50 citations · 302 across the 44 of their papers we have counts for
45 papers
A Gromov--Wasserstein Geometric View of Spectrum-Preserving Graph Coarsening
Yifan Chen, Rentian Yao, Yun Yang +1
Graph coarsening is a technique for solving large-scale graph problems by working on a smaller version of the original graph, and possibly interpolating the results back to the ori…
On the Convergence of Coordinate Ascent Variational Inference
Anirban Bhattacharya, Debdeep Pati, Yun Yang
As a computational alternative to Markov chain Monte Carlo approaches, variational inference (VI) is becoming more and more popular for approximating intractable posterior distribu…
Global and Local Mixture Consistency Cumulative Learning for Long-tailed Visual Recognitions
Fei Du, Peng Yang, Qi Jia +3
In this paper, our goal is to design a simple learning paradigm for long-tail visual recognition, which not only improves the robustness of the feature extractor but also alleviate…
Statistically Optimal K-means Clustering via Nonnegative Low-rank Semidefinite Programming
Yubo Zhuang, Xiaohui Chen, Yun Yang +1
-means clustering is a widely used machine learning method for identifying patterns in large datasets. Recently, semidefinite programming (SDP) relaxations have been proposed fo…
Estimating Distributions with Low-dimensional Structures Using Mixtures of Generative Models
Rong Tang, Yun Yang
There has been a growing interest in statistical inference from data satisfying the so-called manifold hypothesis, assuming data points in the high-dimensional ambient space to lie…
Likelihood Adjusted Semidefinite Programs for Clustering Heterogeneous Data
Yubo Zhuang, Xiaohui Chen, Yun Yang
Clustering is a widely deployed unsupervised learning tool. Model-based clustering is a flexible framework to tackle data heterogeneity when the clusters have different shapes. Lik…