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Quantization

102 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

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

HAQ: Hardware-Aware Automated Quantization with Mixed Precision

CVPR 2019 MIT-HAN-LAB/ProxylessNAS

Compared with conventional methods, our framework is fully automated and can specialize the quantization policy for different neural network architectures and hardware architectures.

QUANTIZATION