Validate positive range for log-scale distribution parameters

[saivedant169]

What this PR does / why we need it

Fixes #2678.

A parameter with a logUniform or logNormal distribution and a non-positive min or max is currently admitted by the webhook and then crashes the suggestion service at math.log (hyperopt create_hyperopt_domain, and skopt's hardcoded log-uniform prior) with ValueError: math domain error.

validateParameters now rejects logUniform / logNormal parameters whose min or max parses to a value <= 0, with a clear field error, so the experiment is refused at admission instead of crashing the suggestion pod. This matches how the validator already rejects other invalid feasibleSpace values, and follows the same fail-at-admission approach as #2666.

The check only fires when the value parses as a float and is <= 0, so non-numeric min/max are left to the existing handling.

Test

Added a TestValidateParameters case (non-positive min for logUniform).

go test ./pkg/webhook/v1beta1/experiment/validator/ -run TestValidateParameters
ok  github.com/kubeflow/katib/pkg/webhook/v1beta1/experiment/validator

/kind bug

[google-oss-prow]

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[google-oss-prow]

@saivedant169: Cannot trigger testing until a trusted user reviews the PR and leaves an /ok-to-test message.

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[saivedant169]

@andreyvelich this one has been open about a week without a look. The red checks are the flaky ones (the trial-controller TestReconcileBatchJob gomock timing test and the e2e version-matrix timeouts), not the validator change, which passes. Since I can't trigger a re-run myself, could you kick the CI and take a look when you have a moment? It's a small kind/bug fix (positive-range validation for logUniform/logNormal params).