31 citations · 62 across the 9 of their papers we have counts for
9 papers
Multi-View Encoders for Performance Prediction in LLM-Based Agentic Workflows
Patara Trirat, Wonyong Jeong, Sung Ju Hwang
Large language models (LLMs) have demonstrated remarkable capabilities across diverse tasks, but optimizing LLM-based agentic systems remains challenging due to the vast search spa…
AutoML-Agent: A Multi-Agent LLM Framework for Full-Pipeline AutoML
Patara Trirat, Wonyong Jeong, Sung Ju Hwang
Automated machine learning (AutoML) accelerates AI development by automating tasks in the development pipeline, such as optimal model search and hyperparameter tuning. Existing Aut…
Personalized Subgraph Federated Learning
Jinheon Baek, Wonyong Jeong, Jiongdao Jin +2
Subgraphs of a larger global graph may be distributed across multiple devices, and only locally accessible due to privacy restrictions, although there may be links between subgraph…
Bitwidth Heterogeneous Federated Learning with Progressive Weight Dequantization
Jaehong Yoon, Geon Park, Wonyong Jeong +1
In practical federated learning scenarios, the participating devices may have different bitwidths for computation and memory storage by design. However, despite the progress made i…
Factorized-FL: Agnostic Personalized Federated Learning with Kernel Factorization & Similarity Matching
Wonyong Jeong, Sung Ju Hwang
In real-world federated learning scenarios, participants could have their own personalized labels which are incompatible with those from other clients, due to using different label…
Task-Adaptive Neural Network Search with Meta-Contrastive Learning
Wonyong Jeong, Hayeon Lee, Gun Park +3
Most conventional Neural Architecture Search (NAS) approaches are limited in that they only generate architectures without searching for the optimal parameters. While some NAS meth…
Chimbuko: A Workflow-Level Scalable Performance Trace Analysis Tool
Sungsoo Ha, Wonyong Jeong, Gyorgy Matyasfalvi +11
Because of the limits input/output systems currently impose on high-performance computing systems, a new generation of workflows that include online data reduction and analysis is…
Federated Semi-Supervised Learning with Inter-Client Consistency & Disjoint Learning
Wonyong Jeong, Jaehong Yoon, Eunho Yang +1
While existing federated learning approaches mostly require that clients have fully-labeled data to train on, in realistic settings, data obtained at the client-side often comes wi…
Federated Continual Learning with Weighted Inter-client Transfer
Jaehong Yoon, Wonyong Jeong, Giwoong Lee +2
There has been a surge of interest in continual learning and federated learning, both of which are important in deep neural networks in real-world scenarios. Yet little research ha…