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Published at November 20

AGLP: A Graph Learning Perspective for Semi-supervised Domain Adaptation

cs.CV

cs.AI

Released Date: November 20, 2024

Authors: Houcheng Su¹, Mengzhu Wang², Jiao Li³, Nan Yin⁴, Li Shen⁵

Aff.: ¹University of Macau; ²Hebei University of Technology; ³UESTC; ⁴Zayed University of Artificial Intelligence, United Arab Emirates; ⁵Sun Yat-sen University

Arxiv: http://arxiv.org/abs/2411.13152v1

Method	A→C	A→P	A→R	C→A	C→P	C→R	P→A	P→C	P→R	R→A	R→C	R→P	Avg
S+T	54.0	73.1	74.2	57.6	72.3	68.3	63.5	53.8	73.1	67.8	55.7	80.8	66.2
DANN[3]	54.7	68.3	73.8	55.1	67.5	67.1	56.6	51.8	69.2	65.2	57.3	75.5	63.5
ENT[4]	61.3	79.5	79.1	64.7	79.1	70.2	62.6	85.7	71.9	73.4	66.4	86.2	74.0
APE[8]	63.9	81.1	80.2	66.6	79.9	76.8	67.1	65.2	82.0	74.0	70.4	87.7	75.7
DECOTA[26]	64.0	81.8	80.5	68.0	83.2	79.0	69.9	68.0	82.1	74.0	70.4	87.7	75.7
MME[20]	63.6	79.0	79.7	67.2	79.6	76.6	65.5	64.6	80.1	71.3	64.6	85.5	73.1
MME SLA[27]	65.9	81.1	80.5	69.2	81.9	79.4	69.7	67.4	81.9	74.7	68.4	87.4	75.6
CDAC[11]	66.7	79.0	83.6	66.7	78.0	80.0	64.1	67.2	86.2	68.7	69.7	86.2	74.7
CDAC SLA[27]	65.6	81.4	81.1	68.2	82.1	80.1	67.7	68.9	82.6	69.0	69.7	86.3	75.2
AGLP(Ours)	68.9	85.1	87.2	70.3	82.1	81.0	70.3	71.3	88.2	71.3	70.3	85.6	77.6