Spectral Neural Networks: Approximation Theory and Optimization Landscape

no code implementations • 1 Oct 2023 • Chenghui Li, Rishi Sonthalia, Nicolas Garcia Trillos

There is a large variety of machine learning methodologies that are based on the extraction of spectral geometric information from data.

Auto-CARD: Efficient and Robust Codec Avatar Driving for Real-time Mobile Telepresence

no code implementations • CVPR 2023 • Yonggan Fu, Yuecheng Li, Chenghui Li, Jason Saragih, Peizhao Zhang, Xiaoliang Dai, Yingyan Lin

Real-time and robust photorealistic avatars for telepresence in AR/VR have been highly desired for enabling immersive photorealistic telepresence.

Neural Architecture Search

A Fast Scale-Invariant Algorithm for Non-negative Least Squares with Non-negative Data

no code implementations • 8 Mar 2022 • Jelena Diakonikolas, Chenghui Li, Swati Padmanabhan, Chaobing Song

In particular, while the oracle complexity of unconstrained least squares problems necessarily scales with one of the data matrix constants (typically the spectral norm) and these problems are solved to additive error, we show that nonnegative least squares problems with nonnegative data are solvable to multiplicative error and with complexity that is independent of any matrix constants.

Large sample spectral analysis of graph-based multi-manifold clustering

1 code implementation • NeurIPS 2023 • Nicolas Garcia Trillos, Pengfei He, Chenghui Li

We investigate sufficient conditions that similarity graphs on data sets must satisfy in order for their corresponding graph Laplacians to capture the right geometric information to solve the MMC problem.

Clustering