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Model Compression

1928 directly classified papers

Papers per year

Papers

Feature-map-level Online Adversarial Knowledge Distillation ICML 2020
HAWQ-V2: Hessian Aware trace-Weighted Quantization of Neural Networks NIPS 2020
Position-based Scaled Gradient for Model Quantization and Pruning NIPS 2020
Automatic Differentiation of Sketched Regression AISTATS 2020
Iterative Compression of End-to-End ASR Model Using AutoML INTERSPEECH 2020
TinyBERT: Distilling BERT for Natural Language Understanding EMNLP 2020
Attribution Preservation in Network Compression for Reliable Network Interpretation NIPS 2020
BRP-NAS: Prediction-based NAS using GCNs NIPS 2020
AdaBERT: Task-Adaptive BERT Compression with Differentiable Neural Architecture Search IJCAI 2020
FastBERT: a Self-distilling BERT with Adaptive Inference Time ACL 2020
Learnable Bernoulli Dropout for Bayesian Deep Learning AISTATS 2020
AutoPrivacy: Automated Layer-wise Parameter Selection for Secure Neural Network Inference NIPS 2020
Optimal Lottery Tickets via Subset Sum: Logarithmic Over-Parameterization is Sufficient NIPS 2020
Movement Pruning: Adaptive Sparsity by Fine-Tuning NIPS 2020
Funnel-Transformer: Filtering out Sequential Redundancy for Efficient Language Processing NIPS 2020
Training Binary Neural Networks through Learning with Noisy Supervision ICML 2020
Soft Threshold Weight Reparameterization for Learnable Sparsity ICML 2020
Channel Pruning Guided by Classification Loss and Feature Importance AAAI 2020
Real-Time Object Tracking via Meta-Learning: Efficient Model Adaptation and One-Shot Channel Pruning AAAI 2020
Towards Fully 8-bit Integer Inference for the Transformer Model IJCAI 2020
CDC: Classification Driven Compression for Bandwidth Efficient Edge-Cloud Collaborative Deep Learning IJCAI 2020
P-KDGAN: Progressive Knowledge Distillation with GANs for One-class Novelty Detection IJCAI 2020
Soft Threshold Ternary Networks IJCAI 2020
Channel Pruning via Automatic Structure Search IJCAI 2020
A Mean Field Theory of Quantized Deep Networks: The Quantization-Depth Trade-Off NIPS 2019