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Hi there πŸ‘‹

Currently, I am a senior software engineer at Alibaba Group. My job focuses on building platforms for training and serving large deep learning models, such as diffusion models and transformers used in AIGC applications.

Before joining Alibaba, I was a software engineer at Huawei Cloud. During this period, I worked on a cloud native software for data analysis and federated learning. My work is about building a Spark-like distributed execution framework, and implementing distributed machine learning models. A lot of my efforts were also devoted to performance optimization using parallel computing, heterogeneous computing, and distributed computing.

I got my M.Sc degree from the Learning And Mining from DatA (LAMDA) group in Nanjing University, supervised by Prof. Zhi-Hua Zhou and Prof. Yuan Jiang. My research interests included ensemble learning and its applications in areas like anomaly detection and federated learning. Two popular repositories developed by me are Ensemble-Pytorch and Deep-Forest.

Yi-Xuan XU's Projects

clustering icon clustering

Clustering / Subspace Clustering Algorithms on MATLAB

deep-clustering-network icon deep-clustering-network

PyTorch Implementation of "Towards K-Means-Friendly Spaces: Simultaneous Deep Learning and Clustering," Bo Yang et al., ICML'2017.

deep-forest icon deep-forest

An Efficient, Scalable and Optimized Python Framework for Deep Forest (2021.2.1)

deepctr-torch icon deepctr-torch

【PyTorch】Easy-to-use,Modular and Extendible package of deep-learning based CTR models.

diffusers icon diffusers

πŸ€— Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch

ensemble-pytorch icon ensemble-pytorch

A unified ensemble framework for PyTorch to improve the performance and robustness of your deep learning model.

gcforest icon gcforest

This is the official implementation for the paper 'Deep forest: Towards an alternative to deep neural networks'

ipython icon ipython

Official repository for IPython itself. Other repos in the IPython organization contain things like the website, documentation builds, etc.

lcodc icon lcodc

A Latency and Coverage Optimized Data Collection Scheme for Smart Cities Based on Vehicular Ad-hoc Networks, Sensors, 2017.

light-random-forest icon light-random-forest

Experimental Random Forest for Handling Extremely Large Dataset based on Scikit-Learn.

megatron-lm icon megatron-lm

Ongoing research training transformer models at scale

pyod icon pyod

A Python Toolbox for Scalable Outlier Detection (Anomaly Detection)

recforest icon recforest

Implementation of "Reconstruction-based Anomaly Detection with Completely Random Forest," SIAM International Conference on Data Mining (SDM), 2021.

sktime icon sktime

A unified framework for machine learning with time series

soft-decision-tree icon soft-decision-tree

PyTorch Implementation of "Distilling a Neural Network Into a Soft Decision Tree." Nicholas Frosst, Geoffrey Hinton., 2017.

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