6 citations · 11 across the 4 of their papers we have counts for
7 papers
Graph-Driven Generative Models for Heterogeneous Multi-Task Learning
Wenlin Wang, Hongteng Xu, Zhe Gan +6
We propose a novel graph-driven generative model, that unifies multiple heterogeneous learning tasks into the same framework. The proposed model is based on the fact that heterogen…
Learning to Recommend from Sparse Data via Generative User Feedback
Wenlin Wang, Hongteng Xu, Ruiyi Zhang +3
Traditional collaborative filtering (CF) based recommender systems tend to perform poorly when the user-item interactions/ratings are highly scarce. To address this, we propose a l…
Zero-Shot Recognition via Optimal Transport
Wenlin Wang, Hongteng Xu, Guoyin Wang +2
We propose an optimal transport (OT) framework for generalized zero-shot learning (GZSL), seeking to distinguish samples for both seen and unseen classes, with the assist of auxili…
Synthetic Data Generation and Adaption for Object Detection in Smart Vending Machines
Kai Wang, Fuyuan Shi, Wenqi Wang +2
This paper presents an improved scheme for the generation and adaption of synthetic images for the training of deep Convolutional Neural Networks(CNNs) to perform the object detect…
Wide Compression: Tensor Ring Nets
Wenqi Wang, Yifan Sun, Brian Eriksson +2
Deep neural networks have demonstrated state-of-the-art performance in a variety of real-world applications. In order to obtain performance gains, these networks have grown larger…
Efficient Low Rank Tensor Ring Completion
Wenqi Wang, Vaneet Aggarwal, Shuchin Aeron
Using the matrix product state (MPS) representation of the recently proposed tensor ring decompositions, in this paper we propose a tensor completion algorithm, which is an alterna…