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Model Compression

1,718 papers

Papers per year

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Papers

Data-Distortion Guided Self-Distillation for Deep Neural Networks AAAI 2019
Balanced Sparsity for Efficient DNN Inference on GPU AAAI 2019
Network Recasting: A Universal Method for Network Architecture Transformation AAAI 2019
Near-Lossless Binarization of Word Embeddings AAAI 2019
Similarity Preserving Deep Asymmetric Quantization for Image Retrieval AAAI 2019
Learning Compressed Sentence Representations for On-Device Text Processing ACL 2019
On-device Structured and Context Partitioned Projection Networks ACL 2019
Flambé: A Customizable Framework for Machine Learning Experiments ACL 2019
Towards a Theoretical Understanding of Hashing-Based Neural Nets AISTATS 2019
KAMA-NNs: Low-dimensional Rotation Based Neural Networks AISTATS 2019
Adaptive Ensemble Prediction for Deep Neural Networks based on Confidence Level AISTATS 2019
Unifying Heterogeneous Classifiers With Distillation CVPR 2019
Learning Without Memorizing CVPR 2019
Efficient Multi-Domain Learning by Covariance Normalization CVPR 2019
All You Need Is a Few Shifts: Designing Efficient Convolutional Neural Networks for Image Classification CVPR 2019
Quantization Networks CVPR 2019
Cross Domain Model Compression by Structurally Weight Sharing CVPR 2019
IRLAS: Inverse Reinforcement Learning for Architecture Search CVPR 2019
Fully Learnable Group Convolution for Acceleration of Deep Neural Networks CVPR 2019
Structured Pruning of Neural Networks With Budget-Aware Regularization CVPR 2019
Cascaded Projection: End-To-End Network Compression and Acceleration CVPR 2019
ECC: Platform-Independent Energy-Constrained Deep Neural Network Compression via a Bilinear Regression Model CVPR 2019
Importance Estimation for Neural Network Pruning CVPR 2019
Regularizing Activation Distribution for Training Binarized Deep Networks CVPR 2019
Simultaneously Optimizing Weight and Quantizer of Ternary Neural Network Using Truncated Gaussian Approximation CVPR 2019