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Pseudospectral Bounds for Transient Amplification in Coupled Gradient Descent

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arXiv:2606. 04031v1 Announce Type: new Abstract: Coupled gradient descent--where the update of one parameter block depends on another--underlies bilevel optimization, two-time-scale stochastic approximation, and adversarial training.

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Authors: Ahanaf Hasan Ariq
Released: 2026-06-05 (2mo ago)
Topic: Related to current project
Relation to my work: Read next because Pseudospectral Bounds for Transient Amplification in Coupled Gradient Descent overlaps with clean result "Language-mismatch LoRA SFT on Qwen2.5-7B leaks the trained completion language into bystander directives the model was never trained on, absent under same-language SFT (LOW confidence)", clean result "The marker is a representational handle, not a behavioural one — sharing it between a villain persona and the assistant transfers no misalignment (HIGH confidence)", experiment "Can capability be taught through another persona?". Matching terms: under, line, another. Source: arxiv cs.LG (Machine Learning).
arXiv: 2606.04031

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