Wen Tang

Works (7)

Updated: July 5th, 2023 14:44

2022 journal article

Deep transform and metric learning network: Wedding deep dictionary learning and neural network

NEUROCOMPUTING, 509, 244–256.

By: W. Tang n, E. Chouzenoux *, J. Pesquet * & H. Krim n

author keywords: Deep dictionary learning; Deep neural network; Metric learning; Transform learning; Proximal operator; Differentiable programming
TL;DR: A novel DDL approach where each DL layer can be formulated as a combination of one linear layer and a Recurrent Neural Network (RNN) is proposed, shown to flexibly account for the layer-associated and learned metric. (via Semantic Scholar)
Source: Web Of Science
Added: October 11, 2022

2022 journal article

Discovering urban functional zones from biased and sparse points of interests and sparse human activities

EXPERT SYSTEMS WITH APPLICATIONS, 207.

By: W. Tang n, A. Chakeri & H. Krim n

author keywords: Functional zones discovering; Latent region representation learning; Sparse and bias POIs; GPS data; Conditional random field clustering; Function annotation
TL;DR: The proposed framework to discover the real functional zones from the biased and extremely sparse Point of Interests (POIs) can better identify functional zones than the benchmarks, and enhance understanding of urban structures with a finer granularity under practical conditions. (via Semantic Scholar)
UN Sustainable Development Goals Color Wheel
UN Sustainable Development Goal Categories
11. Sustainable Cities and Communities (Web of Science; OpenAlex)
Source: Web Of Science
Added: August 8, 2022

2021 article

DEEP TRANSFORM AND METRIC LEARNING NETWORKS

2021 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP 2021), pp. 2735–2739.

By: W. Tang n, E. Chouzenoux, J. Pesquet * & H. Krim n

author keywords: Deep Dictionary Learning; Deep Neural Network; Metric Learning; Transform Learning; Proximal Operator; Differentiable Programming
TL;DR: This work proposes a novel Deep DL approach where each DL layer can be formulated and solved as a combination of one linear layer and a Recurrent Neural Network, where the RNN is flexibly regraded as a layer-associated learned metric. (via Semantic Scholar)
UN Sustainable Development Goals Color Wheel
UN Sustainable Development Goal Categories
4. Quality Education (OpenAlex)
Source: Web Of Science
Added: November 29, 2021

2020 journal article

Analysis of Network Effect in the Competition of Self- Publishing Market

JOURNAL OF THEORETICAL AND APPLIED ELECTRONIC COMMERCE RESEARCH, 15(3), 50–68.

By: L. Chen * & W. Tang n

author keywords: Self-publishing; Online publishing; Network effect; Compatibility strategy; Duopoly competition
TL;DR: A duopoly model to examine the impact of the network effect on competition in this emerging market shows that self-publishing writers receive higher royalties compared with the scenario of no network effect except in the case of both platforms choosing incompatibility strategy in the standard market. (via Semantic Scholar)
UN Sustainable Development Goals Color Wheel
UN Sustainable Development Goal Categories
Source: Web Of Science
Added: May 8, 2020

2019 journal article

Analysis Dictionary Learning Based Classification: Structure for Robustness

IEEE TRANSACTIONS ON IMAGE PROCESSING, 28(12), 6035–6046.

By: W. Tang n, A. Panahi n, H. Krim  n & L. Dai*

author keywords: Discriminate analysis dictionary learning; distributed analysis dictionary learning; structured mapping; supervised learning
TL;DR: A consensus structured analysis dictionary and a global classifier are jointly learned in the distributed approach to safeguard the discriminative power and the efficiency of classification. (via Semantic Scholar)
UN Sustainable Development Goals Color Wheel
UN Sustainable Development Goal Categories
10. Reduced Inequalities (OpenAlex)
Source: Web Of Science
Added: October 19, 2020

2016 conference paper

A topological collapse for document summarization

2016 IEEE 17th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), 2016-August.

By: H. Guan*, W. Tang*, H. Krim*, J. Keiser, A. Rindos* & R. Sazdanovic n 

Contributors: H. Guan*, W. Tang*, H. Krim*, J. Keiser, A. Rindos* & R. Sazdanovic n 

TL;DR: DoCollapse is proposed, a topological collapse-based unsupervised keyphrase extraction method that relies on networking document by semantic relatedness of candidate keyphrases to facilitate final keyphrase selection. (via Semantic Scholar)
Sources: NC State University Libraries, ORCID, NC State University Libraries
Added: August 6, 2018

2016 conference paper

Analysis dictionary learning for scene classification

2016 IEEE Statistical Signal Processing Workshop (SSP).

By: W. Tang n, I. Otero n, H. Krim n & L. Dai *

TL;DR: A supervised way to train the baseline representation for each class-specific dictionary, and achieve multiple classification by finding the minimum distance between the learned baseline representation and the data's sub-dictionary representation. (via Semantic Scholar)
Source: NC State University Libraries
Added: August 6, 2018

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