Song Bian

According to our database, Song Bian authored at least 18 papers between 2018 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Scaling Laws Meet Model Architecture: Toward Inference-Efficient LLMs.

Song Bian, Tao Yu, Shivaram Venkataraman, Youngsuk Park

CoRR, October, 2025

What Limits Agentic Systems Efficiency?

Song Bian, Minghao Yan, Anand Jayarajan, Gennady Pekhimenko, Shivaram Venkataraman

CoRR, October, 2025

Tesserae: Scalable Placement Policies for Deep Learning Workloads.

Song Bian, Saurabh Agarwal, Md. Tareq Mahmood, Shivaram Venkataraman

CoRR, August, 2025

Scaling Inference-Efficient Language Models.

Song Bian, Minghao Yan, Shivaram Venkataraman

CoRR, January, 2025

Diamond: Harnessing GPU Resources for Scientific Deep Learning.

Haotian Xie, Rohan Marwaha, Minu Mathew, Song Bian, Gengcong Yang, Minghao Yan, Yadu Babuji, Owen Price, Yinzhi Wang, Volodymyr V. Kindratenko, Shivaram Venkataraman, Kyle Chard, Ian T. Foster, Zhao Zhang

Proceedings of the IEEE International Conference on eScience, 2025

2024

Computing in the Era of Large Generative Models: From Cloud-Native to AI-Native.

Yao Lu, Song Bian, Lequn Chen, Yongjun He, Yulong Hui, Matthew Lentz, Beibin Li, Fei Liu, Jialin Li, Qi Liu, Rui Liu, Xiaoxuan Liu, Lin Ma, Kexin Rong, Jianguo Wang, Yingjun Wu, Yongji Wu, Huanchen Zhang, Minjia Zhang, Qizhen Zhang, Tianyi Zhou, Danyang Zhuo

CoRR, 2024

Does Compressing Activations Help Model Parallel Training?

Song Bian, Dacheng Li, Hongyi Wang, Eric P. Xing, Shivaram Venkataraman

Proceedings of the Seventh Annual Conference on Machine Learning and Systems, 2024

Naive Bayes Classifiers over Missing Data: Decision and Poisoning.

Song Bian, Xiating Ouyang, Zhiwei Fan, Paraschos Koutris

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Federated Empirical Risk Minimization via Second-Order Method.

Song Bian, Zhao Song, Junze Yin

CoRR, 2023

Certifiable Robustness for Naive Bayes Classifiers.

Song Bian, Xiating Ouyang, Zhiwei Fan, Paraschos Koutris

CoRR, 2023

2022

CrowdTC: Crowd-powered Learning for Text Classification.

Keyu Yang, Yunjun Gao, Lei Liang, Song Bian, Lu Chen, Baihua Zheng

ACM Trans. Knowl. Discov. Data, 2022

Finding Top-r Influential Communities under Aggregation Functions.

You Peng, Song Bian, Rui Li, Sibo Wang, Jeffrey Xu Yu

Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

2021

DataPrep.EDA: Task-Centric Exploratory Data Analysis for Statistical Modeling in Python.

Jinglin Peng, Weiyuan Wu, Brandon Lockhart, Song Bian, Jing Nathan Yan, Linghao Xu, Zhixuan Chi, Jeffrey M. Rzeszotarski, Jiannan Wang

Proceedings of the SIGMOD '21: International Conference on Management of Data, 2021

2020

Efficient Algorithms for Budgeted Influence Maximization on Massive Social Networks.

Song Bian, Qintian Guo, Sibo Wang, Jeffrey Xu Yu

Proc. VLDB Endow., 2020

CrowdTSC: Crowd-based Neural Networks for Text Sentiment Classification.

Keyu Yang, Yunjun Gao, Lei Liang, Song Bian, Lu Chen, Baihua Zheng

CoRR, 2020

2019

Are Powerful Graph Neural Nets Necessary? A Dissection on Graph Classification.

Ting Chen, Song Bian, Yizhou Sun

CoRR, 2019

SimGNN: A Neural Network Approach to Fast Graph Similarity Computation.

Yunsheng Bai, Hao Ding, Song Bian, Ting Chen, Yizhou Sun, Wei Wang

Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining, 2019

2018

Graph Edit Distance Computation via Graph Neural Networks.

Yunsheng Bai, Hao Ding, Song Bian, Ting Chen, Yizhou Sun, Wei Wang

CoRR, 2018