Search Results for author:
Found 11 papers, 1 papers with code
Rank Subspace Learning for Compact Hash Codes
In this work, we propose a novel hash learning framework that encodes feature's rank orders instead of numeric values in a number of optimal low-dimensional ranking subspaces.
First-Take-All: Temporal Order-Preserving Hashing for 3D Action Videos
With the prevalence of the commodity depth cameras, the new paradigm of user interfaces based on 3D motion capturing and recognition have dramatically changed the way of interactions between human and computers.
Deep Differential Recurrent Neural Networks
The proposed model progressively builds up the ability of the LSTM gates to detect salient dynamical patterns in deeper stacked layers modeling higher orders of DoS, and thus the proposed LSTM model is termed deep differential Recurrent Neural Network (d2RNN).
Toward Extractive Summarization of Online Forum Discussions via Hierarchical Attention Networks
Forum threads are lengthy and rich in content.
Deep Segment Hash Learning for Music Generation
Music generation research has grown in popularity over the past decade, thanks to the deep learning revolution that has redefined the landscape of artificial intelligence.
Syntactic Recurrent Neural Network for Authorship Attribution
In this paper, we introduce a syntactic recurrent neural network to encode the syntactic patterns of a document in a hierarchical structure.
Differential Recurrent Neural Network and its Application for Human Activity Recognition
The Long Short-Term Memory (LSTM) recurrent neural network is capable of processing complex sequential information since it utilizes special gating schemes for learning representations from long input sequences.
Style-aware Neural Model with Application in Authorship Attribution
Writing style is a combination of consistent decisions associated with a specific author at different levels of language production, including lexical, syntactic, and structural.
Attention Based Neural Architecture for Rumor Detection with Author Context Awareness
The prevalence of social media has made information sharing possible across the globe.
A Self-supervised Representation Learning of Sentence Structure for Authorship Attribution
Due to the n-to-1 mapping of words to their structural labels, each word will be embedded into a vector representation which mainly carries structural information.
Improving Online Forums Summarization via Hierarchical Unified Deep Neural Network
In this scheme, Bi-LSTM derives a representation that comprises information of the whole sentence and whole thread; whereas, CNN captures most informative features with respect to context from sentence and thread.
