131 citations · 348 across the 18 of their papers we have counts for
18 papers
General-Purpose Multi-Modal OOD Detection Framework
Viet Duong, Qiong Wu, Zhengyi Zhou +5
Out-of-distribution (OOD) detection identifies test samples that differ from the training data, which is critical to ensuring the safety and reliability of machine learning (ML) sy…
Scalable Neural Symbolic Regression using Control Variables
Xieting Chu, Hongjue Zhao, Enze Xu +3
Symbolic regression (SR) is a powerful technique for discovering the analytical mathematical expression from data, finding various applications in natural sciences due to its good…
Condensed Prototype Replay for Class Incremental Learning
Jiangtao Kong, Zhenyu Zong, Tianyi Zhou +1
Incremental learning (IL) suffers from catastrophic forgetting of old tasks when learning new tasks. This can be addressed by replaying previous tasks' data stored in a memory, whi…
Balancing Privacy Protection and Interpretability in Federated Learning
Zhe Li, Honglong Chen, Zhichen Ni +1
Federated learning (FL) aims to collaboratively train the global model in a distributed manner by sharing the model parameters from local clients to a central server, thereby poten…
Pre-Training Representations of Binary Code Using Contrastive Learning
Yifan Zhang, Chen Huang, Yueke Zhang +3
Binary code analysis and comprehension is critical to applications in reverse engineering and computer security tasks where source code is not available. Unfortunately, unlike sour…
Phy-Taylor: Physics-Model-Based Deep Neural Networks
Yanbing Mao, Lui Sha, Huajie Shao +3
Purely data-driven deep neural networks (DNNs) applied to physical engineering systems can infer relations that violate physics laws, thus leading to unexpected consequences. To ad…
Unsupervised Belief Representation Learning with Information-Theoretic Variational Graph Auto-Encoders
Jinning Li, Huajie Shao, Dachun Sun +6
This paper develops a novel unsupervised algorithm for belief representation learning in polarized networks that (i) uncovers the latent dimensions of the underlying belief space a…
DyDiff-VAE: A Dynamic Variational Framework for Information Diffusion Prediction
Ruijie Wang, Zijie Huang, Shengzhong Liu +7
This paper describes a novel diffusion model, DyDiff-VAE, for information diffusion prediction on social media. Given the initial content and a sequence of forwarding users, DyDiff…
Controllable and Diverse Text Generation in E-commerce
Huajie Shao, Jun Wang, Haohong Lin +4
In E-commerce, a key challenge in text generation is to find a good trade-off between word diversity and accuracy (relevance) in order to make generated text appear more natural an…
Scheduling Real-time Deep Learning Services as Imprecise Computations
Shuochao Yao, Yifan Hao, Yiran Zhao +6
The paper presents an efficient real-time scheduling algorithm for intelligent real-time edge services, defined as those that perform machine intelligence tasks, such as voice reco…
ControlVAE: Tuning, Analytical Properties, and Performance Analysis
Huajie Shao, Zhisheng Xiao, Shuochao Yao +3
This paper reviews the novel concept of controllable variational autoencoder (ControlVAE), discusses its parameter tuning to meet application needs, derives its key analytic proper…
DynamicVAE: Decoupling Reconstruction Error and Disentangled Representation Learning
Huajie Shao, Haohong Lin, Qinmin Yang +3
This paper challenges the common assumption that the weight , in -VAE, should be larger than in order to effectively disentangle latent factors. We demonstrate that -V…
paper2repo: GitHub Repository Recommendation for Academic Papers
Huajie Shao, Dachun Sun, Jiahao Wu +7
GitHub has become a popular social application platform, where a large number of users post their open source projects. In particular, an increasing number of researchers release r…
ControlVAE: Controllable Variational Autoencoder
Huajie Shao, Shuochao Yao, Dachun Sun +5
Variational Autoencoders (VAE) and their variants have been widely used in a variety of applications, such as dialog generation, image generation and disentangled representation le…
Hierarchical Overlapping Belief Estimation by Structured Matrix Factorization
Chaoqi Yang, Jinyang Li, Ruijie Wang +6
Much work on social media opinion polarization focuses on a flat categorization of stances (or orthogonal beliefs) of different communities from media traces. We extend in this wor…
STFNets: Learning Sensing Signals from the Time-Frequency Perspective with Short-Time Fourier Neural Networks
Shuochao Yao, Ailing Piao, Wenjun Jiang +10
Recent advances in deep learning motivate the use of deep neural networks in Internet-of-Things (IoT) applications. These networks are modelled after signal processing in the human…
FastDeepIoT: Towards Understanding and Optimizing Neural Network Execution Time on Mobile and Embedded Devices
Shuochao Yao, Yiran Zhao, Huajie Shao +4
Deep neural networks show great potential as solutions to many sensing application problems, but their excessive resource demand slows down execution time, pausing a serious impedi…
RDeepSense: Reliable Deep Mobile Computing Models with Uncertainty Estimations
Shuochao Yao, Yiran Zhao, Huajie Shao +4
Recent advances in deep learning have led various applications to unprecedented achievements, which could potentially bring higher intelligence to a broad spectrum of mobile and ub…