26 citations · 32 across the 22 of their papers we have counts for
10 papers · 1 filter
Instance Optimal Sparse Recovery from Nonlinear Observations: A Unified Framework
Junren Chen, Arian Maleki
This paper develops a unified framework for instance optimal sparse recovery from nonlinear observations. The main ingredient is a signal-dependent restricted approximate invertibi…
Near-Optimal Lower Bounds on One-Bit Compressed Sensing of Approximately Sparse Signals
Junren Chen, Arya Mazumdar, Ming Yuan
This paper provides the first near-optimal lower bounds for one-bit compressed sensing of approximately sparse signals lying in a scaled ball, which is a commonly adopted…
One-Bit Clustering for Two Component Sub-Gaussian Mixture Models
Junren Chen, Yun Yang
Clustering is a fundamental problem in statistics and machine learning. We propose the first one-bit clustering method for two-component sub-Gaussian mixture models. The method use…
Robust Instance Optimal Phase-Only Compressed Sensing
Junren Chen, Michael K. Ng, Jonathan Scarlett
Phase-only compressed sensing (PO-CS) concerns the recovery of sparse signals from the phases of complex measurements. Recent results show that sparse signals in the standard spher…
Optimal Quantized Compressed Sensing via Projected Gradient Descent
Junren Chen, Ming Yuan
This paper provides a unified treatment to the recovery of structured signals living in a star-shaped set from general quantized measurements $\mathcal{Q}(\mathbf{A}\mathbf{x}-\mat…
One-Bit Phase Retrieval: Optimal Rates and Efficient Algorithms
Junren Chen, Ming Yuan
In this paper, we study the sample complexity and develop efficient optimal algorithms for 1-bit phase retrieval: recovering a signal from phaseless…
Uniform Recovery Guarantees for Quantized Corrupted Sensing Using Structured or Generative Priors
Junren Chen, Zhaoqiang Liu, Meng Ding +1
This paper studies quantized corrupted sensing where the measurements are contaminated by unknown corruption and then quantized by a dithered uniform quantizer. We establish unifor…
Exact Thresholds for Noisy Non-Adaptive Group Testing
Junren Chen, Jonathan Scarlett
In recent years, the mathematical limits and algorithmic bounds for probabilistic group testing have become increasingly well-understood, with exact asymptotic thresholds now being…
Solving Quadratic Systems with Full-Rank Matrices Using Sparse or Generative Priors
Junren Chen, Michael K. Ng, Zhaoqiang Liu
The problem of recovering a signal from a quadratic system with full-rank ma…
Uniform Exact Reconstruction of Sparse Signals and Low-rank Matrices from Phase-Only Measurements
Junren Chen, Michael K. Ng
In phase-only compressive sensing (PO-CS), our goal is to recover low-complexity signals (e.g., sparse signals, low-rank matrices) from the phase of complex linear measurements. Wh…