Cover Image

Deep Reinforcement Learning for Online Optimal Execution Strategies

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Micheli, Alessandro, Monod, Mélodie
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

NeuralSurv: Deep Survival Analysis with Bayesian Uncertainty Quantification
by: Monod, Mélodie, et al.
Published: (2025)

Diffusion Models for Inverse Problems in the Exponential Family
by: Micheli, Alessandro, et al.
Published: (2025)

Entropic Riemannian Neural Optimal Transport
by: Micheli, Alessandro, et al.
Published: (2026)

Riemannian Neural Optimal Transport
by: Micheli, Alessandro, et al.
Published: (2026)

TorchSurv: A Lightweight Package for Deep Survival Analysis
by: Monod, Mélodie, et al.
Published: (2024)

Minimax Optimal Strategy for Delayed Observations in Online Reinforcement Learning
by: Lee, Harin, et al.
Published: (2026)

Optimal Execution with Reinforcement Learning
by: Hafsi, Yadh, et al.
Published: (2024)

Reinforcement Learning in Queue-Reactive Models: Application to Optimal Execution
by: Espana, Tomas, et al.
Published: (2025)

ORVIT: Near-Optimal Online Distributionally Robust Reinforcement Learning
by: Ghosh, Debamita, et al.
Published: (2025)

Analyzing Adversarial Inputs in Deep Reinforcement Learning
by: Corsi, Davide, et al.
Published: (2024)

Online Matching via Reinforcement Learning: An Expert Policy Orchestration Strategy
by: Mignacco, Chiara, et al.
Published: (2025)

Gradient Estimation Methods of Approximate Multipliers for High-Accuracy Retraining of Deep Learning Models
by: Meng, Chang, et al.
Published: (2025)

Metric Graph Kernels via the Tropical Torelli Map
by: Cao, Yueqi, et al.
Published: (2025)

Optimal Parallelization Strategies for Active Flow Control in Deep Reinforcement Learning-Based Computational Fluid Dynamics
by: Jia, Wang, et al.
Published: (2024)

Aquatic Navigation: A Challenging Benchmark for Deep Reinforcement Learning
by: Corsi, Davide, et al.
Published: (2024)

Online Training and Pruning of Deep Reinforcement Learning Networks
by: Guenter, Valentin Frank Ingmar, et al.
Published: (2025)

Approximating Persistent Homology for Large Datasets
by: Cao, Yueqi, et al.
Published: (2022)

Image-Based Deep Reinforcement Learning with Intrinsically Motivated Stimuli: On the Execution of Complex Robotic Tasks
by: Valencia, David, et al.
Published: (2024)

Breaking Symmetry Bottlenecks in GNN Readouts
by: Talhi, Mouad, et al.
Published: (2026)

Unsupervised-to-Online Reinforcement Learning
by: Kim, Junsu, et al.
Published: (2024)

World Models Unlock Optimal Foraging Strategies in Reinforcement Learning Agents
by: Fonseca, Yesid, et al.
Published: (2025)

Near-Optimal Partially Observable Reinforcement Learning with Partial Online State Information
by: Shi, Ming, et al.
Published: (2023)

Research on Autonomous Driving Decision-making Strategies based Deep Reinforcement Learning
by: Wang, Zixiang, et al.
Published: (2024)

A Forget-and-Grow Strategy for Deep Reinforcement Learning Scaling in Continuous Control
by: Kang, Zilin, et al.
Published: (2025)

Online Pre-Training for Offline-to-Online Reinforcement Learning
by: Shin, Yongjae, et al.
Published: (2025)

Benchmarking Robustness of Deep Reinforcement Learning approaches to Online Portfolio Management
by: Velay, Marc, et al.
Published: (2023)

Restless Bandits with Individual Penalty Constraints: Near-Optimal Indices and Deep Reinforcement Learning
by: Zamir, Nida, et al.
Published: (2026)

Optimal Policy Sparsification and Low Rank Decomposition for Deep Reinforcement Learning
by: Goddla, Vikram
Published: (2024)

Online Episodic Convex Reinforcement Learning
by: Moreno, Bianca Marin, et al.
Published: (2025)

Online Control of Adaptive Large Neighborhood Search using Deep Reinforcement Learning
by: Reijnen, Robbert, et al.
Published: (2022)

Towards Active Flow Control Strategies Through Deep Reinforcement Learning
by: Montalà, Ricard, et al.
Published: (2024)

Transformer-Guided Deep Reinforcement Learning for Optimal Takeoff Trajectory Design of an eVTOL Drone
by: Roberts II, Nathan M., et al.
Published: (2025)

Online Learning of Optimal Sequential Testing Policies
by: Chen, Qiyuan, et al.
Published: (2025)

Learning Optimal Search Strategies
by: Ankirchner, Stefan, et al.
Published: (2026)

Surprisal-Guided Selection: Compute-Optimal Test-Time Strategies for Execution-Grounded Code Generation
by: Barnes, Jarrod
Published: (2026)

Deep Reinforcement Learning-driven Cross-Community Energy Interaction Optimal Scheduling
by: Li, Yang, et al.
Published: (2023)

Reinforcement Learning With Sparse-Executing Actions via Sparsity Regularization
by: Pang, Jing-Cheng, et al.
Published: (2021)

Gradual Transition from Bellman Optimality Operator to Bellman Operator in Online Reinforcement Learning
by: Omura, Motoki, et al.
Published: (2025)

Harnessing Density Ratios for Online Reinforcement Learning
by: Amortila, Philip, et al.
Published: (2024)

Online Planning for Multi-UAV Pursuit-Evasion in Unknown Environments Using Deep Reinforcement Learning
by: Chen, Jiayu, et al.
Published: (2024)