180 citations
- NAVER Cloud (South Korea)KR41 papers
- Korea Advanced Institute of Science and TechnologyKR15 papers
- Sungkyunkwan UniversityKR10 papers
- Seoul National UniversityKR9 papers
- Yonsei UniversityKR8 papers
- Virginia TechUS5 papers
- Line Corporation (Japan)JP4 papers
- University of TorontoCA4 papers
- Inha UniversityKR3 papers
- Kootenay Association for Science & TechnologyCA3 papers
- Korea UniversityKR3 papers
- Daegu Gyeongbuk Institute of Science and TechnologyKR2 papers
11 papers · 1 filter
Quotient Normalized Maximum Likelihood Criterion for Learning Bayesian Network Structures
Tomi Silander, Janne Leppä-aho, Elias Jääsaari +1
We introduce an information theoretic criterion for Bayesian network structure learning which we call quotient normalized maximum likelihood (qNML). In contrast to the closely rela…
A Scalable and Transferable Time Series Prediction Framework for Demand Forecasting
Young-Jin Park, Donghyun Kim, Frédéric Odermatt +2
Time series forecasting is one of the most essential and ubiquitous tasks in many business problems, including demand forecasting and logistics optimization. Traditional time serie…
Residual Correction in Real-Time Traffic Forecasting
Daejin Kim, Youngin Cho, Dongmin Kim +2
Predicting traffic conditions is tremendously challenging since every road is highly dependent on each other, both spatially and temporally. Recently, to capture this spatial and t…
e-CLIP: Large-Scale Vision-Language Representation Learning in E-commerce
Wonyoung Shin, Jonghun Park, Taekang Woo +3
Understanding vision and language representations of product content is vital for search and recommendation applications in e-commerce. As a backbone for online shopping platforms…
GenHPF: General Healthcare Predictive Framework with Multi-task Multi-source Learning
Kyunghoon Hur, Jungwoo Oh, Junu Kim +7
Despite the remarkable progress in the development of predictive models for healthcare, applying these algorithms on a large scale has been challenging. Algorithms trained on a par…
FedRN: Exploiting k-Reliable Neighbors Towards Robust Federated Learning
SangMook Kim, Wonyoung Shin, Soohyuk Jang +2
Robustness is becoming another important challenge of federated learning in that the data collection process in each client is naturally accompanied by noisy labels. However, it is…