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metadata
license: mit
tags:
  - icml2026-repro
  - single-index-models
  - gradient-descent
  - theory-reproduction

Reproduction results — "Full-Batch Gradient Descent Outperforms One-Pass SGD" (ICML 2026 #26332)

Raw and aggregated results for an independent reproduction of arXiv:2602.02431 / OpenReview QItZDBVCT0.

All numbers were produced locally on 2x NVIDIA RTX 4000 Ada with the scripts in the reproduction logbook (scripts/sim.py, scripts/sweep_spherical.py, scripts/sweep_online_sgd.py, scripts/sweep_squared_gd.py, scripts/spectral_audit.py, scripts/thm32_bound.py).

file contents
sweep_quad.csv full-batch spherical GD, σ(z)=z², per-run squared overlap (Claim 1)
sweep_trunc.csv full-batch spherical GD, σ(z)=min(z²,8) (Claims 2/5)
sweep_smooth.csv same with the C^∞ truncation of paper eq. (3.10) (robustness)
sweep_online_{trunc,quad}.csv one-pass spherical SGD baseline over a grid of η=c/d (Claim 5)
gd_trunc_r2_{traj,summary}.csv squared-loss full-batch GD, r₀=d⁻² (Claims 3/4)
gd_trunc_r15_{traj,summary}.csv squared-loss full-batch GD, r₀=d⁻¹⁵ (exact Theorem 4.1 setting)
gd_quad_r2_*, gdd_* untruncated-activation and δ-sweep controls
gd_trunc_eta*_* learning-rate sweep for the O(log d / η) phase-1 length
audit_{spectrum,uniform_bbp,indicator}.csv numerical audits of the spectral statements
thm32_bound.csv audit of the Theorem 3.2 deficit bound 1 − C(e^{−M/2} + (d/n)^{1/5})
agg_*.csv, thresholds.csv, threshold_fits.csv aggregated curves and log-d fits

Logbook: https://huggingface.co/spaces/vimarsh/repro-full-batch-gd-outperforms-one-pass-sgd-sample-complexity-separation