Object categorization using adaptive graph-based semi-supervised learning
In this chapter, we introduce a new efficient graph construction method that can be used by
many automatic learning tasks. Unlike the mainstream, our proposed method
simultaneously estimates the graph structure and its edge weights through sample coding
via data self-representativeness. Compared with the recent ℓ 1 graph based on sparse
coding, the proposed coding scheme has an analytical solution and thus is more efficient.
The chapter has two main contributions. Firstly, it introduces a principled two-phase …
many automatic learning tasks. Unlike the mainstream, our proposed method
simultaneously estimates the graph structure and its edge weights through sample coding
via data self-representativeness. Compared with the recent ℓ 1 graph based on sparse
coding, the proposed coding scheme has an analytical solution and thus is more efficient.
The chapter has two main contributions. Firstly, it introduces a principled two-phase …
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