TESALOCS, a hybrid of tensor-train sampling and local search, reports order-of-magnitude gains over gradient-only methods on 20 100-dimensional benchmarks, though the experimental baseline is incomplete.
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High-dimensional Optimization with Low Rank Tensor Sampling and Local Search
TESALOCS, a hybrid of tensor-train sampling and local search, reports order-of-magnitude gains over gradient-only methods on 20 100-dimensional benchmarks, though the experimental baseline is incomplete.