Text classification improved by integrating bidirectional LSTM with two-dimensional max pooling
Recurrent Neural Network (RNN) is one of the most popular architectures used in Natural
Language Processsing (NLP) tasks because its recurrent structure is very suitable to process …
Language Processsing (NLP) tasks because its recurrent structure is very suitable to process …
Achieving exact cluster recovery threshold via semidefinite programming
The binary symmetric stochastic block model deals with a random graph of n vertices partitioned
into two equal-sized clusters, such that each pair of vertices is independently connected …
into two equal-sized clusters, such that each pair of vertices is independently connected …
Distributed statistical machine learning in adversarial settings: Byzantine gradient descent
We consider the distributed statistical learning problem over decentralized systems that are
prone to adversarial attacks. This setup arises in many practical applications, including …
prone to adversarial attacks. This setup arises in many practical applications, including …
Semantic expansion using word embedding clustering and convolutional neural network for improving short text classification
Text classification can help users to effectively handle and exploit useful information hidden
in large-scale documents. However, the sparsity of data and the semantic sensitivity to …
in large-scale documents. However, the sparsity of data and the semantic sensitivity to …
Joint entity and relation extraction based on a hybrid neural network
S Zheng, Y Hao, D Lu, H Bao, J Xu, H Hao, B Xu - Neurocomputing, 2017 - Elsevier
Entity and relation extraction is a task that combines detecting entity mentions and recognizing
entities’ semantic relationships from unstructured text. We propose a hybrid neural …
entities’ semantic relationships from unstructured text. We propose a hybrid neural …
Review of CRISPR/Cas9 sgRNA design tools
The adaptive immunity system in bacteria and archaea, Clustered Regularly Interspaced
Short Palindromic Repeats, CRISPR-associate (CRISPR/Cas), has been adapted as a …
Short Palindromic Repeats, CRISPR-associate (CRISPR/Cas), has been adapted as a …
[PDF][PDF] Semantic clustering and convolutional neural network for short text categorization
Short texts usually encounter data sparsity and ambiguity problems in representations for
their lack of context. In this paper, we propose a novel method to model short texts based on …
their lack of context. In this paper, we propose a novel method to model short texts based on …
Self-taught convolutional neural networks for short text clustering
J Xu, B Xu, P Wang, S Zheng, G Tian, J Zhao - Neural Networks, 2017 - Elsevier
Short text clustering is a challenging problem due to its sparseness of text representation.
Here we propose a flexible Self-Taught Convolutional neural network framework for Short Text …
Here we propose a flexible Self-Taught Convolutional neural network framework for Short Text …
[PDF][PDF] Short text clustering via convolutional neural networks
J Xu, P Wang, G Tian, B Xu, J Zhao… - Proceedings of the 1st …, 2015 - aclanthology.org
Short text clustering has become an increasing important task with the popularity of social
media, and it is a challenging problem due to its sparseness of text representation. In this …
media, and it is a challenging problem due to its sparseness of text representation. In this …
Paleoclimatic interpretation of the past 30 ka from isotopic studies of the deep confined aquifer of the North China plain
C Zongyu, Q Jixiang, X Jianming, X Jiaming, Y Hao… - Applied …, 2003 - Elsevier
The δ 18 O and δD values in the deep confined aquifer beneath the North China Plain
which is located at 11230′E–11930′E and 3446′N–4025′N, reflect differences in …
which is located at 11230′E–11930′E and 3446′N–4025′N, reflect differences in …