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Quantization

148 papers with code ยท Methodology

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Precision Gating: Improving Neural Network Efficiency with Dynamic Dual-Precision Activations

17 Feb 2020

We propose precision gating (PG), an end-to-end trainable dynamic dual-precision quantization technique for deep neural networks.

QUANTIZATION

Efficient Matrix Multiplication: The Sparse Power-of-2 Factorization

10 Feb 2020

We present an algorithm to reduce the computational effort for the multiplication of a given matrix with an unknown column vector.

QUANTIZATION

BitPruning: Learning Bitlengths for Aggressive and Accurate Quantization

8 Feb 2020

Neural networks have demonstrably achieved state-of-the art accuracy using low-bitlength integer quantization, yielding both execution time and energy benefits on existing hardware designs that support short bitlengths.

QUANTIZATION

Switchable Precision Neural Networks

7 Feb 2020

Instantaneous and on demand accuracy-efficiency trade-off has been recently explored in the context of neural networks slimming.

QUANTIZATION

Accelerating Deep Learning Inference via Freezing

7 Feb 2020

In this work, we observe that caching intermediate layer outputs can help us avoid running all the layers of a DNN for a sizeable fraction of inference requests.

QUANTIZATION

Random VLAD based Deep Hashing for Efficient Image Retrieval

6 Feb 2020

In addition, the proposed random VLAD layer leads to satisfactory accuracy with low complexity, thus shows promising potentials as an alternative to NetVLAD.

IMAGE RETRIEVAL QUANTIZATION

Achieving the fundamental convergence-communication tradeoff with Differentially Quantized Gradient Descent

6 Feb 2020

The problem of reducing the communication cost in distributed training through gradient quantization is considered.

QUANTIZATION

Generating diverse and natural text-to-speech samples using a quantized fine-grained VAE and auto-regressive prosody prior

6 Feb 2020

Recent neural text-to-speech (TTS) models with fine-grained latent features enable precise control of the prosody of synthesized speech.

DATA AUGMENTATION QUANTIZATION SPEECH RECOGNITION

Emotion Recognition Using Speaker Cues

4 Feb 2020

This research aims at identifying the unknown emotion using speaker cues.

EMOTION RECOGNITION QUANTIZATION

Automatic Pruning for Quantized Neural Networks

3 Feb 2020

In particular, for ResNet-18 on ImageNet, we prune 26. 12% of the model size with Binarized Neural Network quantization, achieving a top-1 classification accuracy of 47. 32% in a model of 2. 47 MB and 59. 30% with a 2-bit DoReFa-Net in 4. 36 MB.

QUANTIZATION