Tue 10 Nov 2020 01:13 - 01:30 at Virtual room 1 - ML In Practice
Tue 10 Nov Times are displayed in time zone: (UTC) Coordinated Universal Time change
Tue 10 Nov
Times are displayed in time zone: (UTC) Coordinated Universal Time change
01:00 - 01:30: ML In PracticePaper Presentations / Industry Papers / Research Papers at Virtual room 1 | |||
| 01:00 - 01:02 Talk | A Comprehensive Study on Challenges in Deploying Deep Learning Based Software Research Papers Zhenpeng ChenPeking University, China, Yanbin CaoPeking University, China, Yuanqiang LiuPeking University, China, Haoyu WangBeijing University of Posts and Telecommunications, Tao XiePeking University, Xuanzhe LiuPeking University, China DOI Pre-print | ||
| 01:03 - 01:04 Talk | A First Look at the Integration of Machine Learning Models in Complex Autonomous Driving Systems: A Case Study on Apollo Industry Papers pengzi Concordia University, Canada, Jinqiu YangConcordia University, Montreal, Canada, Tse-Hsun (Peter) ChenConcordia University, Lei MaKyushu University DOI | ||
| 01:05 - 01:06 Talk | Enhancing the Interoperability between Deep Learning Frameworks by Model Conversion Industry Papers Yu David LiuSUNY Binghamton, USA, Cheng ChenByteDance, China, Ru ZhangMicrosoft Research, Tingting QinMicrosoft Research, China, Xiang JiMicrosoft Research, China, Haoxiang LinMicrosoft Research, Mao YangMicrosoft Research DOI | ||
| 01:07 - 01:08 Talk | Estimating GPU Memory Consumption of Deep Learning Models Industry Papers Yanjie GaoMicrosoft Research, China, Yu David LiuSUNY Binghamton, USA, Hongyu ZhangUniversity of Newcastle, Australia, lizhengxian Microsoft Research, China, Yonghao ZhuMicrosoft Research, China, Haoxiang LinMicrosoft Research, Mao YangMicrosoft Research DOI | ||
| 01:09 - 01:10 Talk | IntelliCode Compose: Code Generation using Transformer Industry Papers Alexey SvyatkovskiyMicrosoft, Shao Kun DengMicrosoft Corporation, Shengyu FuMicrosoft, USA, Neel SundaresanMicrosoft Corporation DOI Pre-print | ||
| 01:11 - 01:12 Talk | Reducing DNN Labelling Cost using Surprise Adequacy: An Industrial Case Study for Autonomous Driving Industry Papers Jinhan KimKAIST, Jeongil JuHyundai Motor Group, South Korea, Robert FeldtChalmers University of Technology, Sweden, Shin YooKorea Advanced Institute of Science and Technology DOI Pre-print | ||
| 01:13 - 01:30 | Conversations on ML In Practice Research Papers Sidong FengAustralian National University, Australia, Tse-Hsun (Peter) ChenConcordia University, Yanbin CaoPeking University, China, Yanjie GaoMicrosoft Research, China, Zhenpeng ChenPeking University, China, M: Joshua GarciaUniversity of California, Irvine | ||