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Efficient Computing

1253 directly classified papers

Papers per year

Papers

A Lightweight Recurrent Network for Sequence Modeling ACL 2019
Neural Shuffle-Exchange Networks - Sequence Processing in O(n log n) Time NIPS 2019
AutoFocus: Efficient Multi-Scale Inference ICCV 2019
On-device Structured and Context Partitioned Projection Networks ACL 2019
Real-Time Open-Domain Question Answering with Dense-Sparse Phrase Index ACL 2019
SSN: Learning Sparse Switchable Normalization via SparsestMax CVPR 2019
Learning Channel-Wise Interactions for Binary Convolutional Neural Networks CVPR 2019
Flambé: A Customizable Framework for Machine Learning Experiments ACL 2019
HAQ: Hardware-Aware Automated Quantization With Mixed Precision CVPR 2019
Adaptive Ensemble Prediction for Deep Neural Networks based on Confidence Level AISTATS 2019
Decoders Matter for Semantic Segmentation: Data-Dependent Decoding Enables Flexible Feature Aggregation CVPR 2019
All You Need Is a Few Shifts: Designing Efficient Convolutional Neural Networks for Image Classification CVPR 2019
HetConv: Heterogeneous Kernel-Based Convolutions for Deep CNNs CVPR 2019
Deeper and Wider Siamese Networks for Real-Time Visual Tracking CVPR 2019
Reversible GANs for Memory-Efficient Image-To-Image Translation CVPR 2019
Memory Efficient Adaptive Optimization NIPS 2019
You Only Propagate Once: Accelerating Adversarial Training via Maximal Principle NIPS 2019
Coresets for Clustering with Fairness Constraints NIPS 2019
E2-Train: Training State-of-the-art CNNs with Over 80% Energy Savings NIPS 2019
Hybrid 8-bit Floating Point (HFP8) Training and Inference for Deep Neural Networks NIPS 2019
Focused Quantization for Sparse CNNs NIPS 2019
High-Dimensional Optimization in Adaptive Random Subspaces NIPS 2019
Understanding Sparse JL for Feature Hashing NIPS 2019
Communication-Efficient Distributed Learning via Lazily Aggregated Quantized Gradients NIPS 2019
More Is Less: Learning Efficient Video Representations by Big-Little Network and Depthwise Temporal Aggregation NIPS 2019