Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
Instance-Dependent Regret Bounds for Nonstochastic Linear Partial Monitoring
Authors: Federico Di Gennaro, Khaled Eldowa, Nicolò Cesa-Bianchi
NeurIPS 2025 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We derive regret bounds that depend on the game structure in a more transparent manner than previous theoretical guarantees for this paradigm. Our bounds feature instance-specific quantities that reflect the degree of alignment between observations and losses, and resemble known guarantees in the stochastic setting. Notably, they achieve the standard T rate in easy (locally observable) games and T 2/3 in hard (globally observable) games, where T is the time horizon. All the claims made in the abstract and introduction are formalized via theorems stated in the main body and formally proven in the appendix. Question: For each theoretical result, does the paper provide the full set of assumptions and a complete (and correct) proof? Answer: [Yes] The answer NA means that the paper does not include experiments. If the paper includes experiments, a No answer to this question will not be perceived well by the reviewers: Making the paper reproducible is important, regardless of whether the code and data are provided or not. |
| Researcher Affiliation | Academia | Federico Di Gennaro , EPFL, Lausanne, Switzerland EMAIL Khaled Eldowa , Università degli Studi di Milano, Milan, Italy & Politecnico di Milano, Milan, Italy EMAIL Nicolò Cesa-Bianchi Università degli Studi di Milano, Milan, Italy & Politecnico di Milano, Milan, Italy EMAIL |
| Pseudocode | Yes | Algorithm 1 Anchored Exploration-by-Optimization. Algorithm 2 Adaptive Anchored Exploration-by-Optimization |
| Open Source Code | No | The answer NA means that paper does not include experiments requiring code. |
| Open Datasets | No | The answer NA means that the paper does not include experiments. |
| Dataset Splits | No | The answer NA means that the paper does not include experiments. |
| Hardware Specification | No | The answer NA means that the paper does not include experiments. |
| Software Dependencies | No | The answer NA means that the paper does not include experiments. |
| Experiment Setup | No | The answer NA means that the paper does not include experiments. |