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..
Selling Reserved Instances in Cloud Computing
Authors: Changjun Wang, Weidong Ma, Tao Qin, Xujin Chen, Xiaodong Hu, Tie-Yan Liu
IJCAI 2015 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We use competitive analysis to evaluate the performance of our mechanisms, and show that both of the mechanisms have a competitive ratio of O(ln(k T)) under some mild assumption... We then prove that no algorithm can achieve a competitive ratio better than ln(2k T) under the same assumption. Therefore, our mechanisms are optimal within a constant factor. |
| Researcher Affiliation | Collaboration | Changjun Wang1, Weidong Ma2, Tao Qin2, Xujin Chen3, Xiaodong Hu3, Tie-Yan Liu2 1Beijing University of Technology, BJC-SEC, Beijing, China 2Microsoft Research, Beijing, China 3Chinese Academy of Sciences, Beijing, China |
| Pseudocode | Yes | Mechanism 1 Pricing rule: When job j arrives, If j does not overfill the system (i.e. t rj , dj , γj(t) + nj C 1), set price... Otherwise, set price pj = + . Allocation rule: If j accepts the price pj and pays for it, allocate nj instances to j from rj to dj. Mechanism 2 Pricing rule: When job j arrives, If AF j = , set price... Otherwise, set price pj = + . Allocation rule: If j accepts the price pj, allocate j to time interval [a j, a j + lj), where... |
| Open Source Code | No | The information is insufficient. The paper does not mention releasing any open-source code for the described methodology. |
| Open Datasets | No | The information is insufficient. The paper is theoretical and does not describe the use of any datasets, public or otherwise. |
| Dataset Splits | No | The information is insufficient. The paper is theoretical and does not describe any dataset splits (training, validation, or test) for experimental reproduction. |
| Hardware Specification | No | The information is insufficient. The paper is theoretical and does not describe any specific hardware used for experiments. |
| Software Dependencies | No | The information is insufficient. The paper is theoretical and does not mention any specific software dependencies with version numbers. |
| Experiment Setup | No | The information is insufficient. The paper is theoretical and does not describe any experimental setup details such as hyperparameters or training settings. |