Accepted Papers
A Weak Supervision Approach to Detecting Visual Anomalies for Automated Testing of Graphics Units. Adi Szeskin, Lev Faivishevsky, Ashwin K. Muppalla, Amitai Armon, and Tom Hope.
CodeCaption: A dataset for captioning data science code. Ioana Baldini, Kavitha Srinivas, and Jiri Navratil.
Defeating the Curse of Dimensionality to Scale JIT Fusion. Jonathan Raiman.
Learning Multi-dimensional Indexing. Vikram Nathan*, Jialin Ding*, Mohammad Alizadeh, and Tim Kraska.
Learned TPU Cost Model for XLA Tensor Programs. Samuel J. Kaufman, Phitchaya Phothilimtha, and Mike Burrows.
Learning Caching Policies with Subsampling. Haonan Wang, Hao He, Mohammad Alizadeh, and Hongzi Mao.
Learning to Fuse. Amirali Abdolrashidi, Qiumin Xu, Shibo Wang, Sudip Roy, and Yanqi Zhou.
SOSD: A Benchmark for Learned Indexes. Andreas Kipf*, Ryan Marcus*, Alexander van Renen*, Mihail Stoian, Alfons Kemper, Tim Kraska, and Thomas Neumann.
Learning to Vectorize Using Deep Reinforcement Learning. Ameer Haj-Ali, Nesreen Ahmed, Theodore L. Willke, Yakun Sophia Shao, Krste Asanovic, and Ion Stoica.
MVFST-RL: An Asynchronous RL Framework for Congestion Control with Delayed Actions. Viswanath Sivakumar, Tim Rocktäschel, Alexander Miller, Heinrich Küttler, Nantas Nardelli, Mike Rabbat, Joelle Pineau, and Sebastian Riedel.
Multi-Task Learning for Storage Systems. Giulio Zhou, and Martin Maas.
Neural Hierarchical Sequence Model for Irregular Data Prefetching. Zhan Shi, Akanksha Jain, Kevin Swersky, Milad Hashemi, Parthasarathy Ranganathan, and Calvin Lin.
Neural-Hardware Architecture Search. Yujun Lin, Driss Hafdi, Kuan Wang, Zhijian Liu, and Song Han.
PRIC: A Privacy-Respecting Image Crowdsourcing Framework for Deep Learning with Anonymized Intermediate Representations. Ang Li, Yixiao Duan, Huanrui Yang, Yiran Chen, and Jianlei Yang.
Predictive Precompute with Recurrent Neural Networks. Hanson Wang, Zehui Wang, and Yuanyuan Ma.
QoS-aware Neural Architecture Search. An-Chieh Cheng, Chieh Hubert Lin, Da-Cheng Juan, Wei Wei, and Min Sun.
Real-time Policy Distillation in Deep Reinforcement Learning. Yuxiang Sun, and Pooyan Fazli.
Reinforcement Learning guided Software Debloating. Nham V Le, Ashish Gehani, Arie Gurfinkel, Susmit Jha, and Jorge A. Navas
Reinforcement learning for bandwidth estimation and congestion control in real-time communications. Joyce Fang, Martin Ellis, Bin Li, Siyao Liu, Yasaman Hosseinkashi, Michael Revow, Albert Sadovnikov, Ziyuan Liu, Peng Cheng, Sachin Ashok, David Zhao, Ross Cutler, Yan Lu, and Johannes Gehrke.
Towards Safe Online Reinforcement Learning in Computer Systems. Hongzi Mao, Malte Schwarzkopf, Hao He, and Mohammad Alizadeh.
TreeCaps: Tree-Structured Capsule Networks for Program Source Code Processing. Vinoj Jayasundara, Nghi Bui, Lingxiao Jiang, and David Lo.
Zero-Shot Learning for Fast Optimization of Computation Graphs. Aditya Paliwal, Felix Gimeno, Vinod Nair, Yujia Li, Miles Lubin, Pushmeet Kohli, and Oriol Vinyals.