Salvato in:
| Autori principali: | , , , , |
|---|---|
| Natura: | Preprint |
| Pubblicazione: |
2025
|
| Soggetti: | |
| Accesso online: | https://arxiv.org/abs/2507.19898 |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1866915453830430720 |
|---|---|
| author | Vares, Parsa Durant, Éloi Pang, Jun Médoc, Nicolas Ghoniem, Mohammad |
| author_facet | Vares, Parsa Durant, Éloi Pang, Jun Médoc, Nicolas Ghoniem, Mohammad |
| contents | Thompson Sampling (TS) and its variants are powerful Multi-Armed Bandit algorithms used to balance exploration and exploitation strategies in active learning. Yet, their probabilistic nature often turns them into a "black box", hindering debugging and trust. We introduce TS-Insight, a visual analytics tool explicitly designed to shed light on the internal decision mechanisms of Thompson Sampling-based algorithms, for model developers. It comprises multiple plots, tracing for each arm the evolving posteriors, evidence counts, and sampling outcomes, enabling the verification, diagnosis, and explainability of exploration/exploitation dynamics. This tool aims at fostering trust and facilitating effective debugging and deployment in complex binary decision-making scenarios especially in sensitive domains requiring interpretable decision-making. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_19898 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | TS-Insight: Visualizing Thompson Sampling for Verification and XAI Vares, Parsa Durant, Éloi Pang, Jun Médoc, Nicolas Ghoniem, Mohammad Human-Computer Interaction Artificial Intelligence Machine Learning I.2.6; H.5.2 Thompson Sampling (TS) and its variants are powerful Multi-Armed Bandit algorithms used to balance exploration and exploitation strategies in active learning. Yet, their probabilistic nature often turns them into a "black box", hindering debugging and trust. We introduce TS-Insight, a visual analytics tool explicitly designed to shed light on the internal decision mechanisms of Thompson Sampling-based algorithms, for model developers. It comprises multiple plots, tracing for each arm the evolving posteriors, evidence counts, and sampling outcomes, enabling the verification, diagnosis, and explainability of exploration/exploitation dynamics. This tool aims at fostering trust and facilitating effective debugging and deployment in complex binary decision-making scenarios especially in sensitive domains requiring interpretable decision-making. |
| title | TS-Insight: Visualizing Thompson Sampling for Verification and XAI |
| topic | Human-Computer Interaction Artificial Intelligence Machine Learning I.2.6; H.5.2 |
| url | https://arxiv.org/abs/2507.19898 |