Interactive Submodular Bandit
Authors: Lin Chen, Andreas Krause, Amin Karbasi
NeurIPS 2017 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Finally, we evaluate our results on four concrete applications, including movie recommendation (on the Movie Lense data set), news recommendation (on Yahoo! Webscope dataset), interactive influence maximization (on a subset of the Facebook network), and personalized data summarization (on Reuters Corpus). In all these applications, we observe that SM-UCB consistently outperforms the prior art. |
| Researcher Affiliation | Academia | Lin Chen1,2, Andreas Krause3, Amin Karbasi1,2 1 Department of Electrical Engineering, 2 Yale Institute for Network Science, Yale University 3 Department of Computer Science, ETH Zürich |
| Pseudocode | Yes | Algorithm 1 SM-UCB |
| Open Source Code | No | The paper does not provide explicit statements or links to open-source code for the described methodology. It only provides a URL for the MovieLens dataset. |
| Open Datasets | Yes | Movie Lens dataset1 where a user-rating matrix M is provided. ... 1https://grouplens.org/datasets/movielens/ ... Yahoo! Webscope dataset R6A2. |
| Dataset Splits | No | The paper mentions using '80% of the users... for training' and 'the remaining nuser users... for testing', but does not explicitly mention or detail a separate 'validation' split as part of the experimental setup. |
| Hardware Specification | No | The paper does not specify any hardware details (e.g., GPU/CPU models, memory) used for running the experiments. |
| Software Dependencies | No | The paper does not provide specific software dependencies with version numbers (e.g., Python 3.x, PyTorch x.x) that would be needed to reproduce the experiments. |
| Experiment Setup | No | The paper describes the datasets and models used, but it does not provide specific experimental setup details such as hyperparameter values (e.g., learning rates, batch sizes, number of epochs) or optimizer settings. |