1 code implementation • 5 May 2024 • Jinyu Cai, Jialong Li, Mingyue Zhang, Munan Li, Chen-Shu Wang, Kenji Tei
Social media platforms such as Twitter, Reddit, and Sina Weibo play a crucial role in global communication but often encounter strict regulations in geopolitically sensitive regions.
no code implementations • 5 May 2024 • Jinyu Cai, Jinglue Xu, Jialong Li, Takuto Ymauchi, Hitoshi Iba, Kenji Tei
Evolutionary computation (EC), as a powerful optimization algorithm, has been applied across various domains.
no code implementations • 20 Feb 2024 • Jinyu Cai, Yunhe Zhang, Zhoumin Lu, Wenzhong Guo, See-Kiong Ng
Although federated learning offers a promising solution, the prevalent non-IID problems and high communication costs present significant challenges, particularly pronounced in collaborations with graph data distributed among different participants.
no code implementations • 5 Feb 2024 • Zichen Zhu, Yang Xu, Lu Chen, Jingkai Yang, Yichuan Ma, Yiming Sun, Hailin Wen, Jiaqi Liu, Jinyu Cai, Yingzi Ma, Situo Zhang, Zihan Zhao, Liangtai Sun, Kai Yu
Rapid progress in multimodal large language models (MLLMs) highlights the need to introduce challenging yet realistic benchmarks to the academic community, while existing benchmarks primarily focus on understanding simple natural images and short context.
no code implementations • 10 Oct 2023 • Jinyu Cai, Yunhe Zhang, Jicong Fan
Under the framework, we provide three algorithms with different computational efficiencies and stabilities for anomalous graph detection.
no code implementations • 11 May 2023 • Jinyu Cai, Jialong Li, Mingyue Zhang, Kenji Tei
We propose a novel approach, Value Iteration Networks with Gated Summarization Module (GS-VIN), which incorporates two main improvements: (1) employing an Adaptive Iteration Strategy in the Value Iteration module to reduce the number of iterations, and (2) introducing a Gated Summarization module to summarize the iterative process.
1 code implementation • 13 Feb 2023 • Yunhe Zhang, Yan Sun, Jinyu Cai, Jicong Fan
Many well-known and effective anomaly detection methods assume that a reasonable decision boundary has a hypersphere shape, which however is difficult to obtain in practice and is not sufficiently compact, especially when the data are in high-dimensional spaces.
no code implementations • 5 Feb 2023 • Jinyu Cai, Yi Han, Wenzhong Guo, Jicong Fan
In this work, we study the problem of partitioning a set of graphs into different groups such that the graphs in the same group are similar while the graphs in different groups are dissimilar.
no code implementations • 9 Jun 2022 • Jinyu Cai, Wenzhong Guo, Jicong Fan
This work presents an unsupervised deep discriminant analysis for clustering.
no code implementations • 6 Jun 2022 • Jinyu Cai, Jicong Fan
This paper presents a simple yet effective method for anomaly detection.
1 code implementation • CVPR 2022 • Jinyu Cai, Jicong Fan, Wenzhong Guo, Shiping Wang, Yunhe Zhang, Zhao Zhang
The proposed method is out of the self-expressive framework, scales to the sample size linearly, and is applicable to arbitrarily large datasets and online clustering scenarios.