Saved in:
| Main Authors: | Usama, Muhammad, Chang, Dong Eui |
|---|---|
| Format: | Preprint |
| Published: |
2019
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/1906.06890 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Distributional Reinforcement Learning with Information Bottleneck for Uncertainty-Aware DRAM Equalization
by: Usama, Muhammad, et al.
Published: (2026)
by: Usama, Muhammad, et al.
Published: (2026)
Deep Reinforcement Learning-Based DRAM Equalizer Parameter Optimization Using Latent Representations
by: Usama, Muhammad, et al.
Published: (2025)
by: Usama, Muhammad, et al.
Published: (2025)
Learning High-Quality Latent Representations for Anomaly Detection and Signal Integrity Enhancement in High-Speed Signals
by: Usama, Muhammad, et al.
Published: (2025)
by: Usama, Muhammad, et al.
Published: (2025)
Real Time Headway Predictions in Urban Rail Systems and Implications for Service Control: A Deep Learning Approach
by: Usama, Muhammad, et al.
Published: (2025)
by: Usama, Muhammad, et al.
Published: (2025)
EvoCoT: Overcoming the Exploration Bottleneck in Reinforcement Learning
by: Liu, Huanyu, et al.
Published: (2025)
by: Liu, Huanyu, et al.
Published: (2025)
Machine learning based state observer for discrete time systems evolving on Lie groups
by: Shanbhag, Soham, et al.
Published: (2024)
by: Shanbhag, Soham, et al.
Published: (2024)
Treatment Stitching with Schrödinger Bridge for Enhancing Offline Reinforcement Learning in Adaptive Treatment Strategies
by: Shin, Dong-Hee, et al.
Published: (2025)
by: Shin, Dong-Hee, et al.
Published: (2025)
PiCSRL: Physics-Informed Contextual Spectral Reinforcement Learning
by: Azadani, Mitra Nasr, et al.
Published: (2026)
by: Azadani, Mitra Nasr, et al.
Published: (2026)
CDE: Curiosity-Driven Exploration for Efficient Reinforcement Learning in Large Language Models
by: Dai, Runpeng, et al.
Published: (2025)
by: Dai, Runpeng, et al.
Published: (2025)
Constraint-Aware Reinforcement Learning via Adaptive Action Scaling
by: Dawood, Murad, et al.
Published: (2025)
by: Dawood, Murad, et al.
Published: (2025)
Search Inspired Exploration in Reinforcement Learning
by: Sotirchos, Georgios, et al.
Published: (2026)
by: Sotirchos, Georgios, et al.
Published: (2026)
Memory-Augmented Architecture for Long-Term Context Handling in Large Language Models
by: Shinwari, Haseeb Ullah Khan, et al.
Published: (2025)
by: Shinwari, Haseeb Ullah Khan, et al.
Published: (2025)
Random Latent Exploration for Deep Reinforcement Learning
by: Mahankali, Srinath, et al.
Published: (2024)
by: Mahankali, Srinath, et al.
Published: (2024)
Preference-Guided Reinforcement Learning for Efficient Exploration
by: Wang, Guojian, et al.
Published: (2024)
by: Wang, Guojian, et al.
Published: (2024)
Model-Free Active Exploration in Reinforcement Learning
by: Russo, Alessio, et al.
Published: (2024)
by: Russo, Alessio, et al.
Published: (2024)
In-context Exploration-Exploitation for Reinforcement Learning
by: Dai, Zhenwen, et al.
Published: (2024)
by: Dai, Zhenwen, et al.
Published: (2024)
Satisficing Exploration for Deep Reinforcement Learning
by: Arumugam, Dilip, et al.
Published: (2024)
by: Arumugam, Dilip, et al.
Published: (2024)
Reinforcement Learning by Guided Safe Exploration
by: Yang, Qisong, et al.
Published: (2023)
by: Yang, Qisong, et al.
Published: (2023)
Deep Dense Exploration for LLM Reinforcement Learning via Pivot-Driven Resampling
by: Guo, Yiran, et al.
Published: (2026)
by: Guo, Yiran, et al.
Published: (2026)
Bayesian Robust Aggregation for Federated Learning
by: Karakulev, Aleksandr, et al.
Published: (2025)
by: Karakulev, Aleksandr, et al.
Published: (2025)
BroRL: Scaling Reinforcement Learning via Broadened Exploration
by: Hu, Jian, et al.
Published: (2025)
by: Hu, Jian, et al.
Published: (2025)
On Efficient Bayesian Exploration in Model-Based Reinforcement Learning
by: Caron, Alberto, et al.
Published: (2025)
by: Caron, Alberto, et al.
Published: (2025)
Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning
by: Hsu, Hao-Lun, et al.
Published: (2024)
by: Hsu, Hao-Lun, et al.
Published: (2024)
Efficient Reinforcement Learning via Decoupling Exploration and Utilization
by: Yang, Jingpu, et al.
Published: (2023)
by: Yang, Jingpu, et al.
Published: (2023)
Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning
by: Wang, Yiran, et al.
Published: (2024)
by: Wang, Yiran, et al.
Published: (2024)
ARD-LoRA: Dynamic Rank Allocation for Parameter-Efficient Fine-Tuning of Foundation Models with Heterogeneous Adaptation Needs
by: Shinwari, Haseeb Ullah Khan, et al.
Published: (2025)
by: Shinwari, Haseeb Ullah Khan, et al.
Published: (2025)
Enhance Exploration in Safe Reinforcement Learning with Contrastive Representation Learning
by: Doan, Duc Kien, et al.
Published: (2025)
by: Doan, Duc Kien, et al.
Published: (2025)
Enhancing Efficiency and Exploration in Reinforcement Learning for LLMs
by: Liao, Mengqi, et al.
Published: (2025)
by: Liao, Mengqi, et al.
Published: (2025)
Neighboring State-based Exploration for Reinforcement Learning
by: Li, Yu-Teng, et al.
Published: (2022)
by: Li, Yu-Teng, et al.
Published: (2022)
Variable-Agnostic Causal Exploration for Reinforcement Learning
by: Nguyen, Minh Hoang, et al.
Published: (2024)
by: Nguyen, Minh Hoang, et al.
Published: (2024)
Exploration in Knowledge Transfer Utilizing Reinforcement Learning
by: Jedlička, Adam, et al.
Published: (2024)
by: Jedlička, Adam, et al.
Published: (2024)
Is Exploration or Optimization the Problem for Deep Reinforcement Learning?
by: Berseth, Glen
Published: (2025)
by: Berseth, Glen
Published: (2025)
LESSON: Learning to Integrate Exploration Strategies for Reinforcement Learning via an Option Framework
by: Kim, Woojun, et al.
Published: (2023)
by: Kim, Woojun, et al.
Published: (2023)
LLM-Explorer: A Plug-in Reinforcement Learning Policy Exploration Enhancement Driven by Large Language Models
by: Hao, Qianyue, et al.
Published: (2025)
by: Hao, Qianyue, et al.
Published: (2025)
Controlling Underestimation Bias in Constrained Reinforcement Learning for Safe Exploration
by: Gao, Shiqing, et al.
Published: (2026)
by: Gao, Shiqing, et al.
Published: (2026)
Hybrid Belief Reinforcement Learning for Efficient Coordinated Spatial Exploration
by: Rizvi, Danish, et al.
Published: (2026)
by: Rizvi, Danish, et al.
Published: (2026)
Randomized Exploration for Reinforcement Learning with Multinomial Logistic Function Approximation
by: Cho, Wooseong, et al.
Published: (2024)
by: Cho, Wooseong, et al.
Published: (2024)
Directed Exploration in Reinforcement Learning from Linear Temporal Logic
by: Bagatella, Marco, et al.
Published: (2024)
by: Bagatella, Marco, et al.
Published: (2024)
Is Exploration All You Need? Effective Exploration Characteristics for Transfer in Reinforcement Learning
by: Balloch, Jonathan C., et al.
Published: (2024)
by: Balloch, Jonathan C., et al.
Published: (2024)
Representation-Driven Reinforcement Learning
by: Nabati, Ofir, et al.
Published: (2023)
by: Nabati, Ofir, et al.
Published: (2023)
Similar Items
-
Distributional Reinforcement Learning with Information Bottleneck for Uncertainty-Aware DRAM Equalization
by: Usama, Muhammad, et al.
Published: (2026) -
Deep Reinforcement Learning-Based DRAM Equalizer Parameter Optimization Using Latent Representations
by: Usama, Muhammad, et al.
Published: (2025) -
Learning High-Quality Latent Representations for Anomaly Detection and Signal Integrity Enhancement in High-Speed Signals
by: Usama, Muhammad, et al.
Published: (2025) -
Real Time Headway Predictions in Urban Rail Systems and Implications for Service Control: A Deep Learning Approach
by: Usama, Muhammad, et al.
Published: (2025) -
EvoCoT: Overcoming the Exploration Bottleneck in Reinforcement Learning
by: Liu, Huanyu, et al.
Published: (2025)