Hongzi Mao

Publication Activity (10 Years)

Years Active: 2014-2022
Publications (10 Years): 26

Top Topics

Cardinality Estimation

Reinforcement Learning

Query Optimizers

Top Venues

Proc. VLDB Endow.

Publications

Ryan Marcus, Parimarjan Negi, Hongzi Mao, Nesime Tatbul, Mohammad Alizadeh, Tim Kraska
Bao: Making Learned Query Optimization Practical. SIGMOD Rec. 51 (1) (2022)
Parimarjan Negi, Ryan C. Marcus, Andreas Kipf, Hongzi Mao, Nesime Tatbul, Tim Kraska, Mohammad Alizadeh
Flow-Loss: Learning Cardinality Estimates That Matter. Proc. VLDB Endow. 14 (11) (2021)
Ryan Marcus, Parimarjan Negi, Hongzi Mao, Nesime Tatbul, Mohammad Alizadeh, Tim Kraska
Bao: Making Learned Query Optimization Practical. SIGMOD Conference (2021)
Parimarjan Negi, Ryan Marcus, Andreas Kipf, Hongzi Mao, Nesime Tatbul, Tim Kraska, Mohammad Alizadeh
Flow-Loss: Learning Cardinality Estimates That Matter. CoRR (2021)
Hongzi Mao, Chenjie Gu, Miaosen Wang, Angie Chen, Nevena Lazic, Nir Levine, Derek Pang, Rene Claus, Marisabel Hechtman, Ching-Han Chiang, Cheng Chen, Jingning Han
Neural Rate Control for Video Encoding using Imitation Learning. CoRR (2020)
Parimarjan Negi, Ryan Marcus, Hongzi Mao, Nesime Tatbul, Tim Kraska, Mohammad Alizadeh
Cost-Guided Cardinality Estimation: Focus Where it Matters. ICDE Workshops (2020)
Qing Feng, Benjamin Letham, Hongzi Mao, Eytan Bakshy
High-Dimensional Contextual Policy Search with Unknown Context Rewards using Bayesian Optimization. NeurIPS (2020)
Zili Meng, Minhu Wang, Jiasong Bai, Mingwei Xu, Hongzi Mao, Hongxin Hu
Interpreting Deep Learning-Based Networking Systems. SIGCOMM (2020)
Lujing Cen, Ryan Marcus, Hongzi Mao, Justin Gottschlich, Mohammad Alizadeh, Tim Kraska
Learned Garbage Collection. CoRR (2020)
Lujing Cen, Ryan Marcus, Hongzi Mao, Justin Gottschlich, Mohammad Alizadeh, Tim Kraska
Learned garbage collection. MAPL@PLDI (2020)
Ryan Marcus, Parimarjan Negi, Hongzi Mao, Nesime Tatbul, Mohammad Alizadeh, Tim Kraska
Bao: Learning to Steer Query Optimizers. CoRR (2020)
Hongzi Mao, Shannon Chen, Drew Dimmery, Shaun Singh, Drew Blaisdell, Yuandong Tian, Mohammad Alizadeh, Eytan Bakshy
Real-world Video Adaptation with Reinforcement Learning. CoRR (2020)
Ryan C. Marcus, Parimarjan Negi, Hongzi Mao, Chi Zhang, Mohammad Alizadeh, Tim Kraska, Olga Papaemmanouil, Nesime Tatbul
Neo: A Learned Query Optimizer. Proc. VLDB Endow. 12 (11) (2019)
Tim Kraska, Mohammad Alizadeh, Alex Beutel, Ed H. Chi, Ani Kristo, Guillaume Leclerc, Samuel Madden, Hongzi Mao, Vikram Nathan
SageDB: A Learned Database System. CIDR (2019)
Ravichandra Addanki, Shaileshh Bojja Venkatakrishnan, Shreyan Gupta, Hongzi Mao, Mohammad Alizadeh
Learning Generalizable Device Placement Algorithms for Distributed Machine Learning. NeurIPS (2019)
Ryan Marcus, Parimarjan Negi, Hongzi Mao, Chi Zhang, Mohammad Alizadeh, Tim Kraska, Olga Papaemmanouil, Nesime Tatbul
Neo: A Learned Query Optimizer. CoRR (2019)
Hongzi Mao, Parimarjan Negi, Akshay Narayan, Hanrui Wang, Jiacheng Yang, Haonan Wang, Ryan Marcus, Ravichandra Addanki, Mehrdad Khani Shirkoohi, Songtao He, Vikram Nathan, Frank Cangialosi, Shaileshh Bojja Venkatakrishnan, Wei-Hung Weng, Song Han, Tim Kraska, Mohammad Alizadeh
Park: An Open Platform for Learning-Augmented Computer Systems. NeurIPS (2019)
Zili Meng, Minhu Wang, Mingwei Xu, Hongzi Mao, Jiasong Bai, Hongxin Hu
Explaining Deep Learning-Based Networked Systems. CoRR (2019)
Hongzi Mao, Shaileshh Bojja Venkatakrishnan, Malte Schwarzkopf, Mohammad Alizadeh
Variance Reduction for Reinforcement Learning in Input-Driven Environments. ICLR (Poster) (2019)
Hongzi Mao, Malte Schwarzkopf, Shaileshh Bojja Venkatakrishnan, Zili Meng, Mohammad Alizadeh
Learning scheduling algorithms for data processing clusters. SIGCOMM (2019)
Ravichandra Addanki, Shaileshh Bojja Venkatakrishnan, Shreyan Gupta, Hongzi Mao, Mohammad Alizadeh
Placeto: Learning Generalizable Device Placement Algorithms for Distributed Machine Learning. CoRR (2019)
Hongzi Mao, Shaileshh Bojja Venkatakrishnan, Malte Schwarzkopf, Mohammad Alizadeh
Variance Reduction for Reinforcement Learning in Input-Driven Environments. CoRR (2018)
Hongzi Mao, Malte Schwarzkopf, Shaileshh Bojja Venkatakrishnan, Zili Meng, Mohammad Alizadeh
Learning Scheduling Algorithms for Data Processing Clusters. CoRR (2018)
Hongzi Mao, Ravi Netravali, Mohammad Alizadeh
Neural Adaptive Video Streaming with Pensieve. SIGCOMM (2017)
Hongzi Mao, Mohammad Alizadeh, Ishai Menache, Srikanth Kandula
Resource Management with Deep Reinforcement Learning. HotNets (2016)
Kanthi Nagaraj, Dinesh Bharadia, Hongzi Mao, Sandeep Chinchali, Mohammad Alizadeh, Sachin Katti
NUMFabric: Fast and Flexible Bandwidth Allocation in Datacenters. SIGCOMM (2016)
Fadel Adib, Chen-Yu Hsu, Hongzi Mao, Dina Katabi, Frédo Durand
Capturing the human figure through a wall. ACM Trans. Graph. 34 (6) (2015)
Fadel Adib, Hongzi Mao, Zachary Kabelac, Dina Katabi, Robert C. Miller
Smart Homes that Monitor Breathing and Heart Rate. CHI (2015)
Fadel Adib, Zachary Kabelac, Hongzi Mao, Dina Katabi, Robert C. Miller
Demo: real-time breath monitoring using wireless signals. MobiCom (2014)