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Co-Regularized PLSA for Multi-Modal Learning

AAAI 2016 · Vision-language and multimodal › Cross-modal learning · approach: Multimodal sentiment analysis · 2 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Replace Link PLSA (identical topic compositions) with sKL coPLSA co-regularizer (ablation)coPLSA · Wikipedia i2t, topic spaceMAP: 0.247 -> 0.413Helped
Replace Link PLSA with sKL coPLSA (ablation)coPLSA · TVGraz i2t, topic spaceMAP: 0.349 -> 0.481Helped
Replace Link PLSA with sKL coPLSA (ablation)coPLSA · TVGraz i2t, semantic spaceMAP: 0.803 -> 0.850Helped
Replace Link PLSA with sKL coPLSA (ablation)coPLSA · Wikipedia t2i, semantic spaceMAP: 0.605 -> 0.724Helped
Replace SCM with sKL coPLSA (ablation)coPLSA · Wikipedia i2t, topic spaceMAP: 0.267 -> 0.413Helped
Replace SCM with sKL coPLSA (ablation)coPLSA · TVGraz t2i, semantic spaceMAP: 0.649 -> 0.850Helped
Use sKL instead of l1 co-regularizer (ablation)coPLSA · Wikipedia i2t, topic spaceMAP: 0.317 -> 0.413Helped
Use sKL instead of l1 co-regularizer (ablation)coPLSA · TVGraz i2t, topic spaceMAP: 0.359 -> 0.481Helped
Use sKL instead of l2 co-regularizer (ablation)coPLSA · TVGraz i2t, topic spaceMAP: 0.450 -> 0.481Helped
Use sKL instead of l2 co-regularizer (ablation)coPLSA · Wikipedia i2t, semantic spaceMAP: 0.706 -> 0.726Helped
Use l2 instead of l1 co-regularizer (ablation)coPLSA · TVGraz i2t, topic spaceMAP: 0.359 -> 0.450Helped
Add semantic abstraction (logistic regression mapping) to topic compositions (ablation)sKL coPLSA · TVGraz i2tMAP: 0.481 -> 0.850Helped

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