Distribution-Flexible Subset Quantization for Post-Quantizing Super-Resolution Networks

1 code implementation • 10 May 2023 • Yunshan Zhong, Mingbao Lin, Jingjing Xie, Yuxin Zhang, Fei Chao, Rongrong Ji

Compared to the common iterative exhaustive search algorithm, our strategy avoids the enumeration of all possible combinations in the universal set, reducing the time complexity from exponential to linear.

Quantization Super-Resolution

Bi-directional Masks for Efficient N:M Sparse Training

1 code implementation • 13 Feb 2023 • Yuxin Zhang, Yiting Luo, Mingbao Lin, Yunshan Zhong, Jingjing Xie, Fei Chao, Rongrong Ji

We focus on addressing the dense backward propagation issue for training efficiency of N:M fine-grained sparsity that preserves at most N out of M consecutive weights and achieves practical speedups supported by the N:M sparse tensor core.

Challenges in Representation Learning: A report on three machine learning contests

11 code implementations • 1 Jul 2013 • Ian J. Goodfellow, Dumitru Erhan, Pierre Luc Carrier, Aaron Courville, Mehdi Mirza, Ben Hamner, Will Cukierski, Yichuan Tang, David Thaler, Dong-Hyun Lee, Yingbo Zhou, Chetan Ramaiah, Fangxiang Feng, Ruifan Li, Xiaojie Wang, Dimitris Athanasakis, John Shawe-Taylor, Maxim Milakov, John Park, Radu Ionescu, Marius Popescu, Cristian Grozea, James Bergstra, Jingjing Xie, Lukasz Romaszko, Bing Xu, Zhang Chuang, Yoshua Bengio

The ICML 2013 Workshop on Challenges in Representation Learning focused on three challenges: the black box learning challenge, the facial expression recognition challenge, and the multimodal learning challenge.

BIG-bench Machine Learning Facial Expression Recognition +2

Horizontal and Vertical Ensemble with Deep Representation for Classification

no code implementations • 12 Jun 2013 • Jingjing Xie, Bing Xu, Zhang Chuang

Representation learning, especially which by using deep learning, has been widely applied in classification.

Classification General Classification +1