1 code implementation • ECCV 2020 • Sungwon Han, Sungwon Park, Sungkyu Park, Sundong Kim, Meeyoung Cha
Unsupervised image classification is a challenging computer vision task.
Ranked #1 on Image Clustering on STL-10 (Backbone metric, using extra training data)
no code implementations • NLP4IF (COLING) 2020 • Mingi Shin, Sungwon Han, Sungkyu Park, Meeyoung Cha
This paper presents a time-topic cohesive model describing the communication patterns on the coronavirus pandemic from three Asian countries.
no code implementations • 18 Apr 2024 • Sungwon Han, Hyeonho Song, Sungwon Park, Meeyoung Cha
Federated learning combines local updates from clients to produce a global model, which is susceptible to poisoning attacks.
1 code implementation • 15 Apr 2024 • Sungwon Han, Jinsung Yoon, Sercan O Arik, Tomas Pfister
The proposed FeatLLM framework only uses this simple predictive model with the discovered features at inference time.
1 code implementation • ICCV 2023 • Sungwon Han, Sungwon Park, Fangzhao Wu, Sundong Kim, Bin Zhu, Xing Xie, Meeyoung Cha
Federated learning is used to train a shared model in a decentralized way without clients sharing private data with each other.
1 code implementation • 18 Jul 2023 • Sungwon Park, Sungwon Han, Fangzhao Wu, Sundong Kim, Bin Zhu, Xing Xie, Meeyoung Cha
Evaluations of real-world scenarios across multiple datasets show that the proposed method enhances the robustness of federated learning against model poisoning attacks.
1 code implementation • 15 Mar 2023 • Sungwon Han, Seungeon Lee, Fangzhao Wu, Sundong Kim, Chuhan Wu, Xiting Wang, Xing Xie, Meeyoung Cha
Algorithmic fairness has become an important machine learning problem, especially for mission-critical Web applications.
1 code implementation • 13 Oct 2022 • Seungeon Lee, Xiting Wang, Sungwon Han, Xiaoyuan Yi, Xing Xie, Meeyoung Cha
We present SELOR, a framework for integrating self-explaining capabilities into a given deep model to achieve both high prediction performance and human precision.
1 code implementation • 19 Jul 2022 • Sungwon Han, Sungwon Park, Fangzhao Wu, Sundong Kim, Chuhan Wu, Xing Xie, Meeyoung Cha
This paper presents FedX, an unsupervised federated learning framework.
no code implementations • 29 Mar 2021 • Sungwon Han, Hyeonho Song, Seungeon Lee, Sungwon Park, Meeyoung Cha
Anomaly detection aims at identifying deviant instances from the normal data distribution.
1 code implementation • CVPR 2021 • Sungwon Park, Sungwon Han, Sundong Kim, Danu Kim, Sungkyu Park, Seunghoon Hong, Meeyoung Cha
Unsupervised image clustering methods often introduce alternative objectives to indirectly train the model and are subject to faulty predictions and overconfident results.
Ranked #1 on Image Clustering on CIFAR-100 (Train Set metric, using extra training data)
1 code implementation • 27 Oct 2020 • Sundong Kim, Tung-Duong Mai, Sungwon Han, Sungwon Park, Thi Nguyen Duc Khanh, Jaechan So, Karandeep Singh, Meeyoung Cha
We study the human-in-the-loop customs inspection scenario, where an AI-assisted algorithm supports customs officers by recommending a set of imported goods to be inspected.
1 code implementation • 22 Jun 2020 • Sungkyu Park, Sungwon Han, Jeongwook Kim, Mir Majid Molaie, Hoang Dieu Vu, Karandeep Singh, Jiyoung Han, Wonjae Lee, Meeyoung Cha
This finding calls for a need to analyze the public discourse by new measures, such as topical dynamics.
Social and Information Networks
1 code implementation • 26 Feb 2020 • Sungwon Han, Yizhan Xu, Sungwon Park, Meeyoung Cha, Cheng-Te Li
Unsupervised embedding learning aims to extract good representation from data without the need for any manual labels, which has been a critical challenge in many supervised learning tasks.
1 code implementation • 18 Dec 2019 • Sungwon Han, Donghyun Ahn, Hyunji Cha, Jeasurk Yang, Sungwon Park, Meeyoung Cha
Satellite imagery has long been an attractive data source that provides a wealth of information on human-inhabited areas.