8 citations · 13 across the 6 of their papers we have counts for
12 papers
Behind the Scenes of Gradient Descent: A Trajectory Analysis via Basis Function Decomposition
Jianhao Ma, Lingjun Guo, Salar Fattahi
This work analyzes the solution trajectory of gradient-based algorithms via a novel basis function decomposition. We show that, although solution trajectories of gradient-based alg…
Global Convergence of Sub-gradient Method for Robust Matrix Recovery: Small Initialization, Noisy Measurements, and Over-parameterization
Jianhao Ma, Salar Fattahi
In this work, we study the performance of sub-gradient method (SubGM) on a natural nonconvex and nonsmooth formulation of low-rank matrix recovery with -loss, where the goa…
A Graph-based Decomposition Method for Convex Quadratic Optimization with Indicators
Peijing Liu, Salar Fattahi, Andrés Gómez +1
In this paper, we consider convex quadratic optimization problems with indicator variables when the matrix defining the quadratic term in the objective is sparse. We use a grap…
Scalable Inference of Sparsely-changing Markov Random Fields with Strong Statistical Guarantees
Salar Fattahi, Andres Gomez
In this paper, we study the problem of inferring time-varying Markov random fields (MRF), where the underlying graphical model is both sparse and changes sparsely over time. Most o…
Sign-RIP: A Robust Restricted Isometry Property for Low-rank Matrix Recovery
Jianhao Ma, Salar Fattahi
Restricted isometry property (RIP), essentially stating that the linear measurements are approximately norm-preserving, plays a crucial role in studying low-rank matrix recovery pr…
Learning Partially Observed Linear Dynamical Systems from Logarithmic Number of Samples
Salar Fattahi
In this work, we study the problem of learning partially observed linear dynamical systems from a single sample trajectory. A major practical challenge in the existing system ident…