Standard GNNs fail to recover linear SDP solutions, but a more expressive architecture emulates first-order solvers, achieves lower error on benchmarks, and yields up to 80% speedups when warm-starting solvers.
We define the functionf in Fact 2 asf(c∞ k ) =y t k
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On the Expressive Power of GNNs to Solve Linear SDPs
Standard GNNs fail to recover linear SDP solutions, but a more expressive architecture emulates first-order solvers, achieves lower error on benchmarks, and yields up to 80% speedups when warm-starting solvers.