SOTAVerified

Quantization

Quantization is a promising technique to reduce the computation cost of neural network training, which can replace high-cost floating-point numbers (e.g., float32) with low-cost fixed-point numbers (e.g., int8/int16).

Source: Adaptive Precision Training: Quantify Back Propagation in Neural Networks with Fixed-point Numbers

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 3751–3800 of 4925 papers

TitleStatusHype
Automated Model Compression by Jointly Applied Pruning and Quantization—0
Pixel precise unsupervised detection of viral particle proliferation in cellular imaging data—0
Going Below and Beyond, Off-the-Grid Velocity Estimation from 1-bit Radar Measurements—0
The quantization error in a Self-Organizing Map as a contrast and colour specific indicator of single-pixel change in large random patterns—0
Modified Vector Quantization for Small-Cell Access Point Placement with Inter-Cell Interference—0
S3-Net: A Fast and Lightweight Video Scene Understanding Network by Single-shot Segmentation—0
Robust building footprint extraction from big multi-sensor data using deep competition network—0
Subtensor Quantization for Mobilenets—0
Paralinguistic Privacy Protection at the Edge—0
A Linearly Convergent Algorithm for Decentralized Optimization: Sending Less Bits for Free!—0
Analytical aspects of non-differentiable neural networks—0
A Greedy Bit-flip Training Algorithm for Binarized Knowledge Graph Embeddings—0
High Performance Natural Language Processing—0
Time regularization as a solution to mitigate quantization induced performance degradation—0
One-Bit Direct Position Determination of Narrowband Gaussian Signals—0
Diagnostic data integration using deep neural networks for real-time plasma analysis—0
INT8 Winograd Acceleration for Conv1D Equipped ASR Models Deployed on Mobile Devices—0
Enhanced Blind Calibration of Uniform Linear Arrays with One-Bit Quantization by Kullback-Leibler Divergence Covariance Fitting—0
Full-Duplex Cell-Free mMIMO Systems: Analysis and Decentralized Optimization—0
FD Cell-Free mMIMO: Analysis and Optimization—0
A QP-adaptive Mechanism for CNN-based Filter in Video Coding—0
MARS: Multi-macro Architecture SRAM CIM-Based Accelerator with Co-designed Compressed Neural Networks—0
Millimeter Wave MIMO Channel Estimation with 1-bit Spatial Sigma-delta Analog-to-Digital Converters—0
Linearly Converging Error Compensated SGDCode0
Recovery of sparse linear classifiers from mixture of responses—0
On Resource-Efficient Bayesian Network Classifiers and Deep Neural NetworksCode0
Mixed-Precision Embedding Using a Cache—0
Comparing Fisher Information Regularization with Distillation for DNN Quantization—0
Robustness-aware 2-bit quantization with real-time performance for neural network—0
FTBNN: Rethinking Non-linearity for 1-bit CNNs and Going BeyondCode0
Check-N-Run: A Checkpointing System for Training Deep Learning Recommendation Models—0
CQ-VAE: Coordinate Quantized VAE for Uncertainty Estimation with Application to Disk Shape Analysis from Lumbar Spine MRI Images—0
Volumetric Calculation of Quantization Error in 3-D Vision Systems—0
Federated Learning in Adversarial Settings—0
FPRaker: A Processing Element For Accelerating Neural Network Training—0
Towards Accurate Quantization and Pruning via Data-free Knowledge Transfer—0
An Investigation on Different Underlying Quantization Schemes for Pre-trained Language Models—0
Enhancement Of Coded Speech Using a Mask-Based Post-Filter—0
Real-time Mask Detection on Google Edge TPU—0
3DMolNet: A Generative Network for Molecular Structures—0
Optimal Gradient Compression for Distributed and Federated Learning—0
AxFormer: Accuracy-driven Approximation of Transformers for Faster, Smaller and more Accurate NLP ModelsCode0
Characterising Bias in Compressed Models—0
Joint Pruning & Quantization for Extremely Sparse Neural Networks—0
Sparse Quantized Spectral Clustering—0
GECKO: Reconciling Privacy, Accuracy and Efficiency in Embedded Deep Learning—0
BiLiMO: Bit-Limited MIMO Radar via Task-Based Quantization—0
Faster Binary Embeddings for Preserving Euclidean DistancesCode0
Compress Polyphone Pronunciation Prediction Model with Shared Labels—0
How LSTM Encodes Syntax: Exploring Context Vectors and Semi-Quantization on Natural Text—0
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All datasetsImageNetCIFAR-10Wiki-40BAgeDB-30CFP-FPCOCO (Common Objects in Context)IJB-BIJB-CKnowledge-based:LFW

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1FQ-ViT (ViT-L)Top-1 Accuracy (%)85.03—Unverified
2FQ-ViT (ViT-B)Top-1 Accuracy (%)83.31—Unverified
3FQ-ViT (Swin-B)Top-1 Accuracy (%)82.97—Unverified
4FQ-ViT (Swin-S)Top-1 Accuracy (%)82.71—Unverified
5FQ-ViT (DeiT-B)Top-1 Accuracy (%)81.2—Unverified
6FQ-ViT (Swin-T)Top-1 Accuracy (%)80.51—Unverified
7FQ-ViT (DeiT-S)Top-1 Accuracy (%)79.17—Unverified
8Xception W8A8Top-1 Accuracy (%)78.97—Unverified
9ADLIK-MO-ResNet50-W4A4Top-1 Accuracy (%)77.88—Unverified
10ADLIK-MO-ResNet50-W3A4Top-1 Accuracy (%)77.34—Unverified
#ModelMetricClaimedVerifiedStatus
13DCNN_VIVA_3MAP160,327.04—Unverified
2DTQMAP0.79—Unverified
#ModelMetricClaimedVerifiedStatus
1OutEffHop-Bert_basePerplexity6.3—Unverified
2OutEffHop-Bert_basePerplexity6.21—Unverified
#ModelMetricClaimedVerifiedStatus
1Accuracy98.13—Unverified
#ModelMetricClaimedVerifiedStatus
1Accuracy92.92—Unverified
#ModelMetricClaimedVerifiedStatus
1SSD ResNet50 V1 FPN 640x640MAP34.3—Unverified
#ModelMetricClaimedVerifiedStatus
1TAR @ FAR=1e-495.13—Unverified
#ModelMetricClaimedVerifiedStatus
1TAR @ FAR=1e-496.38—Unverified
#ModelMetricClaimedVerifiedStatus
13DCNN_VIVA_5All84,809,664—Unverified
#ModelMetricClaimedVerifiedStatus
1Accuracy99.8—Unverified