Qinghao Hu

Orcid: 0000-0003-1034-7502

According to our database1, Qinghao Hu authored at least 46 papers between 2015 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
Deep Learning Workload Scheduling in GPU Datacenters: A Survey.
ACM Comput. Surv., June, 2024

InternEvo: Efficient Long-sequence Large Language Model Training via Hybrid Parallelism and Redundant Sharding.
CoRR, 2024

Characterization of Large Language Model Development in the Datacenter.
Proceedings of the 21st USENIX Symposium on Networked Systems Design and Implementation, 2024

MEGA: A Memory-Efficient GNN Accelerator Exploiting Degree-Aware Mixed-Precision Quantization.
Proceedings of the IEEE International Symposium on High-Performance Computer Architecture, 2024

2023
ECBC: Efficient Convolution via Blocked Columnizing.
IEEE Trans. Neural Networks Learn. Syst., 2023

ATF: An Alternating Training Framework for Weakly Supervised Face Alignment.
IEEE Trans. Multim., 2023

AMSP: Super-Scaling LLM Training via Advanced Model States Partitioning.
CoRR, 2023

Spiking NeRF: Making Bio-inspired Neural Networks See through the Real World.
CoRR, 2023

Boosting Distributed Full-graph GNN Training with Asynchronous One-bit Communication.
CoRR, 2023

A<sup>2</sup>Q: Aggregation-Aware Quantization for Graph Neural Networks.
CoRR, 2023

Accumulated Trivial Attention Matters in Vision Transformers on Small Datasets.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Hydro: Surrogate-Based Hyperparameter Tuning Service in Datacenters.
Proceedings of the 17th USENIX Symposium on Operating Systems Design and Implementation, 2023

MCUNeRF: Packing NeRF into an MCU with 1MB Memory.
Proceedings of the 31st ACM International Conference on Multimedia, 2023

$\rm A^2Q$: Aggregation-Aware Quantization for Graph Neural Networks.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Master-Slave Control Strategy Applied in Microsurgical Robot.
Proceedings of the International Conference on Advanced Robotics and Mechatronics, 2023

Lucid: A Non-intrusive, Scalable and Interpretable Scheduler for Deep Learning Training Jobs.
Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2023

2022
Adversarial Binary Mutual Learning for Semi-Supervised Deep Hashing.
IEEE Trans. Neural Networks Learn. Syst., 2022

DATE: Dual Assignment for End-to-End Fully Convolutional Object Detection.
CoRR, 2022

Deep Learning Workload Scheduling in GPU Datacenters: Taxonomy, Challenges and Vision.
CoRR, 2022

Primo: Practical Learning-Augmented Systems with Interpretable Models.
Proceedings of the 2022 USENIX Annual Technical Conference, 2022

PalQuant: Accelerating High-Precision Networks on Low-Precision Accelerators.
Proceedings of the Computer Vision - ECCV 2022, 2022

MixFormer: Mixing Features across Windows and Dimensions.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
Architecture Aware Latency Constrained Sparse Neural Networks.
CoRR, 2021

HIH: Towards More Accurate Face Alignment via Heatmap in Heatmap.
CoRR, 2021

Generative Zero-shot Network Quantization.
CoRR, 2021

Characterization and prediction of deep learning workloads in large-scale GPU datacenters.
Proceedings of the International Conference for High Performance Computing, 2021

Revisting Quantization Error in Face Alignment.
Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops, 2021

Generative Zero-Shot Network Quantization.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

2020
ATF: Towards Robust Face Alignment via Leveraging Similarity and Diversity across Different Datasets.
Proceedings of the MM '20: The 28th ACM International Conference on Multimedia, 2020

Soft Threshold Ternary Networks.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

ProxyBNN: Learning Binarized Neural Networks via Proxy Matrices.
Proceedings of the Computer Vision - ECCV 2020, 2020

2019
A System-Level Solution for Low-Power Object Detection.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision Workshops, 2019

AirFace: Lightweight and Efficient Model for Face Recognition.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision Workshops, 2019

2018
DeepSearch: A Fast Image Search Framework for Mobile Devices.
ACM Trans. Multim. Comput. Commun. Appl., 2018

Quantized CNN: A Unified Approach to Accelerate and Compress Convolutional Networks.
IEEE Trans. Neural Networks Learn. Syst., 2018

Recent advances in efficient computation of deep convolutional neural networks.
Frontiers Inf. Technol. Electron. Eng., 2018

From Hashing to CNNs: Training BinaryWeight Networks via Hashing.
CoRR, 2018

Semi-supervised Generative Adversarial Hashing for Image Retrieval.
Proceedings of the Computer Vision - ECCV 2018, 2018

Training Binary Weight Networks via Semi-Binary Decomposition.
Proceedings of the Computer Vision - ECCV 2018, 2018

Two-Step Quantization for Low-Bit Neural Networks.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

From Hashing to CNNs: Training Binary Weight Networks via Hashing.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Pseudo Label based Unsupervised Deep Discriminative Hashing for Image Retrieval.
Proceedings of the 2017 ACM on Multimedia Conference, 2017

Fast K-means for Large Scale Clustering.
Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017

2016
Quantized Convolutional Neural Networks for Mobile Devices.
Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

Shoot to Know What: An Application of Deep Networks on Mobile Devices.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
Learning Deep Features For MSR-bing Information Retrieval Challenge.
Proceedings of the 23rd Annual ACM Conference on Multimedia Conference, MM '15, Brisbane, Australia, October 26, 2015


  Loading...