Research map / Learning theory and algorithms / Matrix and tensor methods
Newton-Type Methods for Inference in Higher-Order Markov Random Fields
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use trust-region Newton instead of first-order FISTA | Higher-order MRF inference · Tsukuba stereo | Iterations: 594 -> 357 | Helped |
| Use trust-region Newton rather than first-order methods | TRN-MRF · Higher-order MRF problems | convergence behavior | Mixed |
| Use trust-region Newton rather than AD3 | Higher-order MRF inference · House dataset, Frame 110 | convergence | Helped |
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- Efficient semidefinite-programming-based inference for binary and multi-class MRFs (NeurIPS 2020 · similarity 0.86)
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