Table 7.

Results on OfficeHome-MLT.

Algorithm	F1-Score (by domain)		Accuracy (by domain)		Accuracy (by shot)
	Average	Worst	Average	Worst	Many	Medium	Few	Zero
IRM	0.755	0.686	0.757	0.685	0.826	0.764	0.568	0.550
DANN	0.795	0.710	0.798	0.717	0.856	0.805	0.642	0.550
CDANN	0.785	0.707	0.787	0.711	0.836	0.792	0.655	0.650
CORAL	0.838	0.780	0.840	0.783	0.885	0.853	0.684	0.600
MMD	0.008	0.003	0.010	0.005	0.008	0.012	0.003	0.100
Focal	0.816	0.742	0.818	0.743	0.868	0.828	0.668	0.500
CBLoss	0.825	0.746	0.826	0.749	0.874	0.845	0.632	0.600
LDAM	0.817	0.718	0.817	0.720	0.873	0.827	0.658	0.550
Bsoftmax	0.828	0.759	0.828	0.762	0.875	0.837	0.687	0.650
CRT (2-stage training)	0.836	0.770	0.838	0.775	0.889	0.849	0.677	0.600
BoDA	0.839	0.766	0.842	0.772	0.899	0.851	0.681	0.600
BoDA(2-stage training)	0.845	0.775	0.847	0.778	0.899	0.858	0.687	0.600
ERM	0.818	0.757	0.821	0.765	0.878	0.832	0.642	0.700
GroupDRO	0.818	0.730	0.821	0.734	0.882	0.830	0.645	0.600
Mixup	0.846	0.779	0.848	0.785	0.893	0.860	0.694	0.650
SagNet	0.826	0.744	0.831	0.757	0.896	0.841	0.642	0.600
MLDG	0.824	0.748	0.826	0.752	0.892	0.830	0.665	0.600
MTL	0.820	0.746	0.820	0.743	0.873	0.829	0.658	0.650
Fish	0.822	0.736	0.825	0.745	0.893	0.836	0.616	0.700
BRL (ours)	0.832	0.776	0.833	0.775	0.879	0.837	0.716	0.600
BRL (2-stage training)	0.837	0.784	0.837	0.783	0.881	0.842	0.723	0.600