Symmetric Graph Convolutional Autoencoder for Unsupervised Graph Representation Learning (1908.02441v1)

Abstract: We propose a symmetric graph convolutional autoencoder which produces a low-dimensional latent representation from a graph. In contrast to the existing graph autoencoders with asymmetric decoder parts, the proposed autoencoder has a newly designed decoder which builds a completely symmetric autoencoder form. For the reconstruction of node features, the decoder is designed based on Laplacian sharpening as the counterpart of Laplacian smoothing of the encoder, which allows utilizing the graph structure in the whole processes of the proposed autoencoder architecture. In order to prevent the numerical instability of the network caused by the Laplacian sharpening introduction, we further propose a new numerically stable form of the Laplacian sharpening by incorporating the signed graphs. In addition, a new cost function which finds a latent representation and a latent affinity matrix simultaneously is devised to boost the performance of image clustering tasks. The experimental results on clustering, link prediction and visualization tasks strongly support that the proposed model is stable and outperforms various state-of-the-art algorithms.

• The paper presents a symmetric graph convolutional autoencoder that achieves robust unsupervised graph representation learning.
• It employs a balanced encoder-decoder framework to capture intricate graph structures through convolutional feature encoding.
• Experimental results validate its effectiveness in preserving graph topology and outperforming traditional graph models on key benchmarks.

Analysis of Author Guidelines for ICCV Proceedings

This document presents a comprehensive analysis in the form of author guidelines stipulated for submission to the International Conference on Computer Vision (ICCV). It is structured to address critical areas necessary for the successful preparation, formatting, and submission of manuscripts in alignment with ICCV specifications.

Abstract

The abstract serves as a foundational guideline demonstrating the required formatting standards. It encapsulates a succinct overview necessary for the initial sections of a paper, emphasizing typographical choices such as italics and boldface in specified font sizes. Notably, it directs authors on spatial formatting by advising on spacing pre- and post-abstract content, which is crucial for maintaining consistency.

Document Formatting

A crucial component delineated in the document pertains to the overall formatting of the manuscript. Authors are guided on paper length requirements, specifically limiting core paper content to eight pages, excluding references, while allowing references to extend beyond this limit. Formatting rules also extend to the management of spacing, such as the indentation and justification of the text, which ensures uniform appearance.

The guidelines provide detailed instructions on typefaces, advocating for Times Roman, or its closest equivalent, stressing the uniformity in professional presentations. Moreover, the document prescribes managing illustrations, graphs, and photographs with centered orientation and ensures the printability of such content.

Blind Review Process

The document addresses nuances related to the blind review process extensively. It explores the common misconceptions about anonymizing submissions. Key points include maintaining citation practices without self-referential terms such as "my" or "our," instead quoting in third person. This ensures clear demarcation between anonymity in submissions and contributions to existing literature, which can be integral for maintaining objectivity in peer reviews.

Sections and Mathematics

Throughout, emphasis is placed on numbering sections and mathematical expressions for ease of reference. The importance of providing referable equations underscores the need for clarity and precision, facilitating smoother interactions for readers and reviewers.

Practical Implications

From a practical standpoint, these guidelines are essential in equipping authors with the procedural knowledge necessary for manuscript submission to ICCV. They effectively standardize the submission artifacts, enhance readability, and allow for scalable reviews and proceedings publication.

Future Directions

Procedural guidelines such as those presented are likely to evolve with the advancement of formatting technologies and editorial standards. Future developments may incorporate automated compliance checks or integrate more adaptive document technologies to streamline submissions, enhancing accuracy and consistency across academic publications. AI-enabled tools might further evolve to assist in real-time formatting checks or cross-referencing setup, reducing the burden on authors.

In conclusion, the document provides a comprehensive resource that addresses multiple facets of academic paper submission to ICCV. It provides a basis for uniformity across submissions, which is fundamental in maintaining the scholarly integrity and organizational professionalism of conference proceedings.