2021年5月13日 · To make the representations of positively-related users and items similar to each other while avoiding a collapsed solution, BUIR adopts two distinct encoder networks that learn from each other; the first encoder is trained to predict the output of the second encoder as its target, while the second encoder provides the consistent targets by ...

Gar taldin ni jaonyc; gar sa buir, ori'wadaas'la. - "Nobody cares who your father was, only the father you'll be." (Lit: Bloodline is not important, but you as a father are the most valuable thing.) Mando saying emphasising the importance of a father's role, and that a man is judged more by that than his lineage. Gedet'ye - please

Based on the neighborhood information of users and items, BUIR randomly generates the augmented views of each positive inter-action each time it encodes, then further trains the model by this self-supervision. Our extensive experiments demonstrate that BUIR consistently and significantly outperforms all baseline methods by

Buir Lake (Mongolian: Буйр нуур, romanized: Buyır nağur; Chinese: 贝尔湖; pinyin: Bèi'ěr Hú) is a freshwater lake that straddles the border between Mongolia and China. It lies within the Buir Lake Depression .

2024年1月28日 · buir的核心思想是以目标编码器的输入作为目标，对在线编码器进行训练，同时逐步改进目标编码器。buir与现有的端到端学习框架的主要区别在于，在线编码器和目标编码器以不同的方式进行更新。

本文提出了一种名为buir的新型occf框架，在没有负采样的情况下有效缓解了数据稀疏性问题，并利用随机数据增强来进一步提高模型性能。 实验结果表明，BUIR相比于已有的基线方法显著提高了推荐性能。

Our BUIR framework optimizes the representations of positively-related users and items (i.e., users and their highly preferred items) similar to each other, without explicitly using negative user-item interactions.

Explore, discover, and share academic work by Bilkent University faculty, students, and researchers.

本文的buir提出了一种不需要负样本, 不仅让正样本之间的相关性更强, 也能防止模型塌陷. BUIR有两个encoder, 第一个online encoder用来预测第二个encoder的输出, 第二个target encoder通过慢慢近似第一个encoder提供一个稳定的目标.BUIR通过直接最小化item和user的交叉预测误差 ...

Kal Skirata, born Falin Mattran—sometimes called Kal'buir (Mando'a for "Papa Kal") by the clone commandos that he trained—was a Human male Mandalorian instructor who trained clone commandos in the Grand Army of the Republic during the time of the Separatist Crisis.