activity
20162020
most citedNeural-Symbolic Computing: An Effective Methodology for Principled Integration of Machine Learning and Reasoning

99 citations · 113 across the 5 of their papers we have counts for

collaborators

8 papers

cs.CV20201 cited

Deep Auto-Encoders with Sequential Learning for Multimodal Dimensional Emotion Recognition

Dung Nguyen, Duc Thanh Nguyen, Rui Zeng +5

Multimodal dimensional emotion recognition has drawn a great attention from the affective computing community and numerous schemes have been extensively investigated, making a sign…

cs.CV2020

Joint Deep Cross-Domain Transfer Learning for Emotion Recognition

Dung Nguyen, Sridha Sridharan, Duc Thanh Nguyen +4

Deep learning has been applied to achieve significant progress in emotion recognition. Despite such substantial progress, existing approaches are still hindered by insufficient tra…

cs.CV20192 cited

Fashion Outfit Complementary Item Retrieval

Yen-Liang Lin, Son Tran, Larry S. Davis

Complementary fashion item recommendation is critical for fashion outfit completion. Existing methods mainly focus on outfit compatibility prediction but not in a retrieval setting…

cs.AI201999 cited

Neural-Symbolic Computing: An Effective Methodology for Principled Integration of Machine Learning and Reasoning

Artur d'Avila Garcez, Marco Gori, Luis C. Lamb +3

Current advances in Artificial Intelligence and machine learning in general, and deep learning in particular have reached unprecedented impact not only across research communities,…

cs.CL20196 cited

dpUGC: Learn Differentially Private Representation for User Generated Contents

Xuan-Son Vu, Son N. Tran, Lili Jiang

This paper firstly proposes a simple yet efficient generalized approach to apply differential privacy to text representation (i.e., word embedding). Based on it, we propose a user-…

cs.CL2019

ETNLP: a visual-aided systematic approach to select pre-trained embeddings for a downstream task

Xuan-Son Vu, Thanh Vu, Son N. Tran +1

Given many recent advanced embedding models, selecting pre-trained word embedding (a.k.a., word representation) models best fit for a specific downstream task is non-trivial. In th…