Algorithms - Microsoft Research

Publication

Combinatorial Pure Exploration for Dueling Bandits

Wei Chen, Yihan Du, Longbo Huang, Haoyu Zhao

Proceedings of the 37th International Conference on Machine Learning (ICML) | July 2020

Publication

Network Slicing in Heterogeneous Software-defined RANs

Qiaofeng Qin, Nakjung Choi, Muntasir Raihan Rahman, Marina Thottan, Leandros Tassiulas

IEEE INFOCOM 2020 – IEEE Conference on Computer Communications | July 2020

Publication

(Locally) Differentially Private Combinatorial Semi-Bandits

Xiaoyu Chen, Kai Zheng, Zixin Zhou, Yunchang Yang, Wei Chen, Liwei Wang

Proceedings of the 37th International Conference on Machine Learning (ICML) | July 2020

Publication

Follow the Perturbed Approximate Leader for Solving Semi-bandit Combinatorial Optimization

Feidiao Yang, Wei Chen, Jialin Zhang, Xiaoming Sun

Frontiers in Computer Science | July 2020

Publication

Differentially Private Set Union

Sivakanth Gopi, Pankaj Gulhane, Janardhan (Jana) Kulkarni, Judy Hanwen Shen, Milad Shokouhi, Sergey Yekhanin

International Conference on Machine Learning 2020 | July 2020

Contributed talk at TPDP 2020. Also appeared in the Journal of Privacy and Confidentiality (JPC).

Github Project

Publication

Applying Machine Learning to End-to-end Slice SLA Decomposition

Michael Iannelli, Muntasir Raihan Rahman, Nakjung Choi, Le Wang

2020 6th IEEE Conference on Network Softwarization (NetSoft) | July 2020

Publication

Optimization from Structured Samples for Coverage Functions

Wei Chen, Xiaoming Sun, Jialin Zhang, Zhijie Zhang

Proceedings of the 37th International Conference on Machine Learning, (ICML) | July 2020

Publication

On Dynamic Network Models and Application to Causal Impact

Yu-chia Chen , Avleen S. Bijral, Juan M. Lavista Ferres

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining | July 2020

Microsoft Research Blog

Newly discovered principle reveals how adversarial training can perform robust deep learning

June 30, 2020 | Zeyuan Allen-Zhu, Yuanzhi Li

In machine learning, adversarial examples usually refer to natural inputs plus small, specially crafted perturbations that can fool the model into making mistakes. In recent years, adversarial examples have been repeatedly discovered in deep learning…

Project

DNS Exfiltration Detection

Develop characteristic features of malicious DNS queries and Build anomaly detection models