-
Notifications
You must be signed in to change notification settings - Fork 1
Expand file tree
/
Copy pathpublication.html
More file actions
170 lines (145 loc) · 10.1 KB
/
publication.html
File metadata and controls
170 lines (145 loc) · 10.1 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
---
layout: single
classes: wide
author_profile: true
---
<div id="full-publication" class="section">
<h4 class="section-title">Full Publication List <small>(* indicates equal contributions)</small> </h4>
<hr class="sep">
<h6 class="section-title">International Publications </h6>
<ol class="my_list" reversed>
<li> <strong>KHAN: Knowledge-Aware Hierarchical Attention Networks for Accurate Political Stance Prediction</strong> <br>
<strong><u>Yunyong Ko</u></strong>, Seongeun Ryu, Soeun Han, Youngseung Jeon, Jaehoon Kim, Sohyun Park, Kyungsik Han, Hanghang Tong, and Sang-Wook Kim <br>
<span class="venue conf">ACM Web Conference (<strong>WWW</strong>) 2023</span>
<span class="dot-sep">•</span>
<span>[ <a href="/assets/files/WWW23-khan-paper.pdf">Paper</a> | <a href="https://github.com/yy-ko/khan-www23">Code</a> | <a href="/assets/files/WWW23-khan-presentation.pdf">Slides</a> ]</span>
</li>
<li> <strong>RealGraph-GPU: A High-Performance GPU-Based Graph Engine toward Large-Scale Real-World Network Analysis</strong> <br>
Myung-Hwan Jang, <strong><u>Yunyong Ko</u></strong>, Dongkyu Jeong, Jeong-Min Park, and Sang-Wook Kim <br>
<span class="venue conf">ACM International Conference on Information and Knowledge Management (<strong>ACM CIKM</strong>) 2022</span>
<span class="dot-sep">•</span>
<span>[<a href="/assets/files/CIKM22-realgraph-paper.pdf">Paper</a> | <a href="/assets/files/CIKM22-realgraph-poster.pdf">Poster</a>]</span>
</li>
<li> <strong>Not All Layers Are Equal: A Layer-Wise Adaptive Approach Toward Large-Scale DNN Training </strong> <br>
<strong><u>Yunyong Ko</u></strong>, Dongwon Lee, and Sang-Wook Kim <br>
<span class="venue conf">ACM Web Conference (<strong>WWW</strong>) 2022</span>
<span class="dot-sep">•</span>
<span>[ <a href="/assets/files/WWW22-lena-paper.pdf">Paper</a> | <a href="https://github.com/yy-ko/lena-www22">Code</a> | <a href="/assets/files/WWW22-lena-presentation.pdf">Slides</a> ]</span>
</li>
<li> <strong>D-FEND: A Diffusion-Based Fake News Detection Framework for News Articles Related to COVID-19</strong> <br>
So-Eun Han, <strong><u>Yunyong Ko</u></strong>, Yusim Kim, Heejin Park, Seongsu Oh, and Sang-Wook Kim<br>
<span class="venue conf">ACM Symposium on Applied Computing (<strong>ACM SAC</strong>) 2022</span>
<span class="dot-sep">•</span>
<span>[ <a href="/assets/files/SAC22-dfend-paper.pdf">Paper</a> ]</span>
</li>
<li> <strong>SHAT: A Novel Asynchronous Training Algorithm That Provides Fast Model Convergence in Distributed Deep Learning</strong> <br>
<strong><u>Yunyong Ko</u></strong> and Sang-Wook Kim <br>
<span class="venue journal"> <strong>Applied Sciences </strong> (SCIE) 2022 </span>
<span class="dot-sep">•</span>
<span>[ <a href="/assets/files/AS22-shat-paper.pdf">Paper</a> ]</span>
</li>
<li> <strong>MASCOT: A Quantization Framework for Efficient Matrix Factorization in Recommender Systems </strong> <br>
<strong><u>Yunyong Ko*</u></strong>, Jae-Su Yu*, Hong-Kyun Bae, Yongjun Park, Dongwon Lee, and Sang-Wook Kim <br>
<span class="venue conf"> IEEE International Conference on Data Mining (<strong>IEEE ICDM</strong>) 2021</span>
<span class="dot-sep">•</span>
<span>[ <a href="/assets/files/ICDM21-mascot-paper.pdf">Paper</a><span> | </span> <a href="https://github.com/yy-ko/mascot-icdm21">Code</a> <span> | </span> <a href="/assets/files/ICDM21-mascot-presentation.pdf">Slides</a> ]</span> <br>
<span class="award">Selected as one of the best-ranked papers of ICDM 2021 for fast-track journal invitation</span>
</li>
<li> <strong>ALADDIN: Asymmetric Centralized Training for Distributed Deep Learning </strong> <br>
<strong><u>Yunyong Ko</u></strong>, Kibong Choi, Hyunseung Jei, Dongwon Lee, and Sang-Wook Kim <br>
<span class="venue conf">ACM International Conference on Information and Knowledge Management (<strong>CIKM</strong>) 2021</span>
<span class="dot-sep">•</span>
<span>[ <a href="/assets/files/CIKM21-aladdin-paper.pdf">Paper</a><span> | </span> <a href="/assets/files/CIKM21-aladdin-poster.pdf">Poster</a><span> | </span> <a href="/assets/files/CIKM21-aladdin-presentation.pdf">Slides</a><span> | </span> <a href="https://sites.google.com/view/aladdin-proofs/home?authuser=0">Appendix</a> ]</span><br>
<span class="award">Selected as one of the spotlight presentations of CIKM 2021 </span>
</li>
<li> <strong>An In-Depth Analysis on Distributed Training of Deep Neural Networks </strong> <br>
<strong><u>Yunyong Ko</u></strong>, Kibong Choi, Jiwon Seo, and Sang-Wook Kim <br>
<span class="venue conf">IEEE International Parallel & Distributed Processing Symposium (<strong>IEEE IPDPS</strong>) 2021</span>
<span class="dot-sep">•</span>
<span>[ <a href="/assets/files/IPDPS21-analysis-paper.pdf">Paper</a><span> | </span> <a href="/assets/files/IPDPS21-analysis-presentation.pdf">Slides</a> ]</span> <br>
</li>
<li> <strong>Influence Maximization for Effective Advertisement in Social Networks: Problem, Solution, and Evaluation</strong> <br>
Suk-Jin Hong, <strong><u>Yunyong Ko</u></strong>, Moon-Jeung Joe, and Sang-Wook Kim <br>
<span class="venue conf">ACM Symposium on Applied Computing, (<strong>ACM SAC</strong>) 2019</span>
<span class="dot-sep">•</span>
<span>[ <a href="/assets/files/SAC19-infmax-paper.pdf">Paper</a> ]</span>
</li>
<li> <strong>Efficient and Effective Influence Maximization in Social Networks: A Hybrid-Approach </strong> <br>
<strong><u>Yunyong Ko*</u></strong>, Kyung-Jae Cho*, and Sang-Wook Kim <br>
<span class="venue journal"> <strong>Information Sciences</strong> (SCIE) 2018 </span>
<span class="dot-sep">•</span>
<span>[ <a href="/assets/files/INS18-hybrid-paper.pdf">Paper</a> ]</span> <br>
</li>
<li> <strong>Influence Maximization in Social Networks: A Target-Oriented Estimation</strong> <br>
<strong><u>Yunyong Ko</u></strong>, Dong-Kyu Chae, and Sang-Wook Kim <br>
<span class="venue journal"> <strong>Journal of Information Science</strong> (SCIE) 2018 </span>
<span class="dot-sep">•</span>
<span>[ <a href="/assets/files/JIS18-target-paper.pdf">Paper</a> ]</span> <br>
</li>
<li> <strong>Accurate Path-Based Influence Maximization in Social Networks </strong> <br>
<strong><u>Yunyong Ko</u></strong>, Dong-Kyu Chae, and Sang-Wook Kim <br>
<span class="venue conf">ACM Web Conference (<strong>WWW</strong>) 2016</span>
<span class="dot-sep">•</span>
<span>[ <a href="/assets/files/WWW16-path-paper.pdf">Paper</a> ]</span> <br>
</li>
</ol>
<h6 class="section-title">Domestic Publications </h6>
<ol class="my_list" reversed>
<li> <strong>CoAID+: COVID-19 News Cascade Dataset for Social Context Based Fake News Detection </strong> <br>
Han, S., Kang, Y., <strong><u>Ko, Y.</u></strong>, Ahn, J., Kim, Y.S., Oh, S.S., Park, H., and Kim, S.W. <br>
<span class="venue journal">KIPS Transactions on Software and Data Engineering (KTSDE), Vol. 11, No. 4, pp. 149-156, 2022</span>
<!-- <span class="dot-sep">•</span> -->
<br>
<span class="award">Received the Best Paper Award</span>
</li>
<li> <strong>Precision Switching for Efficient Matrix Factorization in Recommender Systems</strong> <br>
Yu, J.S., <strong><u>Ko, Y.</u></strong>, Bae, H.K., Kang, S., Yu, Y., Park, Y., and Kim, S.W. <br>
<span class="venue conf">KIPS Annual Spring Conference, 2021</span>
</li>
<li> <strong>Parameter Sharding for Synchronous and Asynchronous Distributed Training</strong> <br>
Jung, J., Lim, U., Park, J., Choi, K., <strong><u>Ko, Y.</u></strong>, and Kim, S.W. <br>
<span class="venue conf">Korea Software Congress (KSC), 2020</span>
<!-- <span class="dot-sep">•</span> -->
<br>
<span class="award">Selected as one of the Outstanding Papers</span>
</li>
<li> <strong>Parameter Sharding approaches for DNN Models with a Very Large Layer </strong> <br>
Choi, K., <strong><u>Ko, Y.</u></strong>, and Kim, S.W. <br>
<span class="venue conf">KIPS Annual Fall Conference, 2020</span>
</li>
<li> <strong>Performance Evaluation: Parameter sharding for Distributed Deep Learning </strong> <br>
Choi, K., <strong><u>Ko, Y.</u></strong>, Jae, H., Noh, H., and Kim, S.W. <br>
<span class="venue conf">Korea Computer Congress (KCC), 2019</span>
</li>
<li> <strong>Inter-Node Communications Methods for Distributed Deep Learning </strong> <br>
Choi, K., <strong><u>Ko, Y.</u></strong>, and Kim, S.W. <br>
<span class="venue conf">Korea Software Congress (KSC), 2018</span>
</li>
<li> <strong>A Diffusion Model for Influence Maximization in selecting advertisement agent </strong> <br>
Hong, S.J., <strong><u>Ko, Y.</u></strong>, Kim, S.W., Park, G.<br>
<span class="venue conf"> Workshop on Convergent & Smart Media Systems (CSMS), 2018</span>
</li>
<li> <strong>Accurate Ad-Effect Estimation Method based on Relevance between User and Item </strong> <br>
Hong, S.J., <strong><u>Ko, Y.</u></strong>, Kim, S.W., Park, G.<br>
<span class="venue conf"> The Korea Contents Association (KOCON), 2018</span>
</li>
<li> <strong>Effective Ad-Effect Maximization Exploiting User’s Support and Share </strong> <br>
Hong, S.J., <strong><u>Ko, Y.</u></strong>, Kim, S.W., Park, G.<br>
<span class="venue conf">KIPS Annual Spring Conference, 2018</span>
</li>
<li> <strong>Fast Influence Maximization in Social Networks</strong> <br>
<strong><u>Ko., Y.</u></strong>, Cho, K.J., and Kim, S.W. <br>
<span class="venue journal"> Journal of KIISE (JOK), Vol. 44, No. 10, pp. 1104-1111, 2017</span>
<!-- <span class="dot-sep">•</span> -->
<br>
<span class="award">Selected as one of the Outstanding Papers</span>
</li>
<li> <strong>Efficient CELF Algorithm for Community-based Influence Maximization in Social Networks</strong> <br>
<strong><u>Ko., Y.</u></strong>, Cho, K.J., and Kim, S.W. <br>
<span class="venue conf">Korea Computer Congress (KCC), 2017</span>
<!-- <span class="dot-sep">•</span> -->
<br>
<span class="award">Received the Best Presentation Award</span>
</li>
</ol>
</div>