Copertina

Weight Clipping for Deep Continual and Reinforcement Learning

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Elsayed, Mohamed, Lan, Qingfeng, Lyle, Clare, Mahmood, A. Rupam
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Streaming Deep Reinforcement Learning Finally Works
di: Elsayed, Mohamed, et al.
Pubblicazione: (2024)

Addressing Loss of Plasticity and Catastrophic Forgetting in Continual Learning
di: Elsayed, Mohamed, et al.
Pubblicazione: (2024)

Learning to Optimize for Reinforcement Learning
di: Lan, Qingfeng, et al.
Pubblicazione: (2023)

Revisiting Scalable Hessian Diagonal Approximations for Applications in Reinforcement Learning
di: Elsayed, Mohamed, et al.
Pubblicazione: (2024)

Intentional Updates for Streaming Reinforcement Learning
di: Sharifnassab, Arsalan, et al.
Pubblicazione: (2026)

More Efficient Randomized Exploration for Reinforcement Learning via Approximate Sampling
di: Ishfaq, Haque, et al.
Pubblicazione: (2024)

Efficient Reinforcement Learning by Reducing Forgetting with Elephant Activation Functions
di: Lan, Qingfeng, et al.
Pubblicazione: (2025)

Deep Policy Gradient Methods Without Batch Updates, Target Networks, or Replay Buffers
di: Vasan, Gautham, et al.
Pubblicazione: (2024)

Distributions as Actions: A Unified Framework for Diverse Action Spaces
di: He, Jiamin, et al.
Pubblicazione: (2025)

Operator-Guided Invariance Learning for Continuous Reinforcement Learning
di: Zhang, Zuyuan, et al.
Pubblicazione: (2026)

Clustering-Based Weight Orthogonalization for Stabilizing Deep Reinforcement Learning
di: Ma, Guoqing, et al.
Pubblicazione: (2025)

Exploiting Estimation Bias in Clipped Double Q-Learning for Continous Control Reinforcement Learning Tasks
di: Turcato, Niccolò, et al.
Pubblicazione: (2024)

The Cell Must Go On: Agar.io for Continual Reinforcement Learning
di: Mohamed, Mohamed A., et al.
Pubblicazione: (2025)

OffSeeker: Online Reinforcement Learning Is Not All You Need for Deep Research Agents
di: Zhou, Yuhang, et al.
Pubblicazione: (2026)

Broad Critic Deep Actor Reinforcement Learning for Continuous Control
di: Thalagala, Shiron, et al.
Pubblicazione: (2024)

Towards Batch-to-Streaming Deep Reinforcement Learning for Continuous Control
di: De Monte, Riccardo, et al.
Pubblicazione: (2026)

Synthetic ALS-EEG Data Augmentation for ALS Diagnosis Using Conditional WGAN with Weight Clipping
di: Mutlu, Abdulvahap, et al.
Pubblicazione: (2025)

PPO-Clip Attains Global Optimality: Towards Deeper Understandings of Clipping
di: Huang, Nai-Chieh, et al.
Pubblicazione: (2023)

BandPO: Bridging Trust Regions and Ratio Clipping via Probability-Aware Bounds for LLM Reinforcement Learning
di: Li, Yuan, et al.
Pubblicazione: (2026)

A Unifying Framework for Action-Conditional Self-Predictive Reinforcement Learning
di: Khetarpal, Khimya, et al.
Pubblicazione: (2024)

Neuron-level Balance between Stability and Plasticity in Deep Reinforcement Learning
di: Lan, Jiahua, et al.
Pubblicazione: (2025)

Provable and Practical: Efficient Exploration in Reinforcement Learning via Langevin Monte Carlo
di: Ishfaq, Haque, et al.
Pubblicazione: (2023)

Frequency and Generalisation of Periodic Activation Functions in Reinforcement Learning
di: Mavor-Parker, Augustine N., et al.
Pubblicazione: (2024)

A priori Estimates for Deep Residual Network in Continuous-time Reinforcement Learning
di: Yin, Shuyu, et al.
Pubblicazione: (2024)

Recurrent Deep Reinforcement Learning for Chemotherapy Control under Partial Observability
di: Kiram, Firas Mohamed Elamine, et al.
Pubblicazione: (2026)

From $\log π$ to $π$: Taming Divergence in Soft Clipping via Bilateral Decoupled Decay of Probability Gradient Weight
di: Fu, Xiaoliang, et al.
Pubblicazione: (2026)

An Optimal Discriminator Weighted Imitation Perspective for Reinforcement Learning
di: Xu, Haoran, et al.
Pubblicazione: (2025)

Adaptive Correlation-Weighted Intrinsic Rewards for Reinforcement Learning
di: Nguyen, Viet Bac, et al.
Pubblicazione: (2026)

Age and Power Minimization via Meta-Deep Reinforcement Learning in UAV Networks
di: Sarathchandra, Sankani, et al.
Pubblicazione: (2025)

CUER: Corrected Uniform Experience Replay for Off-Policy Continuous Deep Reinforcement Learning Algorithms
di: Yenicesu, Arda Sarp, et al.
Pubblicazione: (2024)

BAPO: Stabilizing Off-Policy Reinforcement Learning for LLMs via Balanced Policy Optimization with Adaptive Clipping
di: Xi, Zhiheng, et al.
Pubblicazione: (2025)

Continual Learning as Computationally Constrained Reinforcement Learning
di: Kumar, Saurabh, et al.
Pubblicazione: (2023)

An Invitation to Deep Reinforcement Learning
di: Jaeger, Bernhard, et al.
Pubblicazione: (2023)

RLtools: A Fast, Portable Deep Reinforcement Learning Library for Continuous Control
di: Eschmann, Jonas, et al.
Pubblicazione: (2023)

Parseval Regularization for Continual Reinforcement Learning
di: Chung, Wesley, et al.
Pubblicazione: (2024)

Rethinking the Foundations for Continual Reinforcement Learning
di: Elelimy, Esraa, et al.
Pubblicazione: (2025)

A Survey of Continual Reinforcement Learning
di: Pan, Chaofan, et al.
Pubblicazione: (2025)

Approaching Deep Learning through the Spectral Dynamics of Weights
di: Yunis, David, et al.
Pubblicazione: (2024)

Scaling Off-Policy Reinforcement Learning with Batch and Weight Normalization
di: Palenicek, Daniel, et al.
Pubblicazione: (2025)

Higher-Order Action Regularization in Deep Reinforcement Learning: From Continuous Control to Building Energy Management
di: Ahmed, Faizan, et al.
Pubblicazione: (2026)