113 citations · 1.1k across the 69 of their papers we have counts for
8 papers · 1 filter
Discrete Auto-regressive Variational Attention Models for Text Modeling
Xianghong Fang, Haoli Bai, Jian Li +3
Variational autoencoders (VAEs) have been widely applied for text modeling. In practice, however, they are troubled by two challenges: information underrepresentation and posterior…
Effective Data-aware Covariance Estimator from Compressed Data
Xixian Chen, Haiqin Yang, Shenglin Zhao +2
Estimating covariance matrix from massive high-dimensional and distributed data is significant for various real-world applications. In this paper, we propose a data-aware weighted…
Making Online Sketching Hashing Even Faster
Xixian Chen, Haiqin Yang, Shenglin Zhao +2
Data-dependent hashing methods have demonstrated good performance in various machine learning applications to learn a low-dimensional representation from the original data. However…
Discrete Variational Attention Models for Language Generation
Xianghong Fang, Haoli Bai, Zenglin Xu +2
Variational autoencoders have been widely applied for natural language generation, however, there are two long-standing problems: information under-representation and posterior col…
Few Shot Network Compression via Cross Distillation
Haoli Bai, Jiaxiang Wu, Irwin King +1
Model compression has been widely adopted to obtain light-weighted deep neural networks. Most prevalent methods, however, require fine-tuning with sufficient training data to ensur…
Detecting Deep Neural Network Defects with Data Flow Analysis
Jiazhen Gu, Huanlin Xu, Yangfan Zhou +3
Deep neural networks (DNNs) are shown to be promising solutions in many challenging artificial intelligence tasks. However, it is very hard to figure out whether the low precision…