Update LEARNING.md with Exp 3 PCA/SVD full results + v5.1 entry

Update TODO.md with Exp 3 full PCA/SVD results

Exp 3: PCA/Truncated SVD before lstsq — implemented, tested, 0 new solves

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Update TODO.md: evidence-based Phase 2 overhaul with confidence ratings, literature citations, coordinated experiment sequence

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Update LEARNING.md for v5 refactor + new entries

Update SKILL.md for v5 refactored package

Update README.md for v5 refactored package

v5 refactor: add main.py entry point (with W&B init)

v5 refactor: add submission.py (with W&B logging)

v5 refactor: add solvers/conv.py (with lstsq crash fix)

v5 refactor: add solvers/solver_registry.py

v5 refactor: add solvers/tiling.py

v5 refactor: add solvers/__init__.py

v5 refactor: add solvers/analytical.py

v5 refactor: add solvers/geometric.py

v5 refactor: add onnx_helpers.py

v5 refactor: add gather_helpers.py

v5 refactor: add profiler.py

v5 refactor: add data_loader.py

v5 refactor: add validators.py

v5 refactor: create package __init__.py

v5 refactor: add config.py

v5 refactor: add constants.py

Put W&B code back into run_task

Fix ReduceSum axes for opset 17 (axes must be tensor input, not attribute)

Phase 1: Opset 17 switch — Slice-based flip/rotate, tensor-based Pad, IR=8

Update neurogolf_solver.py

v4.3: Update LEARNING.md with closed-loop methodology, separated competitive intelligence from user strategy, updated version history

v4.3: Update SKILL.md with closed-loop methodology, development rules, updated status

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)

Create simple-onnx-processing-tools-README.md

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

Add LEARNING.md - full history, mistakes log, competitive intel, technical deep-dives

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