Search Results for author: Tianjiao Ding

Found 6 papers, 2 papers with code

Efficient Maximal Coding Rate Reduction by Variational Forms

no code implementations CVPR 2022 Christina Baek, Ziyang Wu, Kwan Ho Ryan Chan, Tianjiao Ding, Yi Ma, Benjamin D. Haeffele

The principle of Maximal Coding Rate Reduction (MCR$^2$) has recently been proposed as a training objective for learning discriminative low-dimensional structures intrinsic to high-dimensional data to allow for more robust training than standard approaches, such as cross-entropy minimization.

Image Classification

Unsupervised Manifold Linearizing and Clustering

no code implementations ICCV 2023 Tianjiao Ding, Shengbang Tong, Kwan Ho Ryan Chan, Xili Dai, Yi Ma, Benjamin D. Haeffele

We consider the problem of simultaneously clustering and learning a linear representation of data lying close to a union of low-dimensional manifolds, a fundamental task in machine learning and computer vision.

Clustering Deep Clustering

Image Clustering via the Principle of Rate Reduction in the Age of Pretrained Models

1 code implementation8 Jun 2023 Tianzhe Chu, Shengbang Tong, Tianjiao Ding, Xili Dai, Benjamin David Haeffele, René Vidal, Yi Ma

In this paper, we propose a novel image clustering pipeline that leverages the powerful feature representation of large pre-trained models such as CLIP and cluster images effectively and efficiently at scale.

Clustering Image Clustering +1

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