Learning to Optimize Combinatorial Functions
Authors: Nir Rosenfeld, Eric Balkanski, Amir Globerson, Yaron Singer
ICML 2018 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | In this section we evaluate the performance of our method on the task of optimally choosing trending items in social media platforms. and Results: Figures 2(a) and 2(b) compare the value (number of adopters) for the chosen output of each method. As can be seen, DOPS clearly outperforms other methods by a margin. |
| Researcher Affiliation | Academia | Nir Rosenfeld 1 Eric Balkanski 1 Amir Globerson 2 Yaron Singer 1 1Harvard University 2Tel Aviv University. |
| Pseudocode | Yes | Algorithm 1 DOPS(S = {(Si, zi)}M i=1, m, α) |
| Open Source Code | No | The paper does not provide any explicit statement or link for open-source code for the methodology described. |
| Open Datasets | Yes | We evaluate the performance of our method on a benchmark dataset of propagating Twitter hashtags (Weng et al., 2013). |
| Dataset Splits | No | All pairs (Sω, zω) were randomly partitioned into a train set S and a global test set T using a 90:10 split. The paper does not explicitly mention a separate validation set or its split. |
| Hardware Specification | No | The paper does not provide any specific hardware details (e.g., GPU/CPU models, memory amounts, or detailed computer specifications) used for running its experiments. |
| Software Dependencies | No | The paper mentions optimizing using 'standard convex solvers' and 'the cutting-plane method of Joachims et al. (2009)' but does not provide specific version numbers for any software, libraries, or programming languages used in the experiments. |
| Experiment Setup | No | The paper states that 'Hyper-parameters were tuned using cross validation for all relevant methods' but does not provide specific hyperparameter values (e.g., learning rate, batch size, number of epochs) or system-level training settings. |