v4.3: Update TODO.md with experiment queue, research loop, status key, explicit blending exclusion

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Add benign overfitting theory, double descent, LOOCV Ridge tuning, condition number diagnostics (2026-04-25)

Add lstsq conv research: Ridge regularization, stride_tricks, benign overfitting theory (2026-04-25)

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Replace TODO with roadmap (2026-04-25)

Add deep competitive analysis from notebook dissection (2026-04-25)

Update LEARNING.md: PyTorch conv results, lstsq overfitting analysis

v4.2: Add PyTorch learned conv solver (single+two-layer, multi-seed, ternary snap). Needs GPU to be practical - use on Kaggle with --conv_budget 60

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Split SKILL.md (rules/quick-ref) + LEARNING.md (history/mistakes/analysis)

v4.1: color_map via channel Gather for permutation maps (+15 pts), fix non-permutation fallback to Conv 1x1

v4: ARC-GEN validation + fitting, new analytical solvers (shift/mirror/crop/quad), s_flip opset fix, static profiler, submission.csv

v4: ARC-GEN validation, new analytical solvers, static profiler, s_flip opset fix

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Update README for v3 (306/400)

v3: 306/400 - Fix GatherElements->Gather (opset 10), add concat_enhanced, varshape_spatial_gather, conv_var_diff solvers

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v2: 293/400 tasks solved (was 128). Added variable-shape conv and diff-shape conv solvers.

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v2: add --device cpu/cuda/auto flag, fix providers

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