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.
Tensor networks for dimensionality reduction and large-scale optimization: Part 2 applications and future perspectives
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
math.OC 1years
2025 1verdicts
REJECT 1representative citing papers
citing papers explorer
-
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.