chore(wiki): dangling 링크 canonical 정규화 (768파일/1200건)

이름만 다른(표기 변형) [[위키링크]]를 대상 문서의 canonical 제목으로 치환해
끊겼던 1,200개 링크를 연결. 제목/파일명 정규화 일치만 적용하고 별칭 매칭은
과병합 위험으로 제외(애매성 가드). 원본은 _link_reconcile_backup/ 에 백업.
도구: Datacollect/scripts/link_reconcile_apply.mjs

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

10_Wiki/Topics/AI_and_ML/Cross-Entropy Loss.md

@@ -217,10 +217,10 @@ def mixup_loss(logits, y_a, y_b, lam):
 **기본값**: F.cross_entropy + label_smoothing 0.1 (대부분).
 
 ## 🔗 Graph
-- 부모: [[Loss-Function]] · [[Information_Theory|Information-Theory]] · [[Deep-Learning]]
+- 부모: [[Loss-Function]] · [[Information_Theory|Information-Theory]] · [[Deep Learning]]
 - 변형: [[Focal-Loss]] · [[Label-Smoothing]] · [[LLM_Optimization_and_Deployment_Strategies|Knowledge-Distillation]] · [[KL-Divergence]]
 - 응용: [[Image-Classification-Mastery]]
-- Adjacent: [[Bias-vs-Variance]] · [[Bias-Correction-Algorithm]] · [[Cognitive-Biases]]
+- Adjacent: [[Bias vs Variance Trade-off]] · [[Bias-Correction-Algorithm]] · [[Cognitive Biases]]
 
 ## 🤖 LLM 활용
 **언제**: 매 classification model. 매 LLM training. 매 distillation.
@@ -236,7 +236,7 @@ def mixup_loss(logits, y_a, y_b, lam):
 ## 🧪 검증 / 중복
 - Verified (Bishop "Pattern Recognition", Lin Focal Loss, Hinton distillation).
 - 신뢰도 A.
-- Related: [[Information_Theory|Information-Theory]] · [[Bias-vs-Variance]] · [[Bias-Correction-Algorithm]] · [[Best-of-N_Sampling]].
+- Related: [[Information_Theory|Information-Theory]] · [[Bias vs Variance Trade-off]] · [[Bias-Correction-Algorithm]] · [[Best-of-N_Sampling]].
 
 ## 🕓 Changelog
 | 날짜 | 변경 |