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Efficient Computing

6876 directly classified papers

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Papers

Unconditional Coresets for Regularized Loss Minimization AISTATS 2020
Yolo4Apnea: Real-time Detection of Obstructive Sleep Apnea IJCAI 2020
Overflow Aware Quantization: Accelerating Neural Network Inference by Low-bit Multiply-Accumulate Operations IJCAI 2020
A Sequential Convolution Network for Population Flow Prediction with Explicitly Correlation Modelling IJCAI 2020
Coping With Simulators That Don’t Always Return AISTATS 2020
Fawkes: Faster Mobile Page Loads via App-Inspired Static Templating NSDI 2020
Why Are Learned Indexes So Effective? ICML 2020
Amortized Finite Element Analysis for Fast PDE-Constrained Optimization ICML 2020
CP-NAS: Child-Parent Neural Architecture Search for 1-bit CNNs IJCAI 2020
DropNAS: Grouped Operation Dropout for Differentiable Architecture Search IJCAI 2020
On the importance of pre-training data volume for compact language models EMNLP 2020
Instead of Rewriting Foreign Code for Machine Learning, Automatically Synthesize Fast Gradients NIPS 2020
Hyperparameter Ensembles for Robustness and Uncertainty Quantification NIPS 2020
Structured Convolutions for Efficient Neural Network Design NIPS 2020
Searching for Low-Bit Weights in Quantized Neural Networks NIPS 2020
Ultra-Low Precision 4-bit Training of Deep Neural Networks NIPS 2020
ExpandNets: Linear Over-parameterization to Train Compact Convolutional Networks NIPS 2020
Fixed-Point Back-Propagation Training CVPR 2020
Glance and Focus: a Dynamic Approach to Reducing Spatial Redundancy in Image Classification NIPS 2020
Re-Examining Linear Embeddings for High-Dimensional Bayesian Optimization NIPS 2020
Top-KAST: Top-K Always Sparse Training NIPS 2020
Model Rubik’s Cube: Twisting Resolution, Depth and Width for TinyNets NIPS 2020
Coded Sequential Matrix Multiplication For Straggler Mitigation NIPS 2020
Scalable Graph Neural Networks via Bidirectional Propagation NIPS 2020
Kernel Based Progressive Distillation for Adder Neural Networks NIPS 2020