A Preprint, Dimitar Pilev
We lifted 11 functions out of this paper's own repositories and ran 0 of them in a sandbox. "Ran" means the function executed on a synthesized input and returned a value. It is not a reproduction of the paper's results.
| Repository | Role | Ran |
|---|---|---|
| snenovgmailcom/lshade_hazard_project | canonical | 0 of 11 |
| Function | Status | Where it lives |
|---|---|---|
| cec_wrap | Not yet run | snenovgmailcom/lshade_hazard_project/analysis/validate_quasi_morse.py code served (permissive licence) · get_code("f86244bd1aeddcee") |
| cec_wrap | Not yet run | snenovgmailcom/lshade_hazard_project/benchmarks/benchmark.py code served (permissive licence) · get_code("83fe7bd0e93feb15") |
| convert_history_for_pickle | Not yet run | snenovgmailcom/lshade_hazard_project/benchmarks/benchmark.py code served (permissive licence) · get_code("e0493e1857cb2f34") |
| extract_best_curve | Not yet run | snenovgmailcom/lshade_hazard_project/analysis/plot_quasi_morse.py code served (permissive licence) · get_code("5b12c12c0233990b") |
| extract_timeslice | Not yet run | snenovgmailcom/lshade_hazard_project/analysis/gamma0_validate.py code served (permissive licence) · get_code("1c75367c4528a8f8") |
| gamma0_comb | Not yet run | snenovgmailcom/lshade_hazard_project/analysis/gamma0_validate.py code served (permissive licence) · get_code("7add0d520f258833") |
| gamma0_full | Not yet run | snenovgmailcom/lshade_hazard_project/analysis/gamma0_validate.py code served (permissive licence) · get_code("5de918d2712e468c") |
| get_f_star_cec2017 | Not yet run | snenovgmailcom/lshade_hazard_project/analysis/plot_quasi_morse.py code served (permissive licence) · get_code("27ec7dfc25dd4738") |
| load_runs | Not yet run | snenovgmailcom/lshade_hazard_project/analysis/plot_quasi_morse.py code served (permissive licence) · get_code("a9db344bcccc8706") |
| pad_and_envelope | Not yet run | snenovgmailcom/lshade_hazard_project/benchmarks/benchmark.py code served (permissive licence) · get_code("18c9355e7acae597") |
| ts | Not yet run | snenovgmailcom/lshade_hazard_project/analysis/validate_quasi_morse.py code served (permissive licence) · get_code("7e213629171c1cf7") |
Some links come from the archived Papers with Code dataset (CC BY-SA 4.0): attribution and licence.
We study first-hitting times in Differential Evolution (DE) through a conditional hazard framework. Instead of analyzing convergence via Markov-chain transition kernels or drift arguments, we express the survival probability of a measurable target set A as a product of conditional first-hit probabilities (hazards) p t = P(E t | F t-1 ). This yields distribution-free identities for survival and explicit tail bounds whenever deterministic lower bounds on the hazard hold on the survival event. For the L-SHADE algorithm with current-to-pbest/1 mutation, we construct a checkable algorithmic witness event L t under which the conditional hazard admits an explicit lower bound depending only on sampling rules, population size, and crossover statistics. This separates theoretical constants from empirical event frequencies and explains why worst-case constant-hazard bounds are typically conservative. We complement the theory with a Kaplan-Meier survival analysis on the CEC2017 benchmark suite. Across functions and budgets, we identify three distinct empirical regimes: (i) strongly clustered success, where hitting times concentrate in short bursts; (ii) approximately geometric tails, where a constant-hazard model is accurate; and (iii) intractable cases with no observed hits within the evaluation horizon. The results show that while constant-hazard bounds provide valid tail envelopes, the practical behavior of L-SHADE is governed by burst-like transitions rather than homogeneous per-generation success probabilities.
The same record, over MCP at https://syntology.ai/mcp:
get_harvested_code_for_paper("2601.11499")
get_code_for_paper("2601.11499")
have("2601.11499")
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