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20162022
most cited2-Wasserstein Approximation via Restricted Convex Potentials with Application to Improved Training for GANs

21 citations · 34 across the 16 of their papers we have counts for

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7 papers · 1 filter

math.OC2021

An optimal control approach to particle filtering

Qinsheng Zhang, Amirhossein Taghvaei, Yongxin Chen

We present a novel particle filtering framework for continuous-time dynamical systems with continuous-time measurements. Our approach is based on the duality between estimation and…

math.OC20201 cited

Lasso formulation of the shortest path problem

Anqi Dong, Amirhossein Taghvaei, Tryphon T. Georgiou

The shortest path problem is formulated as an -regularized regression problem, known as lasso. Based on this formulation, a connection is established between Dijkstra's shorte…

math.OC20202 cited

Maximal power output of a stochastic thermodynamic engine

Rui Fu, Amirhossein Taghvaei, Yongxin Chen +1

Classical thermodynamics aimed to quantify the efficiency of thermodynamic engines by bounding the maximal amount of mechanical energy produced compared to the amount of heat requi…

math.OC201921 cited

2-Wasserstein Approximation via Restricted Convex Potentials with Application to Improved Training for GANs

Amirhossein Taghvaei, Amin Jalali

We provide a framework to approximate the 2-Wasserstein distance and the optimal transport map, amenable to efficient training as well as statistical and geometric analysis. With t…

math.OC2018

Derivation and Extensions of the Linear Feedback Particle Filter based on Duality Formalisms

Jin W. Kim, Amirhossein Taghvaei, Prashant G. Mehta

This paper is concerned with a duality-based approach to derive the linear feedback particle filter (FPF). The FPF is a controlled interacting particle system where the control law…

math.OC2017

How regularization affects the critical points in linear networks

Amirhossein Taghvaei, Jin W. Kim, Prashant G. Mehta

This paper is concerned with the problem of representing and learning a linear transformation using a linear neural network. In recent years, there has been a growing interest in t…