Hongzi Mao

According to our database, Hongzi Mao authored at least 23 papers between 2014 and 2022.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2022

Bao: Making Learned Query Optimization Practical.

Ryan Marcus, Parimarjan Negi, Hongzi Mao, Nesime Tatbul, Mohammad Alizadeh, Tim Kraska

SIGMOD Rec., 2022

2021

Flow-Loss: Learning Cardinality Estimates That Matter.

Parimarjan Negi, Ryan Marcus, Andreas Kipf, Hongzi Mao, Nesime Tatbul, Tim Kraska, Mohammad Alizadeh

Proc. VLDB Endow., 2021

2020

Neural Rate Control for Video Encoding using Imitation Learning.

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

CoRR, 2020

Real-world Video Adaptation with Reinforcement Learning.

Hongzi Mao, Shannon Chen, Drew Dimmery, Shaun Singh, Drew Blaisdell, Yuandong Tian, Mohammad Alizadeh, Eytan Bakshy

CoRR, 2020

Bao: Learning to Steer Query Optimizers.

Ryan Marcus, Parimarjan Negi, Hongzi Mao, Nesime Tatbul, Mohammad Alizadeh, Tim Kraska

CoRR, 2020

Interpreting Deep Learning-Based Networking Systems.

Zili Meng, Minhu Wang, Jiasong Bai, Mingwei Xu, Hongzi Mao, Hongxin Hu

Proceedings of the SIGCOMM '20: Proceedings of the 2020 Annual conference of the ACM Special Interest Group on Data Communication on the applications, 2020

Learned garbage collection.

Lujing Cen, Ryan Marcus, Hongzi Mao, Justin Gottschlich, Mohammad Alizadeh, Tim Kraska

Proceedings of the 4th ACM SIGPLAN International Workshop on Machine Learning and Programming Languages, 2020

High-Dimensional Contextual Policy Search with Unknown Context Rewards using Bayesian Optimization.

Qing Feng, Benjamin Letham, Hongzi Mao, Eytan Bakshy

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Cost-Guided Cardinality Estimation: Focus Where it Matters.

Parimarjan Negi, Ryan Marcus, Hongzi Mao, Nesime Tatbul, Tim Kraska, Mohammad Alizadeh

Proceedings of the 36th IEEE International Conference on Data Engineering Workshops, 2020

2019

Neo: A Learned Query Optimizer.

Ryan Marcus, Parimarjan Negi, Hongzi Mao, Chi Zhang, Mohammad Alizadeh, Tim Kraska, Olga Papaemmanouil, Nesime Tatbul

Proc. VLDB Endow., 2019

Explaining Deep Learning-Based Networked Systems.

Zili Meng, Minhu Wang, Mingwei Xu, Hongzi Mao, Jiasong Bai, Hongxin Hu

CoRR, 2019

Placeto: Learning Generalizable Device Placement Algorithms for Distributed Machine Learning.

Ravichandra Addanki, Shaileshh Bojja Venkatakrishnan, Shreyan Gupta, Hongzi Mao, Mohammad Alizadeh

CoRR, 2019

Learning scheduling algorithms for data processing clusters.

Hongzi Mao, Malte Schwarzkopf, Shaileshh Bojja Venkatakrishnan, Zili Meng, Mohammad Alizadeh

Proceedings of the ACM Special Interest Group on Data Communication, 2019

Park: An Open Platform for Learning-Augmented Computer Systems.

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

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Learning Generalizable Device Placement Algorithms for Distributed Machine Learning.

Ravichandra Addanki, Shaileshh Bojja Venkatakrishnan, Shreyan Gupta, Hongzi Mao, Mohammad Alizadeh

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Variance Reduction for Reinforcement Learning in Input-Driven Environments.

Hongzi Mao, Shaileshh Bojja Venkatakrishnan, Malte Schwarzkopf, Mohammad Alizadeh

Proceedings of the 7th International Conference on Learning Representations, 2019

SageDB: A Learned Database System.

Tim Kraska, Mohammad Alizadeh, Alex Beutel, Ed H. Chi, Ani Kristo, Guillaume Leclerc, Samuel Madden, Hongzi Mao, Vikram Nathan

Proceedings of the 9th Biennial Conference on Innovative Data Systems Research, 2019

2017

Neural Adaptive Video Streaming with Pensieve.

Hongzi Mao, Ravi Netravali, Mohammad Alizadeh

Proceedings of the Conference of the ACM Special Interest Group on Data Communication, 2017

2016

NUMFabric: Fast and Flexible Bandwidth Allocation in Datacenters.

Kanthi Nagaraj, Dinesh Bharadia, Hongzi Mao, Sandeep Chinchali, Mohammad Alizadeh, Sachin Katti

Proceedings of the ACM SIGCOMM 2016 Conference, Florianopolis, Brazil, August 22-26, 2016, 2016

Resource Management with Deep Reinforcement Learning.

Hongzi Mao, Mohammad Alizadeh, Ishai Menache, Srikanth Kandula

Proceedings of the 15th ACM Workshop on Hot Topics in Networks, 2016

2015

Capturing the human figure through a wall.

Fadel Adib, Chen-Yu Hsu, Hongzi Mao, Dina Katabi, Frédo Durand

ACM Trans. Graph., 2015

Smart Homes that Monitor Breathing and Heart Rate.

Fadel Adib, Hongzi Mao, Zachary Kabelac, Dina Katabi, Robert C. Miller

Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, 2015

2014

Demo: real-time breath monitoring using wireless signals.

Fadel Adib, Zachary Kabelac, Hongzi Mao, Dina Katabi, Robert C. Miller

Proceedings of the 20th Annual International Conference on Mobile Computing and Networking, 2014