arXiv (All)
open access
Correcting Within-Group Self-Selection Bias in Prioritized Replay
Prioritized experience replay (PER) improves sample efficiency by replaying high-priority transitions, usually according to absolute temporal-difference error. In stochastic environments, PER can distort the distribution of realized outcomes replayed from transitions with the same state-action pair.
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Beyond Class Marginals: Bounding Rehearsal Gaps without Freezing Class Co-occurrence#1061369
- Replay in the Silent Degrees of Freedom: Continual Learning Without an Offline Phase#1115586
- Self-Aligned Forcing: Streaming Video Diffusion with Differentiable Noisy History#1142410
- ElasticTTT: Prior-Preserving Test-Time Tuning for Video Editing#394441
- A Historical Corpus Is Not a Historical System: Auditing Hindsight Leakage in Stateful Data Discovery#1070235
Record · ID 1051790
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive