The implementation of AAAI-17 paper "Collective Deep Quantization of Efficient Cross-modal Retrieval"
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Updated
Mar 15, 2017 - Python
The implementation of AAAI-17 paper "Collective Deep Quantization of Efficient Cross-modal Retrieval"
The implementation of CVPR-17 paper "Deep Visual-Semantic Quantization of Efficient Image Retrieval"
Algorithms related to clustering such as k-Medians, DBSCAN as well as vector quantization.
Exploring "Binary Neural Networks" (https://arxiv.org/abs/1602.02830) in Theano. A set of experiments that use binarised weights and/or activations to reduce computational load of convolutional neural networks.
Some implementations of the Neural Networks Quantization algorithms.
Optimize any image by chroma subsampling and optimized huffman coding in Python. Basically, using JPEG algorithm!
Ternary Gradients to Reduce Communication in Distributed Deep Learning (TensorFlow)
Optimizing Deep Convolutional Neural Network with Ternarized Weights and High Accuracy
SDK for TEE AI Stick (includes model training script, inference library, examples)
Training models with ternary quantized weights using PyTorch
Quantized training using Keras
TensorFlow Quantization Example, for TensorFlow Lite
A Python Wrapper of Pngquant
Some codes used for the numerical examples proposed in https://arxiv.org/abs/1812.05916
Embedding Quantization (Compress Word Embeddings)
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