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feat: modernize PSO and add convergence research

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Migrate the package and examples to the tensor-native PyTorch implementation, add benchmark evidence, and add the guarded post-training convergence protocol with TensorBoard progress monitoring and hash-verified recovery.

Constraint: Preserve one-shot official-test sealing and auditable research artifacts

Rejected: Commit local .omc runs and downloaded datasets | multi-gigabyte runtime state is machine-local

Confidence: high

Scope-risk: broad

Not-tested: Production CUDA run on pieroot-server
This commit is contained in:
jung-geun
2026-09-07 22:03:25 +09:00
parent 9745bb7ad4
commit 813433000a
120 changed files with 198148 additions and 4745 deletions
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benchmark_results/pso_v5_deep_methods.csv
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section,metric,value
protocol,version,MNIST-PSO-RAW-V5 1.0.0
pilot,selected_dimension,full
single_model,test_accuracy,83.23
single_model,test_nll,0.556332
single_model,test_brier,0.253921
single_model,test_ece,0.085242
ensemble,test_accuracy,87.0
ensemble,test_nll,0.535928
ensemble,pairwise_disagreement,0.1585
1 section metric value
2 protocol version MNIST-PSO-RAW-V5 1.0.0
3 pilot selected_dimension full
4 single_model test_accuracy 83.23
5 single_model test_nll 0.556332
6 single_model test_brier 0.253921
7 single_model test_ece 0.085242
8 ensemble test_accuracy 87.0
9 ensemble test_nll 0.535928
10 ensemble pairwise_disagreement 0.1585