158 citations · 274 across the 9 of their papers we have counts for
9 papers
FedSysID: A Federated Approach to Sample-Efficient System Identification
Han Wang, Leonardo F. Toso, James Anderson
We study the problem of learning a linear system model from the observations of clients. The catch: Each client is observing data from a different dynamical system. This work a…
FedADMM: A Federated Primal-Dual Algorithm Allowing Partial Participation
Han Wang, Siddartha Marella, James Anderson
Federated learning is a framework for distributed optimization that places emphasis on communication efficiency. In particular, it follows a client-server broadcast model and is pa…
Learning Linear Models Using Distributed Iterative Hessian Sketching
Han Wang, James Anderson
This work considers the problem of learning the Markov parameters of a linear system from observed data. Recent non-asymptotic system identification results have characterized the…
Large-Scale System Identification Using a Randomized SVD
Han Wang, James Anderson
Learning a dynamical system from input/output data is a fundamental task in the control design pipeline. In the partially observed setting there are two components to identificatio…
Universal 3-Dimensional Perturbations for Black-Box Attacks on Video Recognition Systems
Shangyu Xie, Han Wang, Yu Kong +1
Widely deployed deep neural network (DNN) models have been proven to be vulnerable to adversarial perturbations in many applications (e.g., image, audio and text classifications).…
Masked Face Image Classification with Sparse Representation based on Majority Voting Mechanism
Han Wang
Sparse approximation is the problem to find the sparsest linear combination for a signal from a redundant dictionary, which is widely applied in signal processing and compressed se…