Research map / Graph learning / Graph self-supervised learning
Large-Scale Graph-Based Semi-Supervised Learning via Tree Laplacian Solver
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| use TbTL tree solver instead of LLGC-PCG | graph-based SSL · Extended MNIST l=10000 | accuracy (%): 96.92 -> 96.77 | Hurt |
| use TbTL instead of LLGC-PCG | graph-based SSL · Extended MNIST l=10000 | labeling time (s): 265.2 -> 2.2 | Helped |
| use TbTL tree solver instead of GRF | graph-based SSL · MNIST 8NN graph | running time (s): 73.65 -> 0.15 | Helped |
| use TbTL instead of GPA | tree-based SSL · Extended MNIST l=100 | accuracy (%): 89.63 -> 89.97 | No clear effect |
| use TbTL instead of full graph GRF/LLGC (graph sparsification) | graph-based SSL · small datasets | accuracy | Hurt |
| use tree-based sparse approximation instead of low-rank (AGR, Eigen) | scalable SSL · Extended MNIST l=100 | accuracy (%): 82.27 -> 89.97 | Helped |
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