NAT): token efficient reinforcement learning
by: Sang, Hejian, et al.
Published: (2026)

Emergent temporal abstractions in autoregressive models enable hierarchical reinforcement learning
by: Kobayashi, Seijin, et al.
Published: (2025)

Sparse learned kernels for interpretable and efficient medical time series processing
by: Chen, Sully F., et al.
Published: (2023)

TinySubNets: An efficient and low capacity continual learning strategy
by: Pietroń, Marcin, et al.
Published: (2024)

An efficient deep reinforcement learning environment for flexible job-shop scheduling
by: Wu, Xinquan, et al.
Published: (2025)

FastODT: A tree-based framework for efficient continual learning
by: Bretsko, Daniel, et al.
Published: (2026)

A deep learning and machine learning approach to predict neonatal death in the context of São Paulo
by: Raihan, Mohon, et al.
Published: (2025)

Dynamic feature selection in medical predictive monitoring by reinforcement learning
by: Chen, Yutong, et al.
Published: (2024)

Robust agents learn causal world models
by: Richens, Jonathan, et al.
Published: (2024)

Evaluation of human-model prediction difference on the Internet Scale of Data
by: Liu, Weitang, et al.
Published: (2023)

Designing an efficient and equitable humanitarian supply chain dynamically via reinforcement learning
by: Jin, Weijia
Published: (2025)

Critical appraisal of artificial intelligence for rare-event recognition: principles and pharmacovigilance case studies
by: Noren, G. Niklas, et al.
Published: (2025)

Policy-shaped prediction: avoiding distractions in model-based reinforcement learning
by: Hutson, Miles, et al.
Published: (2024)

Monitoring fairness in machine learning models that predict patient mortality in the ICU
by: van Schaik, Tempest A., et al.
Published: (2024)

Evaluating machine learning models for predicting pesticide toxicity to honey bees
by: Adamczyk, Jakub, et al.
Published: (2025)

Application of predictive machine learning in pen & paper RPG game design
by: Śliwa, Jolanta
Published: (2025)

DISCO: learning to DISCover an evolution Operator for multi-physics-agnostic prediction
by: Morel, Rudy, et al.
Published: (2025)

StormNet: Improving storm surge predictions with a GNN-based spatio-temporal offset forecasting model
by: Nader, Noujoud, et al.
Published: (2026)

Efficient and Private: Memorisation under differentially private parameter-efficient fine-tuning in language models
by: Ma, Olivia, et al.
Published: (2024)

Uncertainty quantification for probabilistic machine learning in earth observation using conformal prediction
by: Singh, Geethen, et al.
Published: (2024)

Deep learning with noisy labels in medical prediction problems: a scoping review
by: Wei, Yishu, et al.
Published: (2024)

Enhanced geometry prediction in laser directed energy deposition using meta-learning
by: Saadi, Abdul Malik Al Mardhouf Al, et al.
Published: (2025)

Accurate and interpretable drug-drug interaction prediction enabled by knowledge subgraph learning
by: Wang, Yaqing, et al.
Published: (2023)

Adaptive traffic signal safety and efficiency improvement by multi objective deep reinforcement learning approach
by: Mirbakhsh, Shahin, et al.
Published: (2024)

Training-efficient density quantum machine learning
by: Coyle, Brian, et al.
Published: (2024)