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CORPUS.txt
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Efficient Processing of Deep Neural Networks- A Tutorial and Survey.txt
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2020-08-07 13:58:04 -06:00 |
EfficientNet Rethinking Model Scaling for Convolutional Neural Networks.txt
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Energy and Policy Considerations for Deep Learning in NLP - Emma Strubell.txt
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Finite-Element Neural Networks for Solving Differential Equations.txt
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Floating Point Operations in Matrix-Vector Calculus.txt
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Green AI - Roy Schwartz.txt
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Harnessing Nonlinearity Predicting Chaotic Systems and Saving Energy.txt
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Identity Mappings in Deep Residual Networks.txt
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Language Models are Few-Shot Learners.txt
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Learning Efficient Convolutional Networks through Network Slimming - Zhuang Liu.txt
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Learning Structured Sparsity in Deep Neural Networks - Wei Wen.txt
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Learning both Weights and Connections for Efficient Neural Networks.txt
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Learning both Weights and Connections for Efficient Neural Networks - Song Han.txt
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Learning to Generalize.txt
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MIXED PRECISION TRAINING - Sharan Narang.txt
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MOGRIFIER LSTM.txt
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Model Compression and Acceleration for Deep Neural Networks - Yu Cheng.txt
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Movement Pruning Adaptive Sparsity by Fine-Tuning.txt
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Network Pruning notes.txt
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Network Trimming_ A Data-Driven Neuron Pruning Approach towards Efficient Deep Architectures.txt
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Optimal Brain - Le Cun.txt
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PLUG AND PLAY LANGUAGE MODELS.txt
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Predicting Performance for Natural Language Processing Tasks.txt
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Predicting trends in the quality of state-of-the-art neural networkswithout access to training or testing dat.txt
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Pruning neural networks without any databy iteratively conserving synaptic flow.txt
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Scalable Gradients for Stochastic Differential Equations.txt
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Scaling Laws for Neural Language Models.txt
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Structured Pruning of Convolutional Neural Networks via L1 Regularization - CHEN YANG.txt
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THE LOTTERY TICKET HYPOTHESIS.txt
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TOWARDS THE SYSTEMATIC REPORTING OF THE ENERGY AND CARBON FOOTPRINTS OF MACHINE LEARNING.txt
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2020-08-06 14:53:44 -06:00 |
The 4 Research Techniques to Train Deep Neural Network Models More Efficiently.txt
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The State of Sparsity in Deep Neural Networks - Trevor Gale.txt
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Tien-Ju_Yang_NetAdapt_Platform-Aware_Neural_ECCV_2018_paper.txt
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2020-08-06 14:53:44 -06:00 |
You Cannot Improve What You Do not Measure FPGA vs. ASIC Efficiency Gaps for ConvolutionalNeural Network Inference.txt
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vDNN Virtualized Deep Neural Networks for Scalable Memory-Efficient Neural Network Design.txt
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