Search Results for author: Heonseok Ha

Found 6 papers, 1 papers with code

FedClassAvg: Local Representation Learning for Personalized Federated Learning on Heterogeneous Neural Networks

1 code implementation25 Oct 2022 Jaehee Jang, Heonseok Ha, Dahuin Jung, Sungroh Yoon

While the existing methods require the collection of auxiliary data or model weights to generate a counterpart, FedClassAvg only requires clients to communicate with a couple of fully connected layers, which is highly communication-efficient.

Personalized Federated Learning Representation Learning +1

FICGAN: Facial Identity Controllable GAN for De-identification

no code implementations2 Oct 2021 Yonghyun Jeong, Jooyoung Choi, Sungwon Kim, Youngmin Ro, Tae-Hyun Oh, Doyeon Kim, Heonseok Ha, Sungroh Yoon

In this work, we present Facial Identity Controllable GAN (FICGAN) for not only generating high-quality de-identified face images with ensured privacy protection, but also detailed controllability on attribute preservation for enhanced data utility.

Attribute De-identification

Security and Privacy Issues in Deep Learning

no code implementations31 Jul 2018 Ho Bae, Jaehee Jang, Dahuin Jung, Hyemi Jang, Heonseok Ha, Hyungyu Lee, Sungroh Yoon

Furthermore, the privacy of the data involved in model training is also threatened by attacks such as the model-inversion attack, or by dishonest service providers of AI applications.

Deep Trustworthy Knowledge Tracing

no code implementations28 May 2018 Heonseok Ha, Uiwon Hwang, Yongjun Hong, Jahee Jang, Sungroh Yoon

Knowledge tracing (KT), a key component of an intelligent tutoring system, is a machine learning technique that estimates the mastery level of a student based on his/her past performance.

Knowledge Tracing

Energy-Based Sequence GANs for Recommendation and Their Connection to Imitation Learning

no code implementations28 Jun 2017 Jaeyoon Yoo, Heonseok Ha, Jihun Yi, Jongha Ryu, Chanju Kim, Jung-Woo Ha, Young-Han Kim, Sungroh Yoon

Recommender systems aim to find an accurate and efficient mapping from historic data of user-preferred items to a new item that is to be liked by a user.

Imitation Learning Recommendation Systems +2

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