5 papers
Learning Deep Modality-Shared Self-Expressiveness for Image Clustering with Textual Information
Xianghan Meng, Wei He, Zhiyuan Huang +1
Leveraging textual information for image clustering has emerged as a promising direction, largely owing to the powerful representations learned by Vision-Language Models (VLMs). Ex…
Mixture-of-Top-k Attention: Efficient Attention via Scalable Fast Weights
Qishuai Wen, Zhiyuan Huang, Xianghan Meng +2
The vanilla self-attention mechanism in Transformers can be viewed as a two-layer fast-weight MLP, whose weights are dynamically induced by inputs and whose hidden dimension is equ…
Multi-Modal Representation Learning via Semi-Supervised Rate Reduction for Generalized Category Discovery
Wei He, Xianghan Meng, Zhiyuan Huang +3
Generalized Category Discovery (GCD) aims to identify both known and unknown categories, with only partial labels given for the known categories, posing a challenging open-set reco…
Exploring a Principled Framework for Deep Subspace Clustering
Xianghan Meng, Zhiyuan Huang, Wei He +3
Subspace clustering is a classical unsupervised learning task, built on a basic assumption that high-dimensional data can be approximated by a union of subspaces (UoS). Nevertheles…
Neural Normalized Cut: A Differential and Generalizable Approach for Spectral Clustering
Wei He, Shangzhi Zhang, Chun-Guang Li +3
Spectral clustering, as a popular tool for data clustering, requires an eigen-decomposition step on a given affinity to obtain the spectral embedding. Nevertheless, such a step suf…