Mathematical Foundations to Neural Network Optimization

Hard Drive Free ONNX IO

User Experience on LibTorch C++ API

Enable Parallelized Non-Autoregressive Decoding Process for Sequence to Sequence Tasks

Understand Autoregressive Models for Sequence to Sequence Tasks

Mathematical Foundations to Neural Network Pruning

Using Bootstrap Distribution to Approximate Sampling Distribution

Sampling Method for Multivariate Joint Distributions

Statistical Inference Requires Sampling

Running Machine Learning Inference as Service from Scratch

Conventional Classification Loss Functions Elucidated

Model Optimization with Genetically Evolved Hyperparameters

Mathematical Foundations to Neural Network Quantization

Gated Linear Units and Gated CNN Explained

Evolution Search on Transformer Neural Network Architectures

Understand the Sparsity Introduced by Group Lasso

Fundamental Theories of Gradient Boosting Machine

Continuing to Support Frozen Graph for TensorFlow 2.x

A Review on the Classic Word2Vec Models

Orchestrated Softmax for Fast Language Model Training