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Efficient Computing

1253 directly classified papers

Papers per year

Papers

Privacy Amplification via Random Check-Ins NIPS 2020
Robust Quantization: One Model to Rule Them All NIPS 2020
Structured Convolutions for Efficient Neural Network Design NIPS 2020
Revisiting Parameter Sharing for Automatic Neural Channel Number Search NIPS 2020
SMYRF - Efficient Attention using Asymmetric Clustering NIPS 2020
Exactly Computing the Local Lipschitz Constant of ReLU Networks NIPS 2020
Once-for-All Adversarial Training: In-Situ Tradeoff between Robustness and Accuracy for Free NIPS 2020
Nimble: Lightweight and Parallel GPU Task Scheduling for Deep Learning NIPS 2020
Glyph: Fast and Accurately Training Deep Neural Networks on Encrypted Data NIPS 2020
Stochastic Optimization with Laggard Data Pipelines NIPS 2020
FracTrain: Fractionally Squeezing Bit Savings Both Temporally and Spatially for Efficient DNN Training NIPS 2020
Accelerating Training of Transformer-Based Language Models with Progressive Layer Dropping NIPS 2020
NanoFlow: Scalable Normalizing Flows with Sublinear Parameter Complexity NIPS 2020
Kernel Methods Through the Roof: Handling Billions of Points Efficiently NIPS 2020
AdaTune: Adaptive Tensor Program Compilation Made Efficient NIPS 2020
Efficient Algorithms for Device Placement of DNN Graph Operators NIPS 2020
Sparse Weight Activation Training NIPS 2020
SAC: Accelerating and Structuring Self-Attention via Sparse Adaptive Connection NIPS 2020
BERT Loses Patience: Fast and Robust Inference with Early Exit NIPS 2020
What if Neural Networks had SVDs? NIPS 2020
Efficient Learning of Generative Models via Finite-Difference Score Matching NIPS 2020
Streaming Batch Gradient Tracking for Neural Network Training (Student Abstract) AAAI 2020
FASTER Recurrent Networks for Efficient Video Classification AAAI 2020
Patch Proposal Network for Fast Semantic Segmentation of High-Resolution Images AAAI 2020
Sparsity-Inducing Binarized Neural Networks AAAI 2020