Convergence of TD(0) under Polynomial Mixing with Nonlinear Function Approximation
Fuente:
arXiv
Saved in:
| Main Authors: | Sridhar, Anupama, Johansen, Alexander |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Convergence of Adam in Deep ReLU Networks via Directional Complexity and Kakeya Bounds
by: Sridhar, Anupama, et al.
Published: (2025)
by: Sridhar, Anupama, et al.
Published: (2025)
Echo: KV-Cache-Free Associative Recall with Spectral Koopman Operators
by: Sridhar, Anupama, et al.
Published: (2026)
by: Sridhar, Anupama, et al.
Published: (2026)
A Concentration Bound for TD(0) with Function Approximation
by: Chandak, Siddharth, et al.
Published: (2023)
by: Chandak, Siddharth, et al.
Published: (2023)
Convergence of off-policy TD(0) with linear function approximation for reversible Markov chains
by: Overmars, Maik, et al.
Published: (2025)
by: Overmars, Maik, et al.
Published: (2025)
A Finite Sample Analysis of Distributional TD Learning with Linear Function Approximation
by: Peng, Yang, et al.
Published: (2025)
by: Peng, Yang, et al.
Published: (2025)
Analysis of Off-Policy $n$-Step TD-Learning with Linear Function Approximation
by: Lim, Han-Dong, et al.
Published: (2025)
by: Lim, Han-Dong, et al.
Published: (2025)
Analysis of Off-Policy Multi-Step TD-Learning with Linear Function Approximation
by: Lee, Donghwan
Published: (2024)
by: Lee, Donghwan
Published: (2024)
Chebyshev Polynomial-Based Kolmogorov-Arnold Networks: An Efficient Architecture for Nonlinear Function Approximation
by: SS, Sidharth, et al.
Published: (2024)
by: SS, Sidharth, et al.
Published: (2024)
A Simple Finite-Time Analysis of TD Learning with Linear Function Approximation
by: Mitra, Aritra
Published: (2024)
by: Mitra, Aritra
Published: (2024)
A Finite-Time Analysis of TD Learning with Linear Function Approximation without Projections or Strong Convexity
by: Lee, Wei-Cheng, et al.
Published: (2025)
by: Lee, Wei-Cheng, et al.
Published: (2025)
Personalized Multi-Agent Average Reward TD-Learning via Joint Linear Approximation
by: Wang, Leo Muxing, et al.
Published: (2026)
by: Wang, Leo Muxing, et al.
Published: (2026)
SCAFFLSA: Taming Heterogeneity in Federated Linear Stochastic Approximation and TD Learning
by: Mangold, Paul, et al.
Published: (2024)
by: Mangold, Paul, et al.
Published: (2024)
Reinforcement Learning with Function Approximation: From Linear to Nonlinear
by: Long, Jihao, et al.
Published: (2023)
by: Long, Jihao, et al.
Published: (2023)
Polynomial Convergence of Riemannian Diffusion Models
by: Xu, Xingyu, et al.
Published: (2026)
by: Xu, Xingyu, et al.
Published: (2026)
Rethinking the Global Convergence of Softmax Policy Gradient with Linear Function Approximation
by: Lin, Max Qiushi, et al.
Published: (2025)
by: Lin, Max Qiushi, et al.
Published: (2025)
Finite-Time Decoupled Convergence in Nonlinear Two-Time-Scale Stochastic Approximation
by: Han, Yuze, et al.
Published: (2024)
by: Han, Yuze, et al.
Published: (2024)
Near-Optimal Convergence of Accelerated Gradient Methods under Generalized and $(L_0, L_1)$-Smoothness
by: Tyurin, Alexander
Published: (2025)
by: Tyurin, Alexander
Published: (2025)
Convergence of Policy Mirror Descent Beyond Compatible Function Approximation
by: Sherman, Uri, et al.
Published: (2025)
by: Sherman, Uri, et al.
Published: (2025)
Convergence Rate in Nonlinear Two-Time-Scale Stochastic Approximation with State (Time)-Dependence
by: Chen, Zixi, et al.
Published: (2025)
by: Chen, Zixi, et al.
Published: (2025)
Dimension Mixer: Group Mixing of Input Dimensions for Efficient Function Approximation
by: Sapkota, Suman, et al.
Published: (2023)
by: Sapkota, Suman, et al.
Published: (2023)
Rates of Convergence in the Central Limit Theorem for Markov Chains, with an Application to TD Learning
by: Srikant, R.
Published: (2024)
by: Srikant, R.
Published: (2024)
The Polynomial Stein Discrepancy for Assessing Moment Convergence
by: Srinivasan, Narayan, et al.
Published: (2024)
by: Srinivasan, Narayan, et al.
Published: (2024)
Convergence of Distributionally Robust Q-Learning with Linear Function Approximation
by: Mandal, Saptarshi, et al.
Published: (2025)
by: Mandal, Saptarshi, et al.
Published: (2025)
Sampling Complexity of TD and PPO in RKHS
by: Zou, Lu, et al.
Published: (2025)
by: Zou, Lu, et al.
Published: (2025)
Gauss-Newton Temporal Difference Learning with Nonlinear Function Approximation
by: Ke, Zhifa, et al.
Published: (2023)
by: Ke, Zhifa, et al.
Published: (2023)
$p$-Adic Polynomial Regression as Alternative to Neural Network for Approximating $p$-Adic Functions of Many Variables
by: Zubarev, Alexander P.
Published: (2025)
by: Zubarev, Alexander P.
Published: (2025)
Linear Convergence of Entropy-Regularized Natural Policy Gradient with Linear Function Approximation
by: Cayci, Semih, et al.
Published: (2021)
by: Cayci, Semih, et al.
Published: (2021)
NDCG-Consistent Softmax Approximation with Accelerated Convergence
by: Pu, Yuanhao, et al.
Published: (2025)
by: Pu, Yuanhao, et al.
Published: (2025)
Equivariant Polynomial Functional Networks
by: Vo, Thieu N., et al.
Published: (2024)
by: Vo, Thieu N., et al.
Published: (2024)
Machine Learning Optimized Orthogonal Basis Piecewise Polynomial Approximation
by: Waclawek, Hannes, et al.
Published: (2024)
by: Waclawek, Hannes, et al.
Published: (2024)
Bridging the Gap Between Average and Discounted TD Learning
by: Tian, Haoxing, et al.
Published: (2026)
by: Tian, Haoxing, et al.
Published: (2026)
Learning a Class of Mixed Linear Regressions: Global Convergence under General Data Conditions
by: Liu, Yujing, et al.
Published: (2025)
by: Liu, Yujing, et al.
Published: (2025)
Closing the gap between SVRG and TD-SVRG with Gradient Splitting
by: Mustafin, Arsenii, et al.
Published: (2022)
by: Mustafin, Arsenii, et al.
Published: (2022)
Universal Decision Learners
by: Mahadevan, Sridhar
Published: (2026)
by: Mahadevan, Sridhar
Published: (2026)
Kan Extension Transformers: A Categorical Unification of Attention, Diffusion, and Predict-Detach Self-Conditioning
by: Mahadevan, Sridhar
Published: (2026)
by: Mahadevan, Sridhar
Published: (2026)
Energy Optimized Piecewise Polynomial Approximation Utilizing Modern Machine Learning Optimizers
by: Waclawek, Hannes, et al.
Published: (2025)
by: Waclawek, Hannes, et al.
Published: (2025)
Polynomial Mixing for Efficient Self-supervised Speech Encoders
by: Feillet, Eva, et al.
Published: (2026)
by: Feillet, Eva, et al.
Published: (2026)
A Convergence Analysis of Approximate Message Passing with Non-Separable Functions and Applications to Multi-Class Classification
by: Çakmak, Burak, et al.
Published: (2024)
by: Çakmak, Burak, et al.
Published: (2024)
TD-Interpreter: Enhancing the Understanding of Timing Diagrams with Visual-Language Learning
by: He, Jie, et al.
Published: (2025)
by: He, Jie, et al.
Published: (2025)
True Online TD-Replan(lambda) Achieving Planning through Replaying
by: Altahhan, Abdulrahman
Published: (2025)
by: Altahhan, Abdulrahman
Published: (2025)
Similar Items
-
Convergence of Adam in Deep ReLU Networks via Directional Complexity and Kakeya Bounds
by: Sridhar, Anupama, et al.
Published: (2025) -
Echo: KV-Cache-Free Associative Recall with Spectral Koopman Operators
by: Sridhar, Anupama, et al.
Published: (2026) -
A Concentration Bound for TD(0) with Function Approximation
by: Chandak, Siddharth, et al.
Published: (2023) -
Convergence of off-policy TD(0) with linear function approximation for reversible Markov chains
by: Overmars, Maik, et al.
Published: (2025) -
A Finite Sample Analysis of Distributional TD Learning with Linear Function Approximation
by: Peng, Yang, et al.
Published: (2025)