activity
20172020
most citedInterpreting Neural Ranking Models using Grad-CAM

10 citations · 11 across the 3 of their papers we have counts for

collaborators

5 papers

cs.LG2020

Short-term Traffic Prediction with Deep Neural Networks: A Survey

Kyungeun Lee, Moonjung Eo, Euna Jung +2

In modern transportation systems, an enormous amount of traffic data is generated every day. This has led to rapid progress in short-term traffic prediction (STTP), in which deep l…

cs.IR202010 cited

Interpreting Neural Ranking Models using Grad-CAM

Jaekeol Choi, Jungin Choi, Wonjong Rhee

Recently, applying deep neural networks in IR has become an important and timely topic. For instance, Neural Ranking Models(NRMs) have shown promising performance compared to the t…

cs.LG2019

DEEP-BO for Hyperparameter Optimization of Deep Networks

Hyunghun Cho, Yongjin Kim, Eunjung Lee +3

The performance of deep neural networks (DNN) is very sensitive to the particular choice of hyper-parameters. To make it worse, the shape of the learning curve can be significantly…

cs.LG2018

Subtask Gated Networks for Non-Intrusive Load Monitoring

Changho Shin, Sunghwan Joo, Jaeryun Yim +3

Non-intrusive load monitoring (NILM), also known as energy disaggregation, is a blind source separation problem where a household's aggregate electricity consumption is broken down…

cs.IT20171 cited

A Downstream Crosstalk Channel Estimation Method for Mix of Legacy and Vectoring-Enabled VDSL

Mehdi Mohseni, Wonjong Rhee, Georgios Ginis

With the latest technology of vectoring, DSL data rates in the order of 100Mbps have become a reality that is under field deployment. The key is to cancel crosstalk from other line…