neural network quantization

Simple Augmentation Goes a Long Way: ADRL for DNN Quantization ICLR 2021 Stochastic Precision Ensemble: Self-Knowledge Distillation for Quantized Deep Neural Networks AAAI 2021 TRQ: Ternary Neural Networks With Residual Quantization AAAI 2021 AdaBits: Neural Network Quantization With Adaptive Bit-Widths CVPR 2020 Adaptive Loss-Aware Quantization for Multi-Bit Networks CVPR 2020 Additive Powers-of-Two Quantization: An Efficient Non-uniform Discretization for Neural Networks ICLR 2020 Bayesian Bits: Unifying Quantization and Pruning NeurIPS 2020 Defending and Harnessing the Bit-Flip Based Adversarial Weight Attack CVPR 2020 Divide and Conquer: Leveraging Intermediate Feature Representations for Quantized Training of Neural Networks ICML 2020 Fully Nested Neural Network for Adaptive Compression and Quantization IJCAI 2020 Harmonious Coexistence of Structured Weight Pruning and Ternarization for Deep Neural Networks AAAI 2020 HAWQ-V2: Hessian Aware trace-Weighted Quantization of Neural Networks NeurIPS 2020 HLHLp: Quantized Neural Networks Training for Reaching Flat Minima in Loss Surface AAAI 2020 Linear Symmetric Quantization of Neural Networks for Low-precision Integer Hardware ICLR 2020 Mixed Precision DNNs: All you need is a good parametrization ICLR 2020 Overflow Aware Quantization: Accelerating Neural Network Inference by Low-bit Multiply-Accumulate Operations IJCAI 2020 Rethinking Differentiable Search for Mixed-Precision Neural Networks CVPR 2020 Robust Quantization: One Model to Rule Them All NeurIPS 2020 Rotated Binary Neural Network NeurIPS 2020 RTN: Reparameterized Ternary Network AAAI 2020 Searching for Low-Bit Weights in Quantized Neural Networks NeurIPS 2020 Soft Threshold Ternary Networks IJCAI 2020 Sparsity-Inducing Binarized Neural Networks AAAI 2020 Towards Accurate Low Bit-Width Quantization with Multiple Phase Adaptations AAAI 2020 Training Quantized Neural Networks With a Full-Precision Auxiliary Module CVPR 2020