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Quantization

92 papers with code · Methodology

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FastText.zip: Compressing text classification models

12 Dec 2016facebookresearch/fastText

We consider the problem of producing compact architectures for text classification, such that the full model fits in a limited amount of memory.

QUANTIZATION TEXT CLASSIFICATION WORD EMBEDDINGS

Link and code: Fast indexing with graphs and compact regression codes

CVPR 2018 facebookresearch/faiss

Similarity search approaches based on graph walks have recently attained outstanding speed-accuracy trade-offs, taking aside the memory requirements.

IMAGE SIMILARITY SEARCH QUANTIZATION

Billion-scale similarity search with GPUs

28 Feb 2017facebookresearch/faiss

Similarity search finds application in specialized database systems handling complex data such as images or videos, which are typically represented by high-dimensional features and require specific indexing structures.

IMAGE SIMILARITY SEARCH QUANTIZATION

Polysemous codes

7 Sep 2016facebookresearch/faiss

This paper considers the problem of approximate nearest neighbor search in the compressed domain.

QUANTIZATION

Trained Ternary Quantization

4 Dec 2016tensorpack/tensorpack

To solve this problem, we propose Trained Ternary Quantization (TTQ), a method that can reduce the precision of weights in neural networks to ternary values.

QUANTIZATION

Improving Neural Network Quantization without Retraining using Outlier Channel Splitting

28 Jan 2019NervanaSystems/distiller

The majority of existing literature focuses on training quantized DNNs, while this work examines the less-studied topic of quantizing a floating-point model without (re)training.

LANGUAGE MODELLING NEURAL NETWORK COMPRESSION QUANTIZATION

Fast Adjustable Threshold For Uniform Neural Network Quantization

19 Dec 2018NervanaSystems/distiller

It can be performed without fine-tuning using calibration procedure (calculation of parameters necessary for quantization), or it is possible to train the network with quantization from scratch.

QUANTIZATION

Model compression via distillation and quantization

ICLR 2018 NervanaSystems/distiller

Deep neural networks (DNNs) continue to make significant advances, solving tasks from image classification to translation or reinforcement learning.

MODEL COMPRESSION QUANTIZATION

Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding

1 Oct 2015NervanaSystems/distiller

To address this limitation, we introduce "deep compression", a three stage pipeline: pruning, trained quantization and Huffman coding, that work together to reduce the storage requirement of neural networks by 35x to 49x without affecting their accuracy.

QUANTIZATION

Word2Bits - Quantized Word Vectors

15 Mar 2018agnusmaximus/Word2Bits

Word vectors require significant amounts of memory and storage, posing issues to resource limited devices like mobile phones and GPUs.

QUANTIZATION QUESTION ANSWERING