neural network compression

Accelerated Inference Framework of Sparse Neural Network Based on Nested Bitmask Structure IJCAI 2019 Approximated Oracle Filter Pruning for Destructive CNN Width Optimization ICML 2019 Data-Dependent Coresets for Compressing Neural Networks with Applications to Generalization Bounds ICLR 2019 ECC: Platform-Independent Energy-Constrained Deep Neural Network Compression via a Bilinear Regression Model CVPR 2019 EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis ICML 2019 HAQ: Hardware-Aware Automated Quantization With Mixed Precision CVPR 2019 KAMA-NNs: Low-dimensional Rotation Based Neural Networks AISTATS 2019 OICSR: Out-In-Channel Sparsity Regularization for Compact Deep Neural Networks CVPR 2019 PRADO: Projection Attention Networks for Document Classification On-Device EMNLP 2019 Private Model Compression via Knowledge Distillation AAAI 2019 Towards a Theoretical Understanding of Hashing-Based Neural Nets AISTATS 2019 Adaptive Quantization of Neural Networks ICLR 2018 Compressing Neural Networks using the Variational Information Bottleneck ICML 2018 NestedNet: Learning Nested Sparse Structures in Deep Neural Networks CVPR 2018 Network Approximation using Tensor Sketching IJCAI 2018 Semi-Orthogonal Low-Rank Matrix Factorization for Deep Neural Networks Interspeech 2018 Stronger Generalization Bounds for Deep Nets via a Compression Approach ICML 2018 Structured Evolution with Compact Architectures for Scalable Policy Optimization ICML 2018 Verifiable Reinforcement Learning via Policy Extraction NeurIPS 2018 Weightless: Lossy weight encoding for deep neural network compression ICML 2018 Soft-to-Hard Vector Quantization for End-to-End Learning Compressible Representations NeurIPS 2017 Theoretical Properties for Neural Networks with Weight Matrices of Low Displacement Rank ICML 2017