Cover Image

Tilted Quantile Gradient Updates for Quantile-Constrained Reinforcement Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Li, Chenglin, Ruan, Guangchun, Geng, Hua
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Optimistic Reinforcement Learning with Quantile Objectives
by: Alipour-Vaezi, Mohammad, et al.
Published: (2025)

Safe Reinforcement Learning with Preference-based Constraint Inference
by: Li, Chenglin, et al.
Published: (2026)

Quantile Geometry Regularization for Distributional Reinforcement Learning
by: Zhang, Zhaofan, et al.
Published: (2026)

Federated Smoothing Proximal Gradient for Quantile Regression with Non-Convex Penalties
by: Mirzaeifard, Reza, et al.
Published: (2024)

Enhancing Spatio-temporal Quantile Forecasting with Curriculum Learning: Lessons Learned
by: Yin, Du, et al.
Published: (2024)

Distributional Reinforcement Learning with Dual Expectile-Quantile Regression
by: Jullien, Sami, et al.
Published: (2023)

Multi-Quantile Regression for Extreme Precipitation Downscaling
by: Najafi, Hamed, et al.
Published: (2026)

Localized Conformal Multi-Quantile Regression
by: Lu, Yuan
Published: (2024)

Distributional GFlowNets with Quantile Flows
by: Zhang, Dinghuai, et al.
Published: (2023)

Optimizing Quantile-based Trading Strategies in Electricity Arbitrage
by: O'Connor, Ciaran, et al.
Published: (2024)

Quantile-Free Uncertainty Quantification in Graph Neural Networks
by: park, Soyoung, et al.
Published: (2026)

Quantile Advantage Estimation: Stabilizing RLVR for LLM Reasoning
by: Wu, Junkang, et al.
Published: (2025)

Beyond MSE: Improving Precipitation Nowcasting with Multi-Quantile Regression
by: van Nieuwkoop, Gijs, et al.
Published: (2026)

Quantile Regression for Distributional Reward Models in RLHF
by: Dorka, Nicolai
Published: (2024)

Estimating Uncertainty with Implicit Quantile Network
by: Lim, Yi Hung
Published: (2024)

Conditional Quantile Estimation for Uncertain Watch Time in Short-Video Recommendation
by: Lin, Chengzhi, et al.
Published: (2024)

Just-In-Time Reinforcement Learning: Continual Learning in LLM Agents Without Gradient Updates
by: Li, Yibo, et al.
Published: (2026)

Model-Free Assessment of Simulator Fidelity via Quantile Curves
by: Iyengar, Garud, et al.
Published: (2025)

Dataset Condensation with Latent Quantile Matching
by: Wei, Wei, et al.
Published: (2024)

Probabilistic Multi-Regional Solar Power Forecasting with Any-Quantile Recurrent Neural Networks
by: Smyl, Slawek, et al.
Published: (2026)

A Quantile Regression Approach for Remaining Useful Life Estimation with State Space Models
by: Frizzo, Davide, et al.
Published: (2025)

Probabilistic Forecasting Cryptocurrencies Volatility: From Point to Quantile Forecasts
by: Dudek, Grzegorz, et al.
Published: (2025)

Graph2TS: Structure-Controlled Time Series Generation via Quantile-Graph VAEs
by: Du, Shaoshuai, et al.
Published: (2026)

Super-Level-Set Regression: Conditional Quantiles via Volume Minimization
by: Braun, Sacha, et al.
Published: (2026)

Memory Constrained Dynamic Subnetwork Update for Transfer Learning
by: Quélennec, Aël, et al.
Published: (2025)

Intentional Updates for Streaming Reinforcement Learning
by: Sharifnassab, Arsalan, et al.
Published: (2026)

Neighbourhood Transformer: Switchable Attention for Monophily-Aware Graph Learning
by: Luo, Yi, et al.
Published: (2026)

Quantile deep learning models for multi-step ahead time series prediction
by: Cheung, Jimmy, et al.
Published: (2024)

Quantile Regression, Variational Autoencoders, and Diffusion Models for Uncertainty Quantification: A Spatial Analysis of Sub-seasonal Wind Speed Prediction
by: Tian, Ganglin, et al.
Published: (2025)

Reliable Real-Time Value at Risk Estimation via Quantile Regression Forest with Conformal Calibration
by: Wang, Du-Yi, et al.
Published: (2026)

Gradient Boosting Reinforcement Learning
by: Fuhrer, Benjamin, et al.
Published: (2024)

Provably Efficient Exploration in Inverse Constrained Reinforcement Learning
by: Yue, Bo, et al.
Published: (2024)

Continual Learning as Computationally Constrained Reinforcement Learning
by: Kumar, Saurabh, et al.
Published: (2023)

State-Constrained Offline Reinforcement Learning
by: Hepburn, Charles A., et al.
Published: (2024)

Locally Constrained Representations in Reinforcement Learning
by: Nath, Somjit, et al.
Published: (2022)

ProRL: Effective Reinforcement Learning for Proactive Recommendation via Rectified Policy Gradient Estimation
by: Hou, Hongru, et al.
Published: (2026)

Gradient Inversion in Federated Reinforcement Learning
by: He, Shenghong
Published: (2025)

Large Scale Constrained Clustering With Reinforcement Learning
by: Schesch, Benedikt, et al.
Published: (2024)

Imitating Cost-Constrained Behaviors in Reinforcement Learning
by: Shao, Qian, et al.
Published: (2024)

Memory Allocation in Resource-Constrained Reinforcement Learning
by: Tamborski, Massimiliano, et al.
Published: (2025)