3 papers
math.ST2026
Bayesian online learning in the one-pass regime: Frequentist validity and uncertainty quantification
Jeyong Lee, Junhyeok Choi, Dongguen Kim +1
Bayesian online learning provides a coherent framework for sequential inference. However, its theoretical understanding remains limited, particularly in the one-pass setting. Exist…
cs.CV2026
Multimodal Dataset Distillation Made Simple by Prototype-Guided Data Synthesis
Junhyeok Choi, Sangwoo Mo, Minwoo Chae
Recent advances in multimodal learning have achieved remarkable success across diverse vision-language tasks. However, such progress heavily relies on large-scale image-text datase…
math.ST2026
Online Bernstein-von Mises theorem
Jeyong Lee, Junhyeok Choi, Minwoo Chae
Online learning is an inferential paradigm in which parameters are updated incrementally from sequentially available data, in contrast to batch learning, where the entire dataset i…