Near-Optimal Quantum Algorithm for Minimizing the Maximal Loss
Authors: Hao Wang, Chenyi Zhang, Tongyang Li
ICLR 2024 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this paper, we conduct a systematic study for quantum algorithms and lower bounds for minimizing the maximum of N convex, Lipschitz functions. On one hand, we develop quantum algorithms with an improved complexity bound of O(Nϵ 5/3 + ϵ 8/3).1 On the other hand, we prove that quantum algorithms must take Ω(Nϵ 2/3) queries to a first order quantum oracle, showing that our dependence on N is optimal up to poly-logarithmic factors. |
| Researcher Affiliation | Academia | School of EECS Peking University Beijing, China Computer Science Department Stanford University Stanford, CA 94305, USA Center on Frontiers of Computing Studies School of Computer Science Peking University Beijing, China |
| Pseudocode | Yes | Algorithm 1: Quantum-Epoch-SGD-Proj on the exponentiated softmax Algorithm 2: Quantum sampling of the softmax distribution. |
| Open Source Code | No | The paper does not provide any links to open-source code for the described methodology or state that it is available. |
| Open Datasets | No | This paper is theoretical and does not involve experimental evaluation on datasets. Therefore, no information on training datasets is provided. |
| Dataset Splits | No | This paper is theoretical and does not involve experimental evaluation on datasets. Therefore, no information on validation splits or cross-validation is provided. |
| Hardware Specification | No | This paper is theoretical and focuses on algorithm design and lower bounds, not on empirical performance requiring specific hardware. Therefore, no hardware specifications are mentioned. |
| Software Dependencies | No | This paper is theoretical and presents algorithms and lower bounds, not an implementation. Therefore, no specific software dependencies with version numbers are mentioned. |
| Experiment Setup | No | This paper is theoretical and does not involve empirical experiments with specific setups or hyperparameters. |