Workshop on Model Mining
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[2] Geoffrey E. Hinton,et al. Distilling the Knowledge in a Neural Network , 2015, ArXiv.
[3] Xiangyu Zhang,et al. ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design , 2018, ECCV.
[4] Changshui Zhang,et al. Agree to Disagree: Adaptive Ensemble Knowledge Distillation in Gradient Space , 2020, NeurIPS.
[5] Xiangyu Zhang,et al. Angle-based Search Space Shrinking for Neural Architecture Search , 2020, ECCV.
[6] Nikos Komodakis,et al. Paying More Attention to Attention: Improving the Performance of Convolutional Neural Networks via Attention Transfer , 2016, ICLR.
[7] Ming-Wei Chang,et al. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding , 2019, NAACL.
[8] Bernhard Schölkopf,et al. Unifying distillation and privileged information , 2015, ICLR.
[9] Fei Wang,et al. ISTA-NAS: Efficient and Consistent Neural Architecture Search by Sparse Coding , 2020, NeurIPS.
[10] Michael S. Bernstein,et al. ImageNet Large Scale Visual Recognition Challenge , 2014, International Journal of Computer Vision.
[11] Mark Chen,et al. Language Models are Few-Shot Learners , 2020, NeurIPS.
[12] Georg Heigold,et al. An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale , 2021, ICLR.
[13] Alok Aggarwal,et al. Regularized Evolution for Image Classifier Architecture Search , 2018, AAAI.
[14] Fei Wang,et al. Local Correlation Consistency for Knowledge Distillation , 2020, ECCV.
[15] H. Alzer. On the Cauchy-Schwarz Inequality☆ , 1999 .
[16] J. Schneider,et al. Literature survey on low rank approximation of matrices , 2017 .
[17] Chang Xu,et al. Learning Student Networks with Few Data , 2020, AAAI.
[18] Xiangyu Zhang,et al. Single Path One-Shot Neural Architecture Search with Uniform Sampling , 2019, ECCV.
[19] Natalia Gimelshein,et al. PyTorch: An Imperative Style, High-Performance Deep Learning Library , 2019, NeurIPS.