43 citations · 64 across the 9 of their papers we have counts for
10 papers
Robust Neural Regression via Uncertainty Learning
Akib Mashrur, Wei Luo, Nayyar A. Zaidi +1
Deep neural networks tend to underestimate uncertainty and produce overly confident predictions. Recently proposed solutions, such as MC Dropout and SDENet, require complex trainin…
Feature Extraction Functions for Neural Logic Rule Learning
Shashank Gupta, Antonio Robles-Kelly, Mohamed Reda Bouadjenek
Combining symbolic human knowledge with neural networks provides a rule-based ante-hoc explanation of the output. In this paper, we propose feature extracting functions for integra…
Toward a Deep Learning-Driven Intrusion Detection Approach for Internet of Things
Mengmeng Ge, Naeem Firdous Syed, Xiping Fu +2
Internet of Things (IoT) has brought along immense benefits to our daily lives encompassing a diverse range of application domains that we regularly interact with, ranging from hea…
Deep Patch-based Human Segmentation
Dongbo Zhang, Zheng Fang, Xuequan Lu +4
3D human segmentation has seen noticeable progress in re-cent years. It, however, still remains a challenge to date. In this paper, weintroduce a deep patch-based method for 3D hum…
Hierarchically Fair Federated Learning
Jingfeng Zhang, Cheng Li, Antonio Robles-Kelly +1
When the federated learning is adopted among competitive agents with siloed datasets, agents are self-interested and participate only if they are fairly rewarded. To encourage the…
Incorporating Expert Prior Knowledge into Experimental Design via Posterior Sampling
Cheng Li, Sunil Gupta, Santu Rana +3
Scientific experiments are usually expensive due to complex experimental preparation and processing. Experimental design is therefore involved with the task of finding the optimal…