阿谀奉承
发表于 2025-3-21 16:24:58
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顶点
发表于 2025-3-21 23:42:58
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carbohydrate
发表于 2025-3-22 00:50:05
Maximum Likelihood,ty distributions, and we used the Wasserstein metric to measure the distance from . to .. Finally, in Chapter 9, we considered the distance from a polynomial system . to the discriminant in the context of numerical analysis.
Expressly
发表于 2025-3-22 06:42:05
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DOLT
发表于 2025-3-22 09:02:05
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名字
发表于 2025-3-22 13:31:03
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吝啬性
发表于 2025-3-22 17:06:59
Polar Degrees,cognized this point for Euclidean distance optimization in Section 2.3, and we will see it again in Theorem 5.5 for polyhedral norms, with focus on theWasserstein metric from optimal transport theory. The punchline is that polar degrees govern linear programming over real algebraic varieties.
Substitution
发表于 2025-3-22 21:21:23
Curvature, curvature. Our main point is to explore how curvature connects to algebraic geometry. We start out with plane curves, and we then turn to more general real algebraic varieties. The third section addresses the fundamental question of how to compute the volume of a tubular neighborhood of a variety.
Control-Group
发表于 2025-3-23 03:56:56
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entice
发表于 2025-3-23 08:05:56
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