Dohyun Kwon | DeepAI

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∙ 09/04/2023

On Penalty Methods for Nonconvex Bilevel Optimization and First-Order Stochastic Approximation

In this work, we study first-order algorithms for solving Bilevel Optimi...

0 Jeongyeol Kwon, et al. ∙

∙ 06/04/2023

Complexity of Block Coordinate Descent with Proximal Regularization and Applications to Wasserstein CP-dictionary Learning

We consider the block coordinate descent methods of Gauss-Seidel type wi...

0 Dohyun Kwon, et al. ∙

∙ 01/26/2023

A Fully First-Order Method for Stochastic Bilevel Optimization

We consider stochastic unconstrained bilevel optimization problems when ...

0 Jeongyeol Kwon, et al. ∙

∙ 12/13/2022

Score-based Generative Modeling Secretly Minimizes the Wasserstein Distance

Score-based generative models are shown to achieve remarkable empirical ...

0 Dohyun Kwon, et al. ∙

∙ 10/27/2021

Training Wasserstein GANs without gradient penalties

We propose a stable method to train Wasserstein generative adversarial n...

0 Dohyun Kwon, et al. ∙

∙ 10/12/2021

Quality-Aware Deep Reinforcement Learning for Streaming in Infrastructure-Assisted Connected Vehicles

This paper proposes a deep reinforcement learning-based video streaming ...

0 Won Joon Yun, et al. ∙

∙ 01/08/2020

Multi-Agent Deep Reinforcement Learning for Cooperative Connected Vehicles

Millimeter-wave (mmWave) base station can offer abundant high capacity c...

0 Dohyun Kwon, et al. ∙

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