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mixture

【「iAcro超话」放映室】午间剧场 —— MMM ver.7 Maximum Mixture Meeting「灵感与启发超话」iAcrophobia官方微博的微博视频

[CL]《Your Mixture-of-Experts LLM Is Secretly an Embedding Model For Free》Z Li, T Zhou [University of Maryland] (2024)网页链接「机器学习」「人工智能」「论文」

[LG]《ExpertFlow: Optimized Expert Activation and Token Allocation for Efficient Mixture-of-Experts Inference》X He, S Zhang, Y Wang, H Yin... [A*STAR & Hong Kong University of Science and Technology] (2024)网页链接「机器学习」「人工智能」「论文」

【ARIA: An Open Multimodal Native Mixture-of-Experts Model】网页链接ARIA：一种开放的多模式原生混合专家模型。

[LG]《Mixture of Parrots: Experts improve memorization more than reasoning》S Jelassi, C Mohri, D Brandfonbrener, A Gu... [Harvard University] (2024)网页链接「机器学习」「人工智能」「论文」

2025蛇年奢华青蛇图腾设计 𐟐 青蛇身披金线，宛如翡翠玉雕，奢华至极！ 𐟐 关键词："Snake Refrigerator Magnet", c4d, 3d style, a green and gold snake side profile, its skin is a mixture of green and gold. The image is filled with intricate patterns and outlines of gold threads, all in red and gold. The snake's eyes are bright and sharp. The images are rich in detail and high resolution, exuding elegance and classic beauty. white background --ar 3:4 --v 6.1

[LG]《The Perfect Blend: Redefining RLHF with Mixture of Judges》T Xu, E Helenowski, K A Sankararaman, D Jin… [Meta GenAI] (2024)网页链接「机器学习」「人工智能」「论文」

高斯混合模型：理解复杂数据的强大工具 𐟌𑊩똦–醴𗥐ˆ模型（Gaussian Mixture Model, GMM）是一种非常强大的统计方法，特别适合处理那些具有多个子群体的数据集。想象一下，你在一个公园里观察猫和狗的行为。每种动物都有自己的活动区域和行为模式，但这些区域可能会重叠。高斯混合模型就像是一个数学工具，能帮助我们理解和预测这些动物的分布，比如哪些区域更可能是猫的领地，哪些更可能是狗的领地。在这个模型中，每个子群体（比如猫和狗）都被建模为一个高斯分布，也就是我们常说的钟形曲线。每个分布由三个主要参数定义：均值（mean，𜉯𜌦述了该子群体的中心位置；协方差（covariance，𜉯𜌦述了数据点的分布范围和形状；以及混合权重（mixing weight，𜉯𜌥†𓥮š了各个子群体在整个数据集中所占的比例。通过这些参数，GMM 不仅能告诉我们猫和狗可能的活动范围，还能估算任一给定区域是由哪种动物占主导的概率。这使得高斯混合模型成为处理混合数据、进行聚类和概率密度估计等问题的理想选择。

It seldom happens that any felicity comes pure as not to be tempered and allayed by some mixture of sorrow.几乎没有任何一种幸福是纯粹的，总是多少掺杂着一些悲哀。「世纪佳恋」

混料设计实验，咋选？各位大佬好，我最近在做一个实验，涉及到混料设计。我用的是Design Expert 13软件，但我对这个软件里的混料设计部分有点搞不清楚。具体来说，我在“mixture”选项下看到了三个选项： simplex lattice：单形格子实验 screening：筛选实验 optimal（custom）：自定义的混料设计根据我查到的资料，“simplex lattice”好像是单形格子实验，“screening”是筛选实验，但我对这两者的区别还是不太明白。而“optimal（custom）”则似乎是混料设计，因为我在文献里看到有人用“D-optimal mixture design”方法，所以我猜测我应该选择这个选项。我的实验目的是为了设计一个基质配比，在四个物质范围内进行实验并评分。然而，我无法确定这三者之间的具体区别、优缺点以及应用方法。希望有经验的大佬们能帮我解答一下，让我知道如何选择最适合我的实验设计方法。谢谢大家！𐟙

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