Model Compression

Knowledge Extraction with No Observable Data NeurIPS 2019 Knowledge Transfer via Distillation of Activation Boundaries Formed by Hidden Neurons AAAI 2019 Learnable Embedding Space for Efficient Neural Architecture Compression ICLR 2019 Learning Compact Model for Large-Scale Multi-Label Data AAAI 2019 Learning Compact Models for Planning with Exogenous Processes CoRL 2019 Learning Compressed Sentence Representations for On-Device Text Processing ACL 2019 Learning Low-precision Neural Networks without Straight-Through Estimator (STE) IJCAI 2019 Learning Without Memorizing CVPR 2019 MEAL: Multi-Model Ensemble via Adversarial Learning AAAI 2019 MetaQuant: Learning to Quantize by Learning to Penetrate Non-differentiable Quantization NeurIPS 2019 MonoForest framework for tree ensemble analysis NeurIPS 2019 Near-Lossless Binarization of Word Embeddings AAAI 2019 Network Recasting: A Universal Method for Network Architecture Transformation AAAI 2019 Neural Network Distillation on IoT Platforms for Sound Event Detection Interspeech 2019 Normalization Helps Training of Quantized LSTM NeurIPS 2019 On-device Structured and Context Partitioned Projection Networks ACL 2019 One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers NeurIPS 2019 On the Downstream Performance of Compressed Word Embeddings NeurIPS 2019 Overcoming Multi-model Forgetting ICML 2019 Patient Knowledge Distillation for BERT Model Compression EMNLP 2019 Private Model Compression via Knowledge Distillation AAAI 2019 Quantization Networks CVPR 2019 Regularizing Activation Distribution for Training Binarized Deep Networks CVPR 2019 RNN Architecture Learning with Sparse Regularization EMNLP 2019 Robust Text Classifier on Test-Time Budgets EMNLP 2019