Efficient Computing

Learning Filter Basis for Convolutional Neural Network Compression ICCV 2019 Learning Fully Dense Neural Networks for Image Semantic Segmentation AAAI 2019 Learning Generalizable Device Placement Algorithms for Distributed Machine Learning NeurIPS 2019 Learning Instance-wise Sparsity for Accelerating Deep Models IJCAI 2019 Learning Recurrent Binary/Ternary Weights ICLR 2019 Learning to Localize Through Compressed Binary Maps CVPR 2019 Learning to Quantize Deep Networks by Optimizing Quantization Intervals With Task Loss CVPR 2019 Learning to Sample CVPR 2019 Learning To Simulate ICLR 2019 LegoNet: Efficient Convolutional Neural Networks with Lego Filters ICML 2019 Lightweight and Efficient Neural Natural Language Processing with Quaternion Networks ACL 2019 LiteEval: A Coarse-to-Fine Framework for Resource Efficient Video Recognition NeurIPS 2019 LIT: Learned Intermediate Representation Training for Model Compression ICML 2019 Loom: Flexible and Efficient NIC Packet Scheduling NSDI 2019 Low-Bit Quantization for Attributed Network Representation Learning IJCAI 2019 Low-Dimensional Bottleneck Features for On-Device Continuous Speech Recognition Interspeech 2019 Low Latency Privacy Preserving Inference ICML 2019 Making AI Forget You: Data Deletion in Machine Learning NeurIPS 2019 MBS: Macroblock Scaling for CNN Model Reduction CVPR 2019 Memory Efficient Adaptive Optimization NeurIPS 2019 Memory-Optimal Direct Convolutions for Maximizing Classification Accuracy in Embedded Applications ICML 2019 MetaPruning: Meta Learning for Automatic Neural Network Channel Pruning ICCV 2019 MnasNet: Platform-Aware Neural Architecture Search for Mobile CVPR 2019 Model-Agnostic and Efficient Exploration of Numerical State Space of Real-World TCP Congestion Control Implementations NSDI 2019 Model Compression with Adversarial Robustness: A Unified Optimization Framework NeurIPS 2019