ICML2023科研海报设计
Extending Kernel PCA through Dualization: Sparsity, Robustness and Fast Algorithms
一张来自 ICML 2023 的真实会议海报，作为科研海报设计参考展示。研读作者如何排布标题、图表和结果，再设计你自己的海报。
读者能从这张海报里答出这些吗？
设计得当的海报能让路过的人几秒内抓住这些要点——可作为你自己科研海报设计的检查清单。
- →What is Kernel Principal Component Analysis (KPCA) primarily used for?
- →What is a major limitation of the classical KPCA method?
- →What is the primary goal of the paper?
- →What is a key contribution of the proposed method in the paper?
- →What approach does the paper use to solve the KPCA problem?
