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model compression

3,562 papers

MC

Papers

Scaling Up Exact Neural Network Compression by ReLU Stability NeurIPS 2021 SEED: Self-supervised Distillation For Visual Representation ICLR 2021 Selective Knowledge Distillation for Neural Machine Translation ACL 2021 Self-boosting for Feature Distillation IJCAI 2021 Self-Born Wiring for Neural Trees ICCV 2021 Shallow-UWnet: Compressed Model for Underwater Image Enhancement (Student Abstract) AAAI 2021 Shapeshifter: a Parameter-efficient Transformer using Factorized Reshaped Matrices NeurIPS 2021 Show, Attend and Distill: Knowledge Distillation via Attention-based Feature Matching AAAI 2021 Shrinking Bigfoot: Reducing wav2vec 2.0 footprint EMNLP 2021 Simple and Effective Stochastic Neural Networks AAAI 2021 Simple and Effective Unsupervised Redundancy Elimination to Compress Dense Vectors for Passage Retrieval EMNLP 2021 Simple Augmentation Goes a Long Way: ADRL for DNN Quantization ICLR 2021 Skip-Convolutions for Efficient Video Processing CVPR 2021 Slimmable Compressive Autoencoders for Practical Neural Image Compression CVPR 2021 Slimmable Generative Adversarial Networks AAAI 2021 Slow Learning and Fast Inference: Efficient Graph Similarity Computation via Knowledge Distillation NeurIPS 2021 SmallER: Scaling Neural Entity Resolution for Edge Devices Interspeech 2021 Space-Time Distillation for Video Super-Resolution CVPR 2021 Sparsity in Deep Learning: Pruning and growth for efficient inference and training in neural networks JMLR 2021 Spike-Thrift: Towards Energy-Efficient Deep Spiking Neural Networks by Limiting Spiking Activity via Attention-Guided Compression WACV 2021 Stateful ODE-Nets using Basis Function Expansions NeurIPS 2021 Step-Ahead Error Feedback for Distributed Training with Compressed Gradient AAAI 2021 Stochastic Precision Ensemble: Self-Knowledge Distillation for Quantized Deep Neural Networks AAAI 2021 Student Customized Knowledge Distillation: Bridging the Gap Between Student and Teacher ICCV 2021 Sub-Bit Neural Networks: Learning To Compress and Accelerate Binary Neural Networks ICCV 2021