9 citations · 10 across the 4 of their papers we have counts for
7 papers
Perturbation of invariant subspaces for ill-conditioned eigensystem
He Lyu, Rongrong Wang
Given a diagonalizable matrix , we study the stability of its invariant subspaces when its matrix of eigenvectors is ill-conditioned. Let be some invariant subsp…
On the -norms of the Singular Vectors of Arbitrary Powers of a Difference Matrix with Applications to Sigma-Delta Quantization
Theodore Faust, Mark Iwen, Rayan Saab +1
Let denote the maximum magnitude of entries of a given matrix . In this paper we show that $$\max \left\{ \|U_r \|_{\max},\|V_r\|_{\max}…
Linear Convergent Decentralized Optimization with Compression
Xiaorui Liu, Yao Li, Rongrong Wang +2
Communication compression has become a key strategy to speed up distributed optimization. However, existing decentralized algorithms with compression mainly focus on compressing DG…
Manifold Denoising by Nonlinear Robust Principal Component Analysis
He Lyu, Ningyu Sha, Shuyang Qin +3
This paper extends robust principal component analysis (RPCA) to nonlinear manifolds. Suppose that the observed data matrix is the sum of a sparse component and a component drawn f…
From compressed sensing to compressed bit-streams: practical encoders, tractable decoders
Rayan Saab, Rongrong Wang, Ozgur Yilmaz
Compressed sensing is now established as an effective method for dimension reduction when the underlying signals are sparse or compressible with respect to some suitable basis or f…
Quantization of compressive samples with stable and robust recovery
Rayan Saab, Rongrong Wang, Ozgur Yilmaz
In this paper we study the quantization stage that is implicit in any compressed sensing signal acquisition paradigm. We propose using Sigma-Delta quantization and a subsequent rec…