Search Results for author: Andreas Pfadler

Found 9 papers, 3 papers with code

Baihe: SysML Framework for AI-driven Databases

no code implementations29 Dec 2021 Andreas Pfadler, Rong Zhu, Wei Chen, Botong Huang, Tianjing Zeng, Bolin Ding, Jingren Zhou

Based on the high level architecture, we then describe a concrete implementation of Baihe for PostgreSQL and present example use cases for learned query optimizers.

Glue: Adaptively Merging Single Table Cardinality to Estimate Join Query Size

no code implementations7 Dec 2021 Rong Zhu, Tianjing Zeng, Andreas Pfadler, Wei Chen, Bolin Ding, Jingren Zhou

Cardinality estimation (CardEst), a central component of the query optimizer, plays a significant role in generating high-quality query plans in DBMS.

Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation

1 code implementation13 Sep 2021 Yuxing Han, Ziniu Wu, Peizhi Wu, Rong Zhu, Jingyi Yang, Liang Wei Tan, Kai Zeng, Gao Cong, Yanzhao Qin, Andreas Pfadler, Zhengping Qian, Jingren Zhou, Jiangneng Li, Bin Cui

Therefore, we propose a new metric P-Error to evaluate the performance of CardEst methods, which overcomes the limitation of Q-Error and is able to reflect the overall end-to-end performance of CardEst methods.

QoS Prediction for 5G Connected and Automated Driving

no code implementations11 Jul 2021 Apostolos Kousaridas, Ramya Panthangi Manjunath, Jose Mauricio Perdomo, Chan Zhou, Ernst Zielinski, Steffen Schmitz, Andreas Pfadler

5G communication system can support the demanding quality-of-service (QoS) requirements of many advanced vehicle-to-everything (V2X) use cases.

Efficient and Scalable Structure Learning for Bayesian Networks: Algorithms and Applications

no code implementations7 Dec 2020 Rong Zhu, Andreas Pfadler, Ziniu Wu, Yuxing Han, Xiaoke Yang, Feng Ye, Zhenping Qian, Jingren Zhou, Bin Cui

To resolve this, we propose a new structure learning algorithm LEAST, which comprehensively fulfills our business requirements as it attains high accuracy, efficiency and scalability at the same time.

Anomaly Detection

FSPN: A New Class of Probabilistic Graphical Model

no code implementations18 Nov 2020 Ziniu Wu, Rong Zhu, Andreas Pfadler, Yuxing Han, Jiangneng Li, Zhengping Qian, Kai Zeng, Jingren Zhou

We introduce factorize sum split product networks (FSPNs), a new class of probabilistic graphical models (PGMs).

FLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation

1 code implementation18 Nov 2020 Rong Zhu, Ziniu Wu, Yuxing Han, Kai Zeng, Andreas Pfadler, Zhengping Qian, Jingren Zhou, Bin Cui

Despite decades of research, existing methods either over simplify the models only using independent factorization which leads to inaccurate estimates, or over complicate them by lossless conditional factorization without any independent assumption which results in slow probability computation.

Learning Efficient Parameter Server Synchronization Policies for Distributed SGD

no code implementations ICLR 2020 Rong Zhu, Sheng Yang, Andreas Pfadler, Zhengping Qian, Jingren Zhou

We apply a reinforcement learning (RL) based approach to learning optimal synchronization policies used for Parameter Server-based distributed training of machine learning models with Stochastic Gradient Descent (SGD).

Q-Learning

POG: Personalized Outfit Generation for Fashion Recommendation at Alibaba iFashion

1 code implementation6 May 2019 Wen Chen, Pipei Huang, Jiaming Xu, Xin Guo, Cheng Guo, Fei Sun, Chao Li, Andreas Pfadler, Huan Zhao, Binqiang Zhao

In particular, there exist two requirements for fashion outfit recommendation: the Compatibility of the generated fashion outfits, and the Personalization in the recommendation process.

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