ISOPO: Proximal policy gradients without pi-old
Fuente:
arXiv
Saved in:
| Main Author: | Abrahamsen, Nilin |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
PROMA: Projected Microbatch Accumulation for Reference-Free Proximal Policy Updates
by: Abrahamsen, Nilin
Published: (2026)
by: Abrahamsen, Nilin
Published: (2026)
A Kaczmarz-inspired approach to accelerate the optimization of neural network wavefunctions
by: Goldshlager, Gil, et al.
Published: (2024)
by: Goldshlager, Gil, et al.
Published: (2024)
Convergence of variational Monte Carlo simulation and scale-invariant pre-training
by: Abrahamsen, Nilin, et al.
Published: (2023)
by: Abrahamsen, Nilin, et al.
Published: (2023)
Learning in complex action spaces without policy gradients
by: Tavakoli, Arash, et al.
Published: (2024)
by: Tavakoli, Arash, et al.
Published: (2024)
Transductive Off-policy Proximal Policy Optimization
by: Gan, Yaozhong, et al.
Published: (2024)
by: Gan, Yaozhong, et al.
Published: (2024)
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)
Bayesian policy gradient and actor-critic algorithms
by: Ghavamzadeh, Mohammad, et al.
Published: (2026)
by: Ghavamzadeh, Mohammad, et al.
Published: (2026)
$\pi2\text{vec}$: Policy Representations with Successor Features
by: Scarpellini, Gianluca, et al.
Published: (2023)
by: Scarpellini, Gianluca, et al.
Published: (2023)
Some remarks on gradient dominance and LQR policy optimization
by: Sontag, Eduardo D.
Published: (2025)
by: Sontag, Eduardo D.
Published: (2025)
Trainability issues in quantum policy gradients
by: Sequeira, André, et al.
Published: (2024)
by: Sequeira, André, et al.
Published: (2024)
A policy gradient approach for optimization of smooth risk measures
by: Vijayan, Nithia, et al.
Published: (2022)
by: Vijayan, Nithia, et al.
Published: (2022)
A Unified Theory of Stochastic Proximal Point Methods without Smoothness
by: Richtárik, Peter, et al.
Published: (2024)
by: Richtárik, Peter, et al.
Published: (2024)
ExO-PPO: an Extended Off-policy Proximal Policy Optimization Algorithm
by: Wang, Hanyong, et al.
Published: (2026)
by: Wang, Hanyong, et al.
Published: (2026)
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)
Off-policy Distributional Q($λ$): Distributional RL without Importance Sampling
by: Tang, Yunhao, et al.
Published: (2024)
by: Tang, Yunhao, et al.
Published: (2024)
Finding good policies in average-reward Markov Decision Processes without prior knowledge
by: Tuynman, Adrienne, et al.
Published: (2024)
by: Tuynman, Adrienne, et al.
Published: (2024)
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)
Quantum natural gradient without monotonicity
by: Sasaki, Toi, et al.
Published: (2024)
by: Sasaki, Toi, et al.
Published: (2024)
The Generalized Proximity Forest
by: Shaw, Ben, et al.
Published: (2025)
by: Shaw, Ben, et al.
Published: (2025)
Layerwise Proximal Replay: A Proximal Point Method for Online Continual Learning
by: Yoo, Jason, et al.
Published: (2024)
by: Yoo, Jason, et al.
Published: (2024)
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)
Forest Proximities for Time Series
by: Shaw, Ben, et al.
Published: (2024)
by: Shaw, Ben, et al.
Published: (2024)
Wasserstein Proximal Policy Gradient
by: Zhu, Zhaoyu, et al.
Published: (2026)
by: Zhu, Zhaoyu, et al.
Published: (2026)
Proximal-IMH: Proximal Posterior Proposals for Independent Metropolis-Hastings with Approximate Operators
by: Chen, Youguang, et al.
Published: (2026)
by: Chen, Youguang, et al.
Published: (2026)
pi-Flow: Policy-Based Few-Step Generation via Imitation Distillation
by: Chen, Hansheng, et al.
Published: (2025)
by: Chen, Hansheng, et al.
Published: (2025)
Central Path Proximal Policy Optimization
by: Milosevic, Nikola, et al.
Published: (2025)
by: Milosevic, Nikola, et al.
Published: (2025)
Proximal Iteration for Nonlinear Adaptive Lasso
by: Wycoff, Nathan, et al.
Published: (2024)
by: Wycoff, Nathan, et al.
Published: (2024)
Proximity Matters: Local Proximity Enhanced Balancing for Treatment Effect Estimation
by: Wang, Hao, et al.
Published: (2024)
by: Wang, Hao, et al.
Published: (2024)
Softmax gradient policy for variance minimization and risk-averse multi armed bandits
by: Turinici, Gabriel
Published: (2026)
by: Turinici, Gabriel
Published: (2026)
Proximal Policy Distillation
by: Spigler, Giacomo
Published: (2024)
by: Spigler, Giacomo
Published: (2024)
Bilevel reinforcement learning via the development of hyper-gradient without lower-level convexity
by: Yang, Yan, et al.
Published: (2024)
by: Yang, Yan, et al.
Published: (2024)
Deep Gaussian Process Proximal Policy Optimization
by: van der Lende, Matthijs, et al.
Published: (2025)
by: van der Lende, Matthijs, et al.
Published: (2025)
Actor-Critic Pretraining for Proximal Policy Optimization
by: Kernbach, Andreas, et al.
Published: (2026)
by: Kernbach, Andreas, et al.
Published: (2026)
Instrumental and Proximal Causal Inference with Gaussian Processes
by: Zhang, Yuqi, et al.
Published: (2026)
by: Zhang, Yuqi, et al.
Published: (2026)
Flow Matching from Viewpoint of Proximal Operators
by: Fukumizu, Kenji, et al.
Published: (2026)
by: Fukumizu, Kenji, et al.
Published: (2026)
The informativeness of the gradient revisited
by: Takhanov, Rustem
Published: (2025)
by: Takhanov, Rustem
Published: (2025)
Localized Uncertainty Quantification in Random Forests via Proximities
by: Rhodes, Jake S., et al.
Published: (2025)
by: Rhodes, Jake S., et al.
Published: (2025)
Proximal Point Nash Learning from Human Feedback
by: Tiapkin, Daniil, et al.
Published: (2025)
by: Tiapkin, Daniil, et al.
Published: (2025)
A Proximal Operator for Inducing 2:4-Sparsity
by: Kübler, Jonas M, et al.
Published: (2025)
by: Kübler, Jonas M, et al.
Published: (2025)
Similar Items
-
PROMA: Projected Microbatch Accumulation for Reference-Free Proximal Policy Updates
by: Abrahamsen, Nilin
Published: (2026) -
A Kaczmarz-inspired approach to accelerate the optimization of neural network wavefunctions
by: Goldshlager, Gil, et al.
Published: (2024) -
Convergence of variational Monte Carlo simulation and scale-invariant pre-training
by: Abrahamsen, Nilin, et al.
Published: (2023) -
Learning in complex action spaces without policy gradients
by: Tavakoli, Arash, et al.
Published: (2024) -
Transductive Off-policy Proximal Policy Optimization
by: Gan, Yaozhong, et al.
Published: (2024)