feat(train): Add ruvector integration — ADR-016, deps, DynamicPersonMatcher

- docs/adr/ADR-016: Full ruvector integration ADR with verified API details
  from source inspection (github.com/ruvnet/ruvector). Covers mincut,
  attn-mincut, temporal-tensor, solver, and attention at v2.0.4.
- Cargo.toml: Add ruvector-mincut, ruvector-attn-mincut, ruvector-temporal-
  tensor, ruvector-solver, ruvector-attention = "2.0.4" to workspace deps
  and wifi-densepose-train crate deps.
- metrics.rs: Add DynamicPersonMatcher wrapping ruvector_mincut::DynamicMinCut
  for subpolynomial O(n^1.5 log n) multi-frame person tracking; adds
  assignment_mincut() public entry point.
- proof.rs, trainer.rs, model.rs, dataset.rs, subcarrier.rs: Agent
  improvements to full implementations (loss decrease verification, SHA-256
  hash, LCG shuffle, ResNet18 backbone, MmFiDataset, linear interp).
- tests: test_config, test_dataset, test_metrics, test_proof, training_bench
  all added/updated. 100+ tests pass with no-default-features.

https://claude.ai/code/session_01BSBAQJ34SLkiJy4A8SoiL4

rust-port/wifi-densepose-rs/crates/wifi-densepose-train/Cargo.toml

@@ -14,6 +14,7 @@ path = "src/bin/train.rs"
 [[bin]]
 name = "verify-training"
 path = "src/bin/verify_training.rs"
+required-features = ["tch-backend"]
 
 [features]
 default = []
@@ -42,6 +43,13 @@ tch = { workspace = true, optional = true }
 # Graph algorithms (min-cut for optimal keypoint assignment)
 petgraph.workspace = true
 
+# ruvector integration (subpolynomial min-cut, sparse solvers, temporal compression, attention)
+ruvector-mincut = { workspace = true }
+ruvector-attn-mincut = { workspace = true }
+ruvector-temporal-tensor = { workspace = true }
+ruvector-solver = { workspace = true }
+ruvector-attention = { workspace = true }
+
 # Data loading
 ndarray-npy.workspace = true
 memmap2 = "0.9"