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Oral
Tue 13:00 Matchmaker: Data Drift Mitigation in Machine Learning for Large-Scale Systems
Ankur Mallick · Kevin Hsieh · Behnaz Arzani · Gauri Joshi
Oral
Tue 14:33 Towards the Co-design of Neural Networks and Accelerators
Yanqi Zhou · Xuanyi Dong · Tianjian Meng · Mingxing Tan · Berkin Akin · Daiyi Peng · Amir Yazdanbakhsh · Da Huang · Ravi Narayanaswami · James Laudon
Oral
Wed 15:27 Bolt: Bridging the Gap between Auto-tuners and Hardware-native Performance
Jiarong Xing · Leyuan Wang · Shang Zhang · Jack Chen · Ang Chen · Yibo Zhu
Oral
Mon 9:21 Random Offset Block Embedding (ROBE) for compressed embedding tables in deep learning recommendation systems
Aditya Desai · Li Chou · Anshumali Shrivastava
Oral
Tue 13:36 SLA-Driven ML INFERENCE FRAMEWORK FOR CLOUDS WITH HETEROGENEOUS ACCELERATORS
Junguk Cho · Diman Zad Tootaghaj · Lianjie Cao · Puneet Sharma
Round Table Discussion
Tue 11:30 Round Table Discussion
Panel
Mon 11:30 The Future of MLSys: Industry and Academia - panel
Shivaram Venkataraman · Salman Avestimehr · Beidi Chen · Azalia Mirhoseini
Oral
Mon 14:33 Apollo: Automatic Partition-based Operator Fusion through Layer by Layer Optimization
Jie Zhao · Xiong Gao · Ruijie Xia · Zhaochuang Zhang · Deshi Chen · Lei Chen · Renwei Zhang · Zhen Geng · Bin Cheng · Xuefeng Jin
Tutorial
Mon 13:00 Gemmini: Enabling Systematic Deep-Learning Architecture Evaluation via Full-Stack Integration
Hasan Genc
Tutorial
Mon 13:00 Time Series Anomaly Detection : Tools, Techniques & Tricks
Patel Dhaval
Oral Session
Mon 8:45 Outstanding Papers
Oral
Mon 13:36 PAPAYA: Practical, Private, and Scalable Federated Learning
Dzmitry Huba · John Nguyen · Kshitiz Malik · Ruiyu Zhu · Mike Rabbat · Ashkan Yousefpour · Carole-Jean Wu · Hongyuan Zhan · Pavel Ustinov · Harish Srinivas · Kaikai Wang · Anthony Shoumikhin · Jesik Min · Mani Malek