Qi Qi @ The University of Iowa
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Graduate Student |
Short Bio
I am a Research Scientist at LLama Applied Multimodal team working on post-training. I have received Ph.D. degree in the Department of Computer Science from the machine learning and optimization group of University of Iowa under the supervision of Prof. Tianbao Yang. Before joined UIowa, I received master degree from University of Science and Technology of China under the supervision of Prof. Thomas Weise and bachelor degree from Qingdao University of Technology.
Before joining meta, I spent a year at Tiktok E-commerce working on multi-modal LLM for platform governance. Every experience is valuable, but some are not ones you'd want to go through again.News
- [11/22] Try our new package ABSGD for handling the general imbalanced classification by just modifying the loss and optimizer to ABLoss, ABSGD/ABAdam ! Tutorial!
- [10/22] Our ABSGD achieve 1st in ResNet50 (rank 4th of 16 in total) on the iWildCam dataset in Standford Wilds out of distribution competition! Try our Code!
- [08/22] Second amazing intern journey at Netflix, work with Shervin Ardeshir and M. Hossein Taghavi
- [01/22] Give an invited talk in 2022 at UberAI about AUPRC maximization.
Packages and Competitions
- I am the author of CIDFLIX, ABSGD package and a contributor of LibAUC (impelemented the AUPRC algorithm)
- Top 1 in ResNet50 (4th/16), iWildCam multi-class species classification, by Standford, 10/2022, [Code]
- Top 1% (11th/4000+), High Potential User Purchase Intention Prediction, by JD.com , [Code]
- QCRD: Quality-guided Contrastive Rationale Distillation for Large Language Models [Arxiv] Wei Wang, Zhaowei Li, Qi Xu, Yiqing Cai, Hang Song, Qi Qi, Ran Zhou, Zhida Huang, Tao Wang, Li Xiao.
- Provable Optimization for Adversarial Fair
Self-supervised Contrastive Learning [Arxiv]
Qi Qi, Quanqi Hu, Qihang Lin, Tianbao Yang - Apple, Machine Learning Intern, June - September, 2023
• Project: Knowledge distillation for next-generation display content object detection
- Netflix, Computer Vision Intern, June - August, 2021/2022
• Project: Imporving identity robustness for face models.
- GroundingGPT:Language Enhanced Multi-modal Grounding Model [Paper][Code]
Zhaowei Li, Qi Xu, Dong Zhang, Hang Song, Yiqing Cai, Qi Qi, Ran Zhou, Junting Pan, Zefeng Li, Van Tu Vu, Zhida Huang, Tao Wangr
To Appear at (ACL 2024) - AUPRC: Stochastic Optimization of Area Under Precision-Recall Curve for Deep Learning with Provable Convergence [Paper][Code Package] [Poster] [Slides]
Qi Qi, Youzhi Luo, Zhao Xu, Shuiwang Ji, Tianbao Yang.
Proceedings of the 35th Conference on Neural Information Processing Systems (NeurIPS 2021, 250+ Github Star) - A Simple and Effective Framework for Pairwise Deep Metric Learning. [Paper][Code][Poster] [Video]
Qi Qi, Yan Yan, Xiaoyu Wang, Tianbao Yang.
16th European Conference on Computer Vision (ECCV 2020) - ABSGD: Attentional Biased Stochastic Gradient for Imbalanced Classification. [Paper] [Code]
Qi Qi, Yi Xu, Rong Jin, Wotao Yin, Tianbao Yang.
Transactions on Machine Learning Research (TMLR, 2023) - Improving Identity-Robustness for Face Models [Paper][Code]
Qi Qi, Shervin Ardershir
The short version to appear at (ICML 2023 SCIS Workshop) - Stochastic Constrained DRO with a Complexity Independent of Sample Size. [Paper][Code]
Qi Qi, Jiameng Lyu, Kung-sik Chan, Er-Wei Bai, Tianbao Yang.
Transactions on Machine Learning Research (TMLR, 2023) - RECOVER: A Practical Online Method for Distributionally Deep Robust Optimization. [Paper][Code][Poster] [Slides]
Qi Qi, Zhishuai Guo, Yi Xu, Rong Jin, Tianbao Yang.
Proceedings of the 35th Conference on Neural Information Processing Systems (NeurIPS 2021) - Variance-Reduced Off-Policy Memory-Efficient Policy Search [Paper][Code]
Daoming Lyu, Qi Qi, Mohammad Ghavamzadeh, Hengshuai Yao, Tianbao Yang, Bo Liu.
Offline Reinforcement Learning Workshop at 34th-Neural Information Processing Systems (Neurips 2020 Workshop) - Stochastic optimization for DC functions and non-smooth non-convex regularizers with non-asymptotic convergence. [Paper][Code]
Yi Xu, Qi Qi, Qihang Lin, Rong Jin, Tianbao Yang.
Proceedings of the 36th International Conference on Machine Learning (ICML 2019). - Modeling optimization algorithm runtime behavior and its applications. [Paper]
Qi Qi, Thomas Weise, and Bin Li.
Proceedings of the Genetic and Evolutionary Computation Conference Companion (GECCO 2017). - Optimization algorithm behavior modeling: A study on the traveling salesman problem[C] [Paper][Slides]
Qi Qi, Thomas Weise, and Bin Li.
Tenth International Conference on Advanced Computational Intelligence ( ICACI 2018). - Automatically discovering clusters of algorithm and problem instance behaviors as well as their causes from experimental data, algorithm setups, and instance features[J] [Paper]
Thomas Weise, Xiaofeng Wang, Qi Qi, Ke Tang, Bin Li.
Applied Soft Computing, 2018, 73: 366-382. - CS 3330 Algorithms
University of Uiowa, Spring 2019
Instructor: Dr. Bandyapadhyay - CS 4350 Logic in Computer Science
University of Iowa, Fall 2018
Instructor: Prof. Hantao Zhang - First Prize of Graduate Scholarship, University of Science and Technology of China, Sep. 2017.
- Outstadning Graduate Awards, Qingdao Technology University, Jul. 2015.
- National Undergraduate Scholarship, Ministry of Education of China, Nov. 2012.
