kiminh Goto Github PK

xbyak

a JIT assembler for x86(IA-32)/x64(AMD64, x86-64) MMX/SSE/SSE2/SSE3/SSSE3/SSE4/FPU/AVX/AVX2/AVX-512 by C++ header

xe-ndcg-experiments

Code to reproduce the experiments reported in "An Alternative Cross Entropy Loss for Learning-to-Rank" (https://arxiv.org/abs/1911.09798)

xf_event_extraction2020top1

科大讯飞2020事件抽取挑战赛第一名解决方案&完整事件抽取系统

xfea

feature engineering toolbox implement in C++ for online and offline consistency

xfeat

Flexible Feature Engineering & Exploration Library using GPUs and Optuna.

xflow

Distributed LR、 FM model on Parameter Server. FTRL and SGD Optimization Algorithm.

xfmers

Quickly initialize bespoke Transformers

xgbm

eXplainable AI using Gradient Boosting Models with LightGBM, XGBoost, and CatBoost.

xgboost-c-cplusplus

c/c++ code for xgboost(train,predict,evaluate)

xgboost-fastforest

Minimal library code to deploy XGBoost models in C++.

xgboost-java

A Java-only repack of XGBoost bindings

xgboost-survival-embeddings

Improving XGBoost survival analysis with embeddings and debiased estimators

xgboost_lr_ffm_hyperopt

xgrad-cam

xlearn

High performance, easy-to-use, and scalable machine learning package for Python and C++, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM).

xlearn0.44_sample

xlearn0.44 sample code for learnning

xlearning

AI on Hadoop

xlearning-xdml

extreame distributed machine learning

xplainer

Explainable AI made easy. Tool which enables developers to explore predictions of their deep learning models. Focused on image classification and TensorFlow 2+.

xrec

Models for explainable recommendation.

xtreme-distil-transformers

XtremeDistil framework for distilling/compressing massive multilingual neural network models to tiny and efficient models for AI at scale

xtremedistil

yahoo-answers-topic-classification-dataset

yahp

hyperparameter management

yolov3-channel-and-layer-pruning

yolov3 channel and layer pruning, Knowledge Distillation 层剪枝，通道剪枝，知识蒸馏

youtube-algorithmic-bias

To uncover the algorithmic biases exhibited by the YouTube content ranking and recommendation algorithms.

youtube-dl

Repository with the code of youtube-dl

youtubednn

Impementation paper "Deep Neural Networks for YouTube Recommendations"

ysaito-qiita

qiita記事用の実験ファイルや実装したツール群

yskip

Incremental Skip-gram Model with Negative Sampling