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Minseop Park

dblp:220/4322 · DBLP profile ↗
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3ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 3

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
2 papers
Trustworthy machine learning · 35% Transfer learning and domain adaptation · 33% Probabilistic and Bayesian machine learning · 17%

Topics — the 6 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Machine learning › Probabilistic and Bayesian machine learning
bayesian meta-learning		 0.412020
Learning to Balance: Bayesian Meta-Learning for Imbalanced and Out-of-distribution Tasks · ICLR 2020
Machine learning › Transfer learning and domain adaptation
meta-learning		 0.412020
Learning to Balance: Bayesian Meta-Learning for Imbalanced and Out-of-distribution Tasks · ICLR 2020
Machine learning › Trustworthy machine learning
out-of-distribution generalization		 0.412020
Learning to Balance: Bayesian Meta-Learning for Imbalanced and Out-of-distribution Tasks · ICLR 2020
Machine learning › Trustworthy machine learning
robustness		 0.412020
Learning to Balance: Bayesian Meta-Learning for Imbalanced and Out-of-distribution Tasks · ICLR 2020
Machine learning › Transfer learning and domain adaptation
few-shot learning		 0.412019
Learning to Propagate Labels: Transductive Propagation Network for Few-Shot Learning · ICLR (Poster) 2019
Machine learning › Learning paradigms › semi-supervised learning › graph-based semi-supervised learning
label propagation		 0.412019
Learning to Propagate Labels: Transductive Propagation Network for Few-Shot Learning · ICLR (Poster) 2019

Methods — techniques the papers use, named apart from their topics

task balancing · 0.4bayesian meta-learning · 0.4
YearPublicationVenuePosition
2020 Learning to Balance: Bayesian Meta-Learning for Imbalanced and Out-of-distribution Tasks
Haebeom Lee, Hayeon Lee, Donghyun Na, Saehoon Kim, Minseop Park, Eunho Yang, Sung Ju Hwang
 ICLR5
2019 Learning to Propagate Labels: Transductive Propagation Network for Few-Shot Learning
Yanbin Liu 0003, Juho Lee 0001, Minseop Park, Saehoon Kim, Eunho Yang, Sung Ju Hwang, Yi Yang 0001
 ICLR (Poster)3
2019 Classifying heart conditions based on class probability output networks
Han Bin Bae, Minseop Park, Rhee Man Kil, Hee Yong Youn
 Neurocomputing2