About me

Education

Georgia Institue of Technology, ISyE

2017-now

Ph.D. in Machine Learning (Expected)

University of Science and Technology of China, ScGY

2013-2017

B.S. in Mathematics and Computer Science.

Professional Experience

Microsoft -- Research Intern

2019-Summer

Profile

I am a 3rd year PhD student in the School of Industrial and Systems Engineering (ISyE) at Georgia Tech. Before I joined Georgia Tech, I received my B.S. Degree in Computer Science and Mathematics from the School of the Gifted Young at University of Science and Technology of China.
My research focuses on deep Learning, adversarial machine learning and open source software development for scientific computing. I am working with Prof. Tuo Zhao in the FLASH (Foundations of LeArning Systems for alcHemy) research group.
Email: jianghm@gatech.edu

Research

Preprints and Working Papers

SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization

2019

Haoming Jiang, Pengcheng He, Weizhu Chen, Xiaodong Liu, Jianfeng Gao and Tuo Zhao [arXiv] [Code]
News (2019/12/05): Rank #1 on GLUE

On the Variance of the Adaptive Learning Rate and Beyond

2019

Liyuan Liu, Haoming Jiang, Pengcheng He, Weizhu Chen, Xiaodong Liu, Jianfeng Gao and Jiawei Han [arXiv] [Code]

Multi-Domain Neural Machine Translation with Word-Level Adaptive Layer-wise Domain Mixing

2019

Haoming Jiang, Chen Liang, Chong Wang and Tuo Zhao [arXiv]

Learning to Defense by Learning to Attack

2019

Zhehui Chen*, Haoming Jiang*, Bo Dai, and Tuo Zhao (*Equal Contribution) [arXiv]
International Conference on Learning Representations (ICLR), Workshop DeepGenStruct, 2019

Boosting Pathwise Coordiante Optimization: Sequential Screening and Proximal Subsampled Newton Subroutine

2018

Haoming Jiang, Xingguo Li, Jason Ge, Mengdi Wang, Mingyi Hong and Tuo Zhao [Code]

Publications

Efficient Approximation of Deep ReLU Networks for Functions on Low Dimensional Manifolds

2019

Minshuo Chen, Haoming Jiang, Wenjing Liao and Tuo Zhao
Annual Conference on Neural Information Processing Systems (NIPS), 2019 [arXiv]

Meta Learning with Relational Information for Short Sequences

2019

Yujia Xie, Haoming Jiang, Feng Liu, Tuo Zhao and Hongyuan Zha
Annual Conference on Neural Information Processing Systems (NIPS), 2019 [arXiv]

On Fast Convergence of Proximal Algorithms for SQRT-Lasso Optimization: Don't Worry About Its Nonsmooth Loss Function

2019

Xingguo Li, Haoming Jiang, Jarvis Haupt, Raman Arora, Han Liu, Mingyi Hong and Tuo Zhao
Conference on Uncertainty in Artificial Intelligence (UAI), 2019 [arXiv] [Code]

On Scalable and Efficient Computation of Large Scale Optimal Transport

2019

Yujia Xie, Minshuo Chen, Haoming Jiang, Tuo Zhao, Hongyuan Zha
International Conference on Machine Learning (ICML), 2019 [arXiv] [Code]

On Computation and Generalization of Generative Adversarial Networks under Spectrum Control

2019

Haoming Jiang, Zhehui Chen, Minshuo Chen, Feng Liu, Dingding Wang, Tuo Zhao
International Conference on Learning Representations (ICLR), 2019 [Pdf] [Code]

Picasso: A Sparse Learning Library for High Dimensional Data Analysis in R and Python

2019

Jason Ge*, Xingguo Li*, Haoming Jiang, Han Liu, Tong Zhang, Mengdi Wang and Tuo Zhao (*Equal Contribution)
Journal of Machine Learning Research (JMLR), 2019 [Pdf] [R Package] [Python Package]

Contextual Text Denoising with Masked Language Model

2019

Yifu Sun, Haoming Jiang
Conference on Empirical Methods in Natural Language Processing (EMNLP), Workshop W-NUT, 2019 [Pdf]

Designing Deployable 3D Scissor Structures with Ball-and-Socket Joints

2018

Xuejin Chen, Haoming Jiang, Tingting Xuan, Lihan Huang, Ligang Liu
Computer Animation & Virtual Worlds (CAVW), 2018 [Pdf]

Scissor-based 3D deployable contours

2017

Haoming Jiang, Xuejin Chen, Tingting Xuan, Lihan Huang, Ligang Liu
International Conference on Virtual Reality and Visualization (ICVRV), 2017 [Pdf]

Softwares

PICASSO: PathwIse CalibrAted Sparse Shooting algOrithm [R Package] [Python Package]

HUGE: High-Dimensional Undirected Graph Estimation [R Package]

SAM: Sparse Additive Modelling [R Package]

ESMOTE: Efficient Synthetic Minority Over-sampling Technique [R Package]

Setup Toolkits: A quick setup toolkit for vim,tmux,zsh on linux server [zip]

FlashPythonToolbox: A few ready-to use python tools for machine learning [Github]

Other Projects

Risk Adjusted Surgeon Score Card Development for Emory Hospital

2018

Innovative SMOTE for High Dimensional and Large Scaled Imbalanced Data [R Package] [Chinese Dissertation]

2017

Data Driven Approach for Deploying Charging Station for Electric Vehicles [Chinese Dissertation]

2017

Analyzing Tweets Sentiment via Machine Learning Approach [Report][Tokenizer] [Extra Unlabeled Data] [Tweets Vectors]

2016

Deep Reinforcement Learning For Raiden Game [Report] [Demo]

2016

Development of GeoLab, an open source 3D model processing system [GeoLab]

2015

Development of body interactive game based on Kinect [Report] [Vedio]

2015

[NOTES] T5, s, Small BERT, MTDA, Distributed Optimization, Introduction to Data Mining ( 2 3 4 5 6 7 8 9 10 ), Social Media Mining ( Link Chp5 )