A policy gradient approach for optimization of smooth risk measures
Fuente:
arXiv
Saved in:
| Main Authors: | Vijayan, Nithia, A, Prashanth L. |
|---|---|
| Format: | Preprint |
| Published: |
2022
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Smoothed functional-based gradient algorithms for off-policy reinforcement learning: A non-asymptotic viewpoint
by: Vijayan, Nithia, et al.
Published: (2021)
by: Vijayan, Nithia, et al.
Published: (2021)
Policy Gradient Methods for Distortion Risk Measures
by: Vijayan, Nithia, et al.
Published: (2021)
by: Vijayan, Nithia, et al.
Published: (2021)
Self-Interested Agents in Collaborative Machine Learning: An Incentivized Adaptive Data-Centric Framework
by: Vijayan, Nithia, et al.
Published: (2024)
by: Vijayan, Nithia, et al.
Published: (2024)
Risk-sensitive reinforcement learning using expectiles, shortfall risk and optimized certainty equivalent risk
by: Gupte, Sumedh, et al.
Published: (2026)
by: Gupte, Sumedh, et al.
Published: (2026)
Towards minimax optimal algorithms for Active Simple Hypothesis Testing
by: Vijayan, Sushant
Published: (2025)
by: Vijayan, Sushant
Published: (2025)
Some remarks on gradient dominance and LQR policy optimization
by: Sontag, Eduardo D.
Published: (2025)
by: Sontag, Eduardo D.
Published: (2025)
Optimization of utility-based shortfall risk: A non-asymptotic viewpoint
by: Gupte, Sumedh, et al.
Published: (2023)
by: Gupte, Sumedh, et al.
Published: (2023)
A policy gradient approach for Finite Horizon Constrained Markov Decision Processes
by: Guin, Soumyajit, et al.
Published: (2022)
by: Guin, Soumyajit, et al.
Published: (2022)
Control randomisation approach for policy gradient and application to reinforcement learning in optimal switching
by: Denkert, Robert, et al.
Published: (2024)
by: Denkert, Robert, et al.
Published: (2024)
Projected gradient methods for nonconvex and stochastic smooth optimization: new complexities and auto-conditioned stepsizes
by: Lan, Guanghui, et al.
Published: (2024)
by: Lan, Guanghui, et al.
Published: (2024)
An interpretable data-driven approach to optimizing clinical fall risk assessment
by: Ganjkhanloo, Fardin, et al.
Published: (2025)
by: Ganjkhanloo, Fardin, et al.
Published: (2025)
An interpretable data-driven approach to optimizing clinical fall risk assessment
by: Ganjkhanloo, Fardin, et al.
Published: (2026)
by: Ganjkhanloo, Fardin, et al.
Published: (2026)
Catastrophic-risk-aware reinforcement learning with extreme-value-theory-based policy gradients
by: Davar, Parisa, et al.
Published: (2024)
by: Davar, Parisa, et al.
Published: (2024)
Regret minimization in Linear Bandits with offline data via extended D-optimal exploration
by: Vijayan, Sushant, et al.
Published: (2025)
by: Vijayan, Sushant, et al.
Published: (2025)
Equivalence of stochastic and deterministic policy gradients
by: Todorov, Emo
Published: (2025)
by: Todorov, Emo
Published: (2025)
Policy gradient methods for ordinal policies
by: Weinberger, Simón, et al.
Published: (2025)
by: Weinberger, Simón, et al.
Published: (2025)
Uniform convergence of the smooth calibration error and its relationship with functional gradient
by: Futami, Futoshi, et al.
Published: (2025)
by: Futami, Futoshi, et al.
Published: (2025)
Softmax gradient policy for variance minimization and risk-averse multi armed bandits
by: Turinici, Gabriel
Published: (2026)
by: Turinici, Gabriel
Published: (2026)
Optimizing Shortfall Risk Metric for Learning Regression Models
by: Ramaswamy, Harish G., et al.
Published: (2025)
by: Ramaswamy, Harish G., et al.
Published: (2025)
Bayesian policy gradient and actor-critic algorithms
by: Ghavamzadeh, Mohammad, et al.
Published: (2026)
by: Ghavamzadeh, Mohammad, et al.
Published: (2026)
Black-box optimization of noisy functions with unknown smoothness
by: Grill, Jean-Bastien, et al.
Published: (2026)
by: Grill, Jean-Bastien, et al.
Published: (2026)
Unlearning as multi-task optimization: A normalized gradient difference approach with an adaptive learning rate
by: Bu, Zhiqi, et al.
Published: (2024)
by: Bu, Zhiqi, et al.
Published: (2024)
ISOPO: Proximal policy gradients without pi-old
by: Abrahamsen, Nilin
Published: (2025)
by: Abrahamsen, Nilin
Published: (2025)
Trainability issues in quantum policy gradients
by: Sequeira, André, et al.
Published: (2024)
by: Sequeira, André, et al.
Published: (2024)
Risk Estimation in a Markov Cost Process: Lower and Upper Bounds
by: Thoppe, Gugan, et al.
Published: (2023)
by: Thoppe, Gugan, et al.
Published: (2023)
Concentration Bounds for Optimized Certainty Equivalent Risk Estimation
by: Ghosh, Ayon, et al.
Published: (2024)
by: Ghosh, Ayon, et al.
Published: (2024)
A stochastic gradient method for trilevel optimization
by: Giovannelli, Tommaso, et al.
Published: (2025)
by: Giovannelli, Tommaso, et al.
Published: (2025)
A Finite-Sample Analysis of an Actor-Critic Algorithm for Mean-Variance Optimization in a Discounted MDP
by: Sangadi, Tejaram, et al.
Published: (2024)
by: Sangadi, Tejaram, et al.
Published: (2024)
q-exponential family for policy optimization
by: Zhu, Lingwei, et al.
Published: (2024)
by: Zhu, Lingwei, et al.
Published: (2024)
Policy Newton methods for Distortion Riskmetrics
by: Pachal, Soumen, et al.
Published: (2025)
by: Pachal, Soumen, et al.
Published: (2025)
Learning in complex action spaces without policy gradients
by: Tavakoli, Arash, et al.
Published: (2024)
by: Tavakoli, Arash, et al.
Published: (2024)
Generalization ability and Vulnerabilities to adversarial perturbations: Two sides of the same coin
by: Lee, Jung Hoon, et al.
Published: (2022)
by: Lee, Jung Hoon, et al.
Published: (2022)
Risk and optimal policies in bandit experiments
by: Adusumilli, Karun
Published: (2021)
by: Adusumilli, Karun
Published: (2021)
Spiking Neural Network: a low power solution for physical layer authentication
by: Lee, Jung Hoon, et al.
Published: (2025)
by: Lee, Jung Hoon, et al.
Published: (2025)
Minimum mean-squared error estimation with bandit feedback
by: Ghosh, Ayon, et al.
Published: (2022)
by: Ghosh, Ayon, et al.
Published: (2022)
Generalized Random Direction Newton Algorithms for Stochastic Optimization
by: Pachal, Soumen, et al.
Published: (2026)
by: Pachal, Soumen, et al.
Published: (2026)
Reinforcement Learning for Exponential Utility: Algorithms and Convergence in Discounted MDPs
by: Thoppe, Gugan, et al.
Published: (2026)
by: Thoppe, Gugan, et al.
Published: (2026)
A note on convergence of Wasserstein policy optimization
by: Šiška, David, et al.
Published: (2026)
by: Šiška, David, et al.
Published: (2026)
Exploring gauge-fixing conditions with gradient-based optimization
by: Detmold, William, et al.
Published: (2024)
by: Detmold, William, et al.
Published: (2024)
Per-example gradients: a new frontier for understanding and improving optimizers
by: Roulet, Vincent, et al.
Published: (2025)
by: Roulet, Vincent, et al.
Published: (2025)
Similar Items
-
Smoothed functional-based gradient algorithms for off-policy reinforcement learning: A non-asymptotic viewpoint
by: Vijayan, Nithia, et al.
Published: (2021) -
Policy Gradient Methods for Distortion Risk Measures
by: Vijayan, Nithia, et al.
Published: (2021) -
Self-Interested Agents in Collaborative Machine Learning: An Incentivized Adaptive Data-Centric Framework
by: Vijayan, Nithia, et al.
Published: (2024) -
Risk-sensitive reinforcement learning using expectiles, shortfall risk and optimized certainty equivalent risk
by: Gupte, Sumedh, et al.
Published: (2026) -
Towards minimax optimal algorithms for Active Simple Hypothesis Testing
by: Vijayan, Sushant
Published: (2025)