QiQi's repositories
A-Simple-and-Effective-Framework-for-Pairewise-Distance-Metric-Learning
Detailed implementation of the paper
JDataCompetitionFinalCode
With two month hard work, my team achieved 13th rank of the algorithms game, not that good also not bad. So I upload our code here, share our experiment, hope it would be useful for the beginners.
ICCV2021_DeepAUC
Official implementation of the paper "Robust Deep AUC Maximization: A New Surrogate Loss and Empirical Studies on Medical Image Classification, ICCV2021"
beautiful-jekyll
:sparkles: Build a beautiful and simple website in literally minutes. Demo at http://deanattali.com/beautiful-jekyll
bigBatch
Code used to generate the results appearing in "Train longer, generalize better: closing the generalization gap in large batch training of neural networks"
boltzmann-machines
Boltzmann Machines in TensorFlow with examples
DC-Functions-with-Nonconvex-Nonsmooth-Regularizer
This is part of the code about PU learning of the paper http://proceedings.mlr.press/v97/xu19c/xu19c.pdf
deeplearning-models
A collection of various deep learning architectures, models, and tips
facenet
Face recognition using Tensorflow
facenet_pytorch
PyTorch implementation of the paper "FaceNet: A Unified Embedding for Face Recognition and Clustering"
fast-dro
PyTorch implementation of efficient algorithms for DRO with CVaR and Chi-Square uncertainty sets
HUCAM
ACM practice by JAVA
incubator-mxnet
Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more
jd
JData京东算法大赛入门程序
Keras-FlappyBird
Using Keras and Deep Q-Network to Play FlappyBird
models
Models and examples built with TensorFlow
Numeric-Represents-on-Evolutionary-Fitness-Results
Recent Research Work.
pytorch-custom-cuda-tutorial
Tutorial for building a custom CUDA function for Pytorch
qiqi-helloworld.github.io-qiqi
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
Stochastic-Optimization-of-Areas-Under-Precision-Recall-Curves-with-Provable-Convergence-AUPRC
@article{qi2021stochastic, title={Stochastic Optimization of Area Under Precision-Recall Curve for Deep Learning with Provable Convergence}, author={Qi, Qi and Luo, Youzhi and Xu, Zhao and Ji, Shuiwang and Yang, Tianbao}, journal={arXiv preprint arXiv:2104.08736}, year={2021} }
vision
Datasets, Transforms and Models specific to Computer Vision