output
20032024
most citedCooperative Multi-Agent Deep Reinforcement Learning for Reliable Surveillance via Autonomous Multi-UAV Control

249 citations

Showing 2020Show all

10 papers · 1 filter

cs.LG202012 cited

Fast and Accurate Pseudoinverse with Sparse Matrix Reordering and Incremental Approach

Jinhong Jung, Lee Sael

How can we compute the pseudoinverse of a sparse feature matrix efficiently and accurately for solving optimization problems? A pseudoinverse is a generalization of a matrix invers…

cs.CV20208 cited

FixBi: Bridging Domain Spaces for Unsupervised Domain Adaptation

Jaemin Na, Heechul Jung, Hyung Jin Chang +1

Unsupervised domain adaptation (UDA) methods for learning domain invariant representations have achieved remarkable progress. However, most of the studies were based on direct adap…

cs.CV20202 cited

Restoring Spatially-Heterogeneous Distortions using Mixture of Experts Network

Sijin Kim, Namhyuk Ahn, Kyung-Ah Sohn

In recent years, deep learning-based methods have been successfully applied to the image distortion restoration tasks. However, scenarios that assume a single distortion only may n…

cond-mat.mes-hall202055 cited

Polarization and localization of single-photon emitters in hexagonal boron nitride wrinkles

Donggyu Yim, Mihyang Yu, Gichang Noh +2

Color centers in 2-dimensional hexagonal boron nitride (h-BN) have recently emerged as stable and bright single-photon emitters (SPEs) operating at room temperature. In this study,…

cs.LG20204 cited

Active Learning with Multiple Kernels

Songnam Hong, Jeongmin Chae

Online multiple kernel learning (OMKL) has provided an attractive performance in nonlinear function learning tasks. Leveraging a random feature approximation, the major drawback of…

quant-ph20205 cited

Experimental implementation of arbitrary entangled operations

Seongjin Hong, Chang Hoon Park, Yeon-Ho Choi +4

Quantum entanglement lies at the heart of quantum mechanics in both fundamental and practical aspects. The entanglement of quantum states has been studied widely, however, the enta…