Deep Learning Methods for S Shaped Utility Maximisation with a Random Reference Point
Fuente:
arXiv
Saved in:
| Main Authors: | Davey, Ashley, Zheng, Harry |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Deep Learning for Constrained Utility Maximisation
by: Davey, Ashley, et al.
Published: (2020)
by: Davey, Ashley, et al.
Published: (2020)
Inference of Utilities and Time Preference in Sequential Decision-Making
by: Cao, Haoyang, et al.
Published: (2024)
by: Cao, Haoyang, et al.
Published: (2024)
Adjoint-Based Aerodynamic Shape Optimization with a Manifold Constraint Learned by Diffusion Models
by: Chen, Long, et al.
Published: (2025)
by: Chen, Long, et al.
Published: (2025)
Soft-Radial Projection for Constrained End-to-End Learning
by: Schneider, Philipp J., et al.
Published: (2026)
by: Schneider, Philipp J., et al.
Published: (2026)
Reinforcement Learning for Corporate Bond Trading: A Sell Side Perspective
by: Atkins, Samuel, et al.
Published: (2024)
by: Atkins, Samuel, et al.
Published: (2024)
S-shaped Utility Maximization with VaR Constraint and Partial Information
by: Zhu, Dongmei, et al.
Published: (2025)
by: Zhu, Dongmei, et al.
Published: (2025)
Neural networks can detect model-free static arbitrage strategies
by: Neufeld, Ariel, et al.
Published: (2023)
by: Neufeld, Ariel, et al.
Published: (2023)
Laser Scan Path Design for Controlled Microstructure in Additive Manufacturing with Integrated Reduced-Order Phase-Field Modeling and Deep Reinforcement Learning
by: Twumasi, Augustine, et al.
Published: (2025)
by: Twumasi, Augustine, et al.
Published: (2025)
Unified continuous-time q-learning for mean-field game and mean-field control problems
by: Wei, Xiaoli, et al.
Published: (2024)
by: Wei, Xiaoli, et al.
Published: (2024)
Mean-field neural networks-based algorithms for McKean-Vlasov control problems *
by: Pham, Huyên, et al.
Published: (2022)
by: Pham, Huyên, et al.
Published: (2022)
Continuous-time q-learning for mean-field control problems
by: Wei, Xiaoli, et al.
Published: (2023)
by: Wei, Xiaoli, et al.
Published: (2023)
Continuous-time reinforcement learning for optimal switching over multiple regimes
by: Huang, Yijie, et al.
Published: (2025)
by: Huang, Yijie, et al.
Published: (2025)
Solving The Dynamic Volatility Fitting Problem: A Deep Reinforcement Learning Approach
by: Gnabeyeu, Emmanuel, et al.
Published: (2024)
by: Gnabeyeu, Emmanuel, et al.
Published: (2024)
Accelerating Fleet Upgrade Decisions with Machine-Learning Enhanced Optimization
by: Chai, Kenrick Howin, et al.
Published: (2025)
by: Chai, Kenrick Howin, et al.
Published: (2025)
Regret-Optimal Federated Transfer Learning for Kernel Regression with Applications in American Option Pricing
by: Yang, Xuwei, et al.
Published: (2023)
by: Yang, Xuwei, et al.
Published: (2023)
An Online Machine Learning Multi-resolution Optimization Framework for Energy System Design Limit of Performance Analysis
by: Amusat, Oluwamayowa O., et al.
Published: (2026)
by: Amusat, Oluwamayowa O., et al.
Published: (2026)
Extended HJB Equation for Mean-Variance Stopping Problem: Vanishing Regularization Method
by: Dong, Yuchao, et al.
Published: (2025)
by: Dong, Yuchao, et al.
Published: (2025)
Reinforcement Learning for Jump-Diffusions, with Financial Applications
by: Gao, Xuefeng, et al.
Published: (2024)
by: Gao, Xuefeng, et al.
Published: (2024)
Variable Clustering via Distributionally Robust Nodewise Regression
by: Wang, Kaizheng, et al.
Published: (2022)
by: Wang, Kaizheng, et al.
Published: (2022)
Bayesian Optimization under Uncertainty for Training a Scale Parameter in Stochastic Models
by: Yadav, Akash, et al.
Published: (2025)
by: Yadav, Akash, et al.
Published: (2025)
Risk-Aware Financial Forecasting Enhanced by Machine Learning and Intuitionistic Fuzzy Multi-Criteria Decision-Making
by: Turgay, Safiye, et al.
Published: (2025)
by: Turgay, Safiye, et al.
Published: (2025)
Base Models for Parabolic Partial Differential Equations
by: Xu, Xingzi, et al.
Published: (2024)
by: Xu, Xingzi, et al.
Published: (2024)
Interpretable and Efficient Data-driven Discovery and Control of Distributed Systems
by: Wolf, Florian, et al.
Published: (2024)
by: Wolf, Florian, et al.
Published: (2024)
Generative Neural Operators of Log-Complexity Can Simultaneously Solve Infinitely Many Convex Programs
by: Kratsios, Anastasis, et al.
Published: (2025)
by: Kratsios, Anastasis, et al.
Published: (2025)
Multi-fidelity Bayesian Optimization: A Review
by: Do, Bach, et al.
Published: (2023)
by: Do, Bach, et al.
Published: (2023)
On the Impact of Feeding Cost Risk in Aquaculture Valuation and Decision Making
by: Ewald, Christian Oliver, et al.
Published: (2023)
by: Ewald, Christian Oliver, et al.
Published: (2023)
Multi-fidelity approaches for general constrained Bayesian optimization with application to aircraft design
by: Cordelier, Oihan, et al.
Published: (2026)
by: Cordelier, Oihan, et al.
Published: (2026)
Exponentially Weighted Moving Models
by: Luxenberg, Eric, et al.
Published: (2024)
by: Luxenberg, Eric, et al.
Published: (2024)
Towards Autonomous Experimentation: Bayesian Optimization over Problem Formulation Space for Accelerated Alloy Development
by: Khatamsaz, Danial, et al.
Published: (2025)
by: Khatamsaz, Danial, et al.
Published: (2025)
Inverse Reinforcement Learning via Convex Optimization
by: Zhu, Hao, et al.
Published: (2025)
by: Zhu, Hao, et al.
Published: (2025)
Controlgym: Large-Scale Control Environments for Benchmarking Reinforcement Learning Algorithms
by: Zhang, Xiangyuan, et al.
Published: (2023)
by: Zhang, Xiangyuan, et al.
Published: (2023)
Improving Surrogate Model Robustness to Perturbations for Dynamical Systems Through Machine Learning and Data Assimilation
by: Ajayakumar, Abhishek, et al.
Published: (2023)
by: Ajayakumar, Abhishek, et al.
Published: (2023)
Polynomial Scaling is Possible For Neural Operator Approximations of Structured Families of BSDEs
by: Furuya, Takashi, et al.
Published: (2024)
by: Furuya, Takashi, et al.
Published: (2024)
Neural Operators Can Play Dynamic Stackelberg Games
by: Alvarez, Guillermo, et al.
Published: (2024)
by: Alvarez, Guillermo, et al.
Published: (2024)
Minimizing Structural Vibrations via Guided Flow Matching Design Optimization
by: van Delden, Jan, et al.
Published: (2025)
by: van Delden, Jan, et al.
Published: (2025)
Continuous-Time Reinforcement Learning for Asset-Liability Management
by: Huang, Yilie
Published: (2025)
by: Huang, Yilie
Published: (2025)
The geometry of financial institutions -- Wasserstein clustering of financial data
by: Riess, Lorenz, et al.
Published: (2023)
by: Riess, Lorenz, et al.
Published: (2023)
Exploring the non-convexity in machine learning using quantum-inspired optimization
by: Kumar, Kandula Eswara Sai, et al.
Published: (2026)
by: Kumar, Kandula Eswara Sai, et al.
Published: (2026)
Solving Inverse Problem for Multi-armed Bandits via Convex Optimization
by: Zhu, Hao, et al.
Published: (2025)
by: Zhu, Hao, et al.
Published: (2025)
A data-driven framework for team selection in Fantasy Premier League
by: Ramezani, Danial, et al.
Published: (2025)
by: Ramezani, Danial, et al.
Published: (2025)
Similar Items
-
Deep Learning for Constrained Utility Maximisation
by: Davey, Ashley, et al.
Published: (2020) -
Inference of Utilities and Time Preference in Sequential Decision-Making
by: Cao, Haoyang, et al.
Published: (2024) -
Adjoint-Based Aerodynamic Shape Optimization with a Manifold Constraint Learned by Diffusion Models
by: Chen, Long, et al.
Published: (2025) -
Soft-Radial Projection for Constrained End-to-End Learning
by: Schneider, Philipp J., et al.
Published: (2026) -
Reinforcement Learning for Corporate Bond Trading: A Sell Side Perspective
by: Atkins, Samuel, et al.
Published: (2024)