1.2k citations · 9.1k across the 205 of their papers we have counts for
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Learning Better Word Embedding by Asymmetric Low-Rank Projection of Knowledge Graph
Fei Tian, Bin Gao, Enhong Chen +1
Word embedding, which refers to low-dimensional dense vector representations of natural words, has demonstrated its power in many natural language processing tasks. However, it may…
On the Depth of Deep Neural Networks: A Theoretical View
Shizhao Sun, Wei Chen, Liwei Wang +2
People believe that depth plays an important role in success of deep neural networks (DNN). However, this belief lacks solid theoretical justifications as far as we know. We invest…
Solving Verbal Comprehension Questions in IQ Test by Knowledge-Powered Word Embedding
Huazheng Wang, Fei Tian, Bin Gao +2
Intelligence Quotient (IQ) Test is a set of standardized questions designed to evaluate human intelligence. Verbal comprehension questions appear very frequently in IQ tests, which…
Thompson Sampling for Budgeted Multi-armed Bandits
Yingce Xia, Haifang Li, Tao Qin +2
Thompson sampling is one of the earliest randomized algorithms for multi-armed bandits (MAB). In this paper, we extend the Thompson sampling to Budgeted MAB, where there is random…