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This paper develops a precise theoretical characterization of the empirical risk landscape for multi-index models in high dimensions, proposing an incremental approximate message passing (IAMP) algorithm that achieves near-optimal performance among polynomial-time methods, using concepts from statistical physics such as replica symmetry breaking.