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pro vyhledávání: '"Jiang, Biye"'
Autor:
Zhang, Zhao-Yu, Sheng, Xiang-Rong, Zhang, Yujing, Jiang, Biye, Han, Shuguang, Deng, Hongbo, Zheng, Bo
Deep learning techniques have been applied widely in industrial recommendation systems. However, far less attention has been paid to the overfitting problem of models in recommendation systems, which, on the contrary, is recognized as a critical issu
Externí odkaz:
http://arxiv.org/abs/2209.06053
Autor:
Li, Jin, Liu, Jie, Li, Shangzhou, Xu, Yao, Cao, Ran, Li, Qi, Jiang, Biye, Wang, Guan, Zhu, Han, Gai, Kun, Zhu, Xiaoqiang
Matching module plays a critical role in display advertising systems. Without query from user, it is challenging for system to match user traffic and ads suitably. System packs up a group of users with common properties such as the same gender or sim
Externí odkaz:
http://arxiv.org/abs/2102.09283
Multi-stage cascade architecture exists widely in many industrial systems such as recommender systems and online advertising, which often consists of sequential modules including matching, pre-ranking, ranking, etc. For a long time, it is believed pr
Externí odkaz:
http://arxiv.org/abs/2007.16122
Autor:
Jiang, Biye, Zhang, Pengye, Chen, Rihan, Dai, Binding, Luo, Xinchen, Yang, Yin, Wang, Guan, Zhou, Guorui, Zhu, Xiaoqiang, Gai, Kun
Modern large-scale systems such as recommender system and online advertising system are built upon computation-intensive infrastructure. The typical objective in these applications is to maximize the total revenue, e.g. GMV~(Gross Merchandise Volume)
Externí odkaz:
http://arxiv.org/abs/2006.09684
The internal states of most deep neural networks are difficult to interpret, which makes diagnosis and debugging during training challenging. Activation maximization methods are widely used, but lead to multiple optima and are hard to interpret (appe
Externí odkaz:
http://arxiv.org/abs/1812.04604
Gibbs sampling is a workhorse for Bayesian inference but has several limitations when used for parameter estimation, and is often much slower than non-sampling inference methods. SAME (State Augmentation for Marginal Estimation) \cite{Doucet99,Doucet
Externí odkaz:
http://arxiv.org/abs/1409.5402
Autor:
Jiang, Biye
Publikováno v:
Jiang, Biye. (2018). Exploratory model analysis for machine learning. UC Berkeley: Computer Science. Retrieved from: http://www.escholarship.org/uc/item/6301t4xq
Machine learning is growing in importance in many different fields. However, it is still very hard for users to tune hyper-parameters when optimizing their models, or perform a comprehensive and interpretable diagnosis for complex models like deep ne
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______325::8e6cea602db45bd648dc38068443b550
http://www.escholarship.org/uc/item/6301t4xq
http://www.escholarship.org/uc/item/6301t4xq
Publikováno v:
Computer Graphics Forum. Dec2013, Vol. 32 Issue 3pt4, p421-430. 10p. 10 Color Photographs, 1 Chart.