Ting-Fan Wu

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3ranked-venue papers

2as first author

0since 2021 · last 2018

—ORCID · none

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

Artificial intelligence and machine learning · 3 · 2 first-authorGraphics, computer vision, multimedia, augmented reality and games · 1

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 3 papers		Segmentation and scene understanding · 64% Learning theory · 13% Probabilistic and Bayesian machine learning · 13%
Theoretical computer science 1 paper		Algorithmic game theory and mechanism design · 100%

Topics — the 8 heaviest of 8, each with the papers that count most for it

Topic	Weight	Papers	Last	Evidence papers
Computer vision › Segmentation and scene understanding semantic segmentation	0.3	1	2018	Efficient Uncertainty Estimation for Semantic Segmentation in Videos · ECCV (1) 2018
Computer vision › Segmentation and scene understanding › video segmentation video semantic segmentation	0.3	1	2018	Efficient Uncertainty Estimation for Semantic Segmentation in Videos · ECCV (1) 2018
Machine learning › Trustworthy machine learning uncertainty estimation	0.1	1	2018	Efficient Uncertainty Estimation for Semantic Segmentation in Videos · ECCV (1) 2018
Machine learning › Learning theory › classification multiclass classification	0.1	2	2004	Probability Estimates for Multi-class Classification by Pairwise Coupling · J. Mach. Learn. Res. 2004 Probability Estimates for Multi-Class Classification by Pairwise Coupling · NIPS 2003
Machine learning › Probabilistic and Bayesian machine learning › class probability estimation pairwise coupling	0.1	2	2004	Probability Estimates for Multi-class Classification by Pairwise Coupling · J. Mach. Learn. Res. 2004 Probability Estimates for Multi-Class Classification by Pairwise Coupling · NIPS 2003
Machine learning › Learning theory classification	0.0	1	2004	Probability Estimates for Multi-class Classification by Pairwise Coupling · J. Mach. Learn. Res. 2004
Machine learning › Probabilistic and Bayesian machine learning › dynamical system linear systems	0.0	1	2003	Probability Estimates for Multi-Class Classification by Pairwise Coupling · NIPS 2003
Algorithmic game theory and mechanism design › social choice voting	0.0	1	2003	Probability Estimates for Multi-Class Classification by Pairwise Coupling · NIPS 2003

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

uncertainty estimation · 0.3pairwise coupling · 0.1linear system · 0.1probability estimation · 0.0

Year	Publication	Venue	Position
2018	Efficient Uncertainty Estimation for Semantic Segmentation in Videos Po-Yu Huang, Wan Ting Hsu, Chun-Yueh Chiu, Ting-Fan Wu, Min Sun 0001	ECCV (1)	4
2004	Probability Estimates for Multi-class Classification by Pairwise Coupling Ting-Fan Wu, Chih-Jen Lin, Ruby C. Weng	J. Mach. Learn. Res.	1
2003	Probability Estimates for Multi-Class Classification by Pairwise Coupling abstract Pairwise coupling is a popular multi-class classiﬁcation method that combines together all pairwise comparisons for each pair of classes. This paper presents two approaches for obtaining class probabilities. Both methods can be reduced to linear systems and are easy to implement. We show conceptually and experimentally that the proposed approaches are more stable than two existing popular methods: voting and [3]. Ting-Fan Wu, Chih-Jen Lin, Ruby C. Weng	NIPS	1