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Efficient Computing

1253 directly classified papers

Papers per year

Papers

Training Deep Neural Networks with 8-bit Floating Point Numbers NIPS 2018
ATOMO: Communication-efficient Learning via Atomic Sparsification NIPS 2018
Navigating with Graph Representations for Fast and Scalable Decoding of Neural Language Models NIPS 2018
Mesh-TensorFlow: Deep Learning for Supercomputers NIPS 2018
Communication Compression for Decentralized Training NIPS 2018
An intriguing failing of convolutional neural networks and the CoordConv solution NIPS 2018
Training DNNs with Hybrid Block Floating Point NIPS 2018
Faster Neural Networks Straight from JPEG NIPS 2018
Learning to Optimize Tensor Programs NIPS 2018
Adaptive Methods for Nonconvex Optimization NIPS 2018
Constructing Fast Network through Deconstruction of Convolution NIPS 2018
Frequency-Domain Dynamic Pruning for Convolutional Neural Networks NIPS 2018
FastGRNN: A Fast, Accurate, Stable and Tiny Kilobyte Sized Gated Recurrent Neural Network NIPS 2018
GradiVeQ: Vector Quantization for Bandwidth-Efficient Gradient Aggregation in Distributed CNN Training NIPS 2018
Gather-Excite: Exploiting Feature Context in Convolutional Neural Networks NIPS 2018
BML: A High-performance, Low-cost Gradient Synchronization Algorithm for DML Training NIPS 2018
Learning Time/Memory-Efficient Deep Architectures With Budgeted Super Networks CVPR 2018
Link and Code: Fast Indexing With Graphs and Compact Regression Codes CVPR 2018
Efficient Large-Scale Approximate Nearest Neighbor Search on OpenCL FPGA CVPR 2018
Seeing Small Faces From Robust Anchor's Perspective CVPR 2018
Low-Latency Video Semantic Segmentation CVPR 2018
MegDet: A Large Mini-Batch Object Detector CVPR 2018
Dynamic Zoom-In Network for Fast Object Detection in Large Images CVPR 2018
Selective Classification for Deep Neural Networks NIPS 2017
QSGD: Communication-Efficient SGD via Gradient Quantization and Encoding NIPS 2017