Cover Image

Delightful Policy Gradient

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Osband, Ian
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence Optimization and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Delightful Distributed Policy Gradient
by: Osband, Ian
Published: (2026)

Delightful Exploration
by: Osband, Ian
Published: (2026)

Does This Gradient Spark Joy?
by: Osband, Ian
Published: (2026)

Performative Policy Gradient: Optimality in Performative Reinforcement Learning
by: Basu, Debabrota, et al.
Published: (2025)

Global Convergence Guarantees for Federated Policy Gradient Methods with Adversaries
by: Ganesh, Swetha, et al.
Published: (2024)

Deterministic Policy Gradient for Reinforcement Learning with Continuous Time and State
by: Cheng, Ziheng, et al.
Published: (2025)

Delightful Gradients Accelerate Corner Escape
by: Mei, Jincheng, et al.
Published: (2026)

Towards Efficient Risk-Sensitive Policy Gradient: An Iteration Complexity Analysis
by: Liu, Rui, et al.
Published: (2024)

Policy Optimization in Hybrid Discrete-Continuous Action Spaces via Mixed Gradients
by: Alvo, Matias, et al.
Published: (2026)

Policy Gradient Methods for Risk-Sensitive Distributional Reinforcement Learning with Provable Convergence
by: Xiao, Minheng, et al.
Published: (2024)

Revisiting LQR Control from the Perspective of Receding-Horizon Policy Gradient
by: Zhang, Xiangyuan, et al.
Published: (2023)

Robust Control with Gradient Uncertainty
by: Qi, Qian
Published: (2025)

Gradient Descent Efficiency Index
by: Dhingra, Aviral
Published: (2024)

Unbiased Gradient Low-Rank Projection
by: Pan, Rui, et al.
Published: (2025)

Learning Branching Policies for MILPs with Proximal Policy Optimization
by: Mhamed, Abdelouahed Ben, et al.
Published: (2025)

Finite-Time Analysis of Gradient Descent for Shallow Transformers
by: Arda, Enes, et al.
Published: (2026)

Boosting Gradient Ascent for Continuous DR-submodular Maximization
by: Zhang, Qixin, et al.
Published: (2024)

Riemann Sum Optimization for Accurate Integrated Gradients Computation
by: Swain, Swadesh, et al.
Published: (2024)

Almost Bayesian: The Fractal Dynamics of Stochastic Gradient Descent
by: Hennick, Max, et al.
Published: (2025)

On the Convergence of (Stochastic) Gradient Descent for Kolmogorov--Arnold Networks
by: Gao, Yihang, et al.
Published: (2024)

A Unified Framework for Gradient Aggregation in Multi-Objective Optimization
by: Hu, Zeou, et al.
Published: (2026)

On the Optimal Construction of Unbiased Gradient Estimators for Zeroth-Order Optimization
by: Ma, Shaocong, et al.
Published: (2025)

Implicit Regularization of Gradient Flow on One-Layer Softmax Attention
by: Sheen, Heejune, et al.
Published: (2024)

On a Gradient Approach to Chebyshev Center Problems with Applications to Function Learning
by: Raghuvanshi, Abhinav, et al.
Published: (2026)

Weighted Low-rank Approximation via Stochastic Gradient Descent on Manifolds
by: Xu, Conglong, et al.
Published: (2025)

Rod Flow: A Continuous-Time Model for Gradient Descent at the Edge of Stability
by: Regis, Eric, et al.
Published: (2026)

Isotropic Curvature Model for Understanding Deep Learning Optimization: Is Gradient Orthogonalization Optimal?
by: Su, Weijie
Published: (2025)

On Finding Small Hyper-Gradients in Bilevel Optimization: Hardness Results and Improved Analysis
by: Chen, Lesi, et al.
Published: (2023)

A Methodology Establishing Linear Convergence of Adaptive Gradient Methods under PL Inequality
by: Chakrabarti, Kushal, et al.
Published: (2024)

Enhancing Stochastic Gradient Descent: A Unified Framework and Novel Acceleration Methods for Faster Convergence
by: Deng, Yichuan, et al.
Published: (2024)

Provable Acceleration of Nesterov's Accelerated Gradient Method over Heavy Ball Method in Training Over-Parameterized Neural Networks
by: Liu, Xin, et al.
Published: (2022)

Stability of Primal-Dual Gradient Flow Dynamics for Multi-Block Convex Optimization Problems
by: Ozaslan, Ibrahim K., et al.
Published: (2024)

Qronos: Correcting the Past by Shaping the Future... in Post-Training Quantization
by: Zhang, Shihao, et al.
Published: (2025)

R2L: Reliable Reinforcement Learning: Guaranteed Return & Reliable Policies in Reinforcement Learning
by: Farhi, Nadir
Published: (2025)

Constraint-Anchored Attribution: Feasibility-Certified Counterfactuals and Bonferroni-PAC Sufficient Subsets for Neural CO Policies
by: Lafifi, Sohaib
Published: (2026)

Kinematic Tokenization: Optimization-Based Continuous-Time Tokens for Learnable Decision Policies in Noisy Time Series
by: Kearney, Griffin
Published: (2026)

Classical and Deep Reinforcement Learning Inventory Control Policies for Pharmaceutical Supply Chains with Perishability and Non-Stationarity
by: Stranieri, Francesco, et al.
Published: (2025)

CORL: Reinforcement Learning of MILP Policies Solved via Branch and Bound
by: Anand, Akhil S, et al.
Published: (2025)

Benchmarking Reinforcement Learning via Stochastic Converse Optimality: Generating Systems with Known Optimal Policies
by: Ibrahim, Sinan, et al.
Published: (2026)

Lagrangian Index Policy for Restless Bandits with Average Reward
by: Avrachenkov, Konstantin, et al.
Published: (2024)