Model Compression

Validating the Lottery Ticket Hypothesis with Inertial Manifold Theory NeurIPS 2021 Winning Lottery Tickets in Deep Generative Models AAAI 2021 Winograd Algorithm for AdderNet ICML 2021 Zero-Shot Adversarial Quantization CVPR 2021 AdaBERT: Task-Adaptive BERT Compression with Differentiable Neural Architecture Search IJCAI 2020 AdaBits: Neural Network Quantization With Adaptive Bit-Widths CVPR 2020 Adaptive Loss-Aware Quantization for Multi-Bit Networks CVPR 2020 Adaptive Neural Connections for Sparsity Learning WACV 2020 Additive Powers-of-Two Quantization: An Efficient Non-uniform Discretization for Neural Networks ICLR 2020 Adversarially Robust Streaming Algorithms via Differential Privacy NeurIPS 2020 Adversarial Nonnegative Matrix Factorization ICML 2020 AI Feynman 2.0: Pareto-optimal symbolic regression exploiting graph modularity NeurIPS 2020 Analyzing Redundancy in Pretrained Transformer Models EMNLP 2020 And the Bit Goes Down: Revisiting the Quantization of Neural Networks ICLR 2020 A "Network Pruning Network'' Approach to Deep Model Compression WACV 2020 A Study on Encodings for Neural Architecture Search NeurIPS 2020 A Tensor Compiler for Unified Machine Learning Prediction Serving OSDI 2020 Attribution Preservation in Network Compression for Reliable Network Interpretation NeurIPS 2020 AutoCompress: An Automatic DNN Structured Pruning Framework for Ultra-High Compression Rates AAAI 2020 Automatic Differentiation of Sketched Regression AISTATS 2020 Automatic Neural Network Compression by Sparsity-Quantization Joint Learning: A Constrained Optimization-Based Approach CVPR 2020 AutoPrivacy: Automated Layer-wise Parameter Selection for Secure Neural Network Inference NeurIPS 2020 Auxiliary Training: Towards Accurate and Robust Models CVPR 2020 Balancing Cost and Benefit with Tied-Multi Transformers ACL 2020 Bayesian Bits: Unifying Quantization and Pruning NeurIPS 2020