3 papers
cs.DB2019
IDEALEM: Statistical Similarity Based Data Reduction
Dongeun Lee, Alex Sim, Jaesik Choi +1
Many applications such as scientific simulation, sensing, and power grid monitoring tend to generate massive amounts of data, which should be compressed first prior to storage and…
cs.LG2019
Solving Large-Scale 0-1 Knapsack Problems and its Application to Point Cloud Resampling
Duanshun Li, Jing Liu, Noseong Park +7
0-1 knapsack is of fundamental importance in computer science, business, operations research, etc. In this paper, we present a deep learning technique-based method to solve large-s…
cs.IT2015
Improving Imprecise Compressive Sensing Models
Dongeun Lee, Rafael Lima, Jaesik Choi
Random sampling in compressive sensing (CS) enables the compression of large amounts of input signals in an efficient manner, which is useful for many applications. CS reconstructs…