TEACH: Temporal Variance-Driven Curriculum for Reinforcement Learning
Fuente:
arXiv
Saved in:
| Main Authors: | Chaudhary, Gaurav, Behera, Laxmidhar |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
From Novelty to Imitation: Self-Distilled Rewards for Offline Reinforcement Learning
by: Chaudhary, Gaurav, et al.
Published: (2025)
by: Chaudhary, Gaurav, et al.
Published: (2025)
MOORL: A Framework for Integrating Offline-Online Reinforcement Learning
by: Chaudhary, Gaurav, et al.
Published: (2025)
by: Chaudhary, Gaurav, et al.
Published: (2025)
Match or Replay: Self Imitating Proximal Policy Optimization
by: Chaudhary, Gaurav, et al.
Published: (2026)
by: Chaudhary, Gaurav, et al.
Published: (2026)
VCRL: Variance-based Curriculum Reinforcement Learning for Large Language Models
by: Jiang, Guochao, et al.
Published: (2025)
by: Jiang, Guochao, et al.
Published: (2025)
Dynamic Hand Gesture Recognition for Robot Manipulator Tasks
by: Sharma, Dharmendra, et al.
Published: (2026)
by: Sharma, Dharmendra, et al.
Published: (2026)
Pathway-based Progressive Inference (PaPI) for Energy-Efficient Continual Learning
by: Gaurav, Suyash, et al.
Published: (2025)
by: Gaurav, Suyash, et al.
Published: (2025)
Governance-as-a-Service: A Multi-Agent Framework for AI System Compliance and Policy Enforcement
by: Gaurav, Suyash, et al.
Published: (2025)
by: Gaurav, Suyash, et al.
Published: (2025)
A Variance Minimization Approach to Temporal-Difference Learning
by: Chen, Xingguo, et al.
Published: (2024)
by: Chen, Xingguo, et al.
Published: (2024)
Shrinking the Variance: Shrinkage Baselines for Reinforcement Learning with Verifiable Rewards
by: Zeng, Guanning, et al.
Published: (2025)
by: Zeng, Guanning, et al.
Published: (2025)
Averaging $n$-step Returns Reduces Variance in Reinforcement Learning
by: Daley, Brett, et al.
Published: (2024)
by: Daley, Brett, et al.
Published: (2024)
On the Benefit of Optimal Transport for Curriculum Reinforcement Learning
by: Klink, Pascal, et al.
Published: (2023)
by: Klink, Pascal, et al.
Published: (2023)
Mean-Variance Efficient Reinforcement Learning with Applications to Dynamic Financial Investment
by: Kato, Masahiro, et al.
Published: (2020)
by: Kato, Masahiro, et al.
Published: (2020)
Distributionally Robust Self Paced Curriculum Reinforcement Learning
by: Satheesh, Anirudh, et al.
Published: (2025)
by: Satheesh, Anirudh, et al.
Published: (2025)
Curriculum Reinforcement Learning for Complex Reward Functions
by: Freitag, Kilian, et al.
Published: (2024)
by: Freitag, Kilian, et al.
Published: (2024)
Curriculum Learning-Driven PIELMs for Fluid Flow Simulations
by: Dwivedi, Vikas, et al.
Published: (2025)
by: Dwivedi, Vikas, et al.
Published: (2025)
Variance-Adaptive Optimal Algorithm for Reinforcement Learning with Multinomial Logit Function Approximation
by: Kim, Wonyoung, et al.
Published: (2026)
by: Kim, Wonyoung, et al.
Published: (2026)
Enhancing Offline Reinforcement Learning with Curriculum Learning-Based Trajectory Valuation
by: Abolfazli, Amir, et al.
Published: (2025)
by: Abolfazli, Amir, et al.
Published: (2025)
Probabilistic Curriculum Learning for Goal-Based Reinforcement Learning
by: Salt, Llewyn, et al.
Published: (2025)
by: Salt, Llewyn, et al.
Published: (2025)
Efficient Preference-Based Reinforcement Learning Using Learned Dynamics Models
by: Liu, Yi, et al.
Published: (2023)
by: Liu, Yi, et al.
Published: (2023)
Dual-Criterion Curriculum Learning: Application to Temporal Data
by: Abel, Gaspard, et al.
Published: (2026)
by: Abel, Gaspard, et al.
Published: (2026)
TACO: Temporal Latent Action-Driven Contrastive Loss for Visual Reinforcement Learning
by: Zheng, Ruijie, et al.
Published: (2023)
by: Zheng, Ruijie, et al.
Published: (2023)
Realistic Curriculum Reinforcement Learning for Autonomous and Sustainable Marine Vessel Navigation
by: Xiaocai, Zhang, et al.
Published: (2026)
by: Xiaocai, Zhang, et al.
Published: (2026)
Learning-Driven Exploration for Reinforcement Learning
by: Usama, Muhammad, et al.
Published: (2019)
by: Usama, Muhammad, et al.
Published: (2019)
Efficient Reinforcement Finetuning via Adaptive Curriculum Learning
by: Shi, Taiwei, et al.
Published: (2025)
by: Shi, Taiwei, et al.
Published: (2025)
Proximal Curriculum with Task Correlations for Deep Reinforcement Learning
by: Tzannetos, Georgios, et al.
Published: (2024)
by: Tzannetos, Georgios, et al.
Published: (2024)
Adaptive Multi-Fidelity Reinforcement Learning for Variance Reduction in Engineering Design Optimization
by: Agrawal, Akash, et al.
Published: (2025)
by: Agrawal, Akash, et al.
Published: (2025)
Reducing Variance Caused by Communication in Decentralized Multi-agent Deep Reinforcement Learning
by: Zhu, Changxi, et al.
Published: (2025)
by: Zhu, Changxi, et al.
Published: (2025)
DVAO: Dynamic Variance-adaptive Advantage Optimization for Multi-reward Reinforcement Learning
by: Jiang, Guochao, et al.
Published: (2026)
by: Jiang, Guochao, et al.
Published: (2026)
Curriculum-Guided Reinforcement Learning for Synthesizing Gas-Efficient Financial Derivatives Contracts
by: Mridul, Maruf Ahmed, et al.
Published: (2025)
by: Mridul, Maruf Ahmed, et al.
Published: (2025)
CRISP: Curriculum Inducing Primitive Informed Subgoal Prediction for Hierarchical Reinforcement Learning
by: Singh, Utsav, et al.
Published: (2023)
by: Singh, Utsav, et al.
Published: (2023)
Learning to Predict Chaos: Curriculum-Driven Training for Robust Forecasting of Chaotic Dynamics
by: Vejendla, Harshil
Published: (2025)
by: Vejendla, Harshil
Published: (2025)
Reinforcement Learning From State and Temporal Differences
by: Weaver, Lex, et al.
Published: (2025)
by: Weaver, Lex, et al.
Published: (2025)
Temporal Abstraction in Reinforcement Learning with Offline Data
by: Ayyagari, Ranga Shaarad, et al.
Published: (2024)
by: Ayyagari, Ranga Shaarad, et al.
Published: (2024)
Advantage-based Temporal Attack in Reinforcement Learning
by: He, Shenghong
Published: (2026)
by: He, Shenghong
Published: (2026)
Curriculum Negative Mining For Temporal Networks
by: Chen, Ziyue, et al.
Published: (2024)
by: Chen, Ziyue, et al.
Published: (2024)
Learning Progress Driven Multi-Agent Curriculum
by: Zhao, Wenshuai, et al.
Published: (2022)
by: Zhao, Wenshuai, et al.
Published: (2022)
Curriculum Learning with Quality-Driven Data Selection
by: Wu, Biao, et al.
Published: (2024)
by: Wu, Biao, et al.
Published: (2024)
Long N-step Surrogate Stage Reward to Reduce Variances of Deep Reinforcement Learning in Complex Problems
by: Zhong, Junmin, et al.
Published: (2022)
by: Zhong, Junmin, et al.
Published: (2022)
Acquiring Diverse Skills using Curriculum Reinforcement Learning with Mixture of Experts
by: Celik, Onur, et al.
Published: (2024)
by: Celik, Onur, et al.
Published: (2024)
Efficient Deep Learning: A Survey on Making Deep Learning Models Smaller, Faster, and Better
by: Menghani, Gaurav
Published: (2021)
by: Menghani, Gaurav
Published: (2021)
Similar Items
-
From Novelty to Imitation: Self-Distilled Rewards for Offline Reinforcement Learning
by: Chaudhary, Gaurav, et al.
Published: (2025) -
MOORL: A Framework for Integrating Offline-Online Reinforcement Learning
by: Chaudhary, Gaurav, et al.
Published: (2025) -
Match or Replay: Self Imitating Proximal Policy Optimization
by: Chaudhary, Gaurav, et al.
Published: (2026) -
VCRL: Variance-based Curriculum Reinforcement Learning for Large Language Models
by: Jiang, Guochao, et al.
Published: (2025) -
Dynamic Hand Gesture Recognition for Robot Manipulator Tasks
by: Sharma, Dharmendra, et al.
Published: (2026)