2 citations · 2 across the 14 of their papers we have counts for
8 papers · 1 filter
Cost-Sensitive Freeze-thaw Bayesian Optimization for Efficient Hyperparameter Tuning
Dong Bok Lee, Aoxuan Silvia Zhang, Byungjoo Kim +5
In this paper, we address the problem of \emph{cost-sensitive} hyperparameter optimization (HPO) built upon freeze-thaw Bayesian optimization (BO). Specifically, we assume a scenar…
Bayesian Neural Scaling Law Extrapolation with Prior-Data Fitted Networks
Dongwoo Lee, Dong Bok Lee, Steven Adriaensen +5
Scaling has been a major driver of recent advancements in deep learning. Numerous empirical studies have found that scaling laws often follow the power-law and proposed several var…
PCoreSet: Effective Active Learning through Knowledge Distillation from Vision-Language Models
Seongjae Kang, Dong Bok Lee, Hyungjoon Jang +2
Knowledge distillation (KD) is a widely used framework for training compact, task-specific models by transferring the knowledge from teacher models. However, its application to act…
FedSVD: Adaptive Orthogonalization for Private Federated Learning with LoRA
Seanie Lee, Sangwoo Park, Dong Bok Lee +5
Low-Rank Adaptation (LoRA), which introduces a product of two trainable low-rank matrices into frozen pre-trained weights, is widely used for efficient fine-tuning of language mode…
Simple yet Effective Semi-supervised Knowledge Distillation from Vision-Language Models via Dual-Head Optimization
Seongjae Kang, Dong Bok Lee, Hyungjoon Jang +1
Semi-supervised learning (SSL) has emerged as a practical solution for addressing data scarcity challenges by leveraging unlabeled data. Recently, vision-language models (VLMs), pr…
FedRand: Enhancing Privacy in Federated Learning with Randomized LoRA Subparameter Updates
Sangwoo Park, Seanie Lee, Byungjoo Kim +1
Federated Learning (FL) is a widely used framework for training models in a decentralized manner, ensuring that the central server does not have direct access to data from local cl…
Mol-LLaMA: Towards General Understanding of Molecules in Large Molecular Language Model
Dongki Kim, Wonbin Lee, Sung Ju Hwang
Understanding molecules is key to understanding organisms and driving advances in drug discovery, requiring interdisciplinary knowledge across chemistry and biology. Although large…
Cost-Sensitive Multi-Fidelity Bayesian Optimization with Transfer of Learning Curve Extrapolation
Dong Bok Lee, Aoxuan Silvia Zhang, Byungjoo Kim +4
In this paper, we address the problem of cost-sensitive multi-fidelity Bayesian Optimization (BO) for efficient hyperparameter optimization (HPO). Specifically, we assume a scenari…