9 citations · 21 across the 9 of their papers we have counts for
10 papers
Load Disaggregation under Incomplete Inventory with Structured Unclaimed Demand
Saman Mostafavi, Robert W. Cox
An incomplete inventory creates a specific attribution ambiguity in load disaggregation: unclaimed demand can offset changes in claimed loads without altering meter reconstruction.…
Visualization of Mobility Digital Twin: Framework Design, Case Study, and Future Challenges
Yueyang Liu, Xiaolong Tu, Dawei Chen +4
A Mobility Digital Twin is an emerging implementation of digital twin technology in the transportation domain, which creates digital replicas for various physical mobility entities…
Continual Learning as Computationally Constrained Reinforcement Learning
Saurabh Kumar, Henrik Marklund, Ashish Rao +4
An agent that efficiently accumulates knowledge to develop increasingly sophisticated skills over a long lifetime could advance the frontier of artificial intelligence capabilities…
A Semi-Supervised Framework for Misinformation Detection
Yueyang Liu, Zois Boukouvalas, Nathalie Japkowicz
The spread of misinformation in social media outlets has become a prevalent societal problem and is the cause of many kinds of social unrest. Curtailing its prevalence is of great…
A Definition of Non-Stationary Bandits
Yueyang Liu, Xu Kuang, Benjamin Van Roy
Despite the subject of non-stationary bandit learning having attracted much recent attention, we have yet to identify a formal definition of non-stationarity that can consistently…
Brain Model State Space Reconstruction Using an LSTM Neural Network
Yueyang Liu, Artemio Soto-Breceda, Yun Zhao +5
Objective Kalman filtering has previously been applied to track neural model states and parameters, particularly at the scale relevant to EEG. However, this approach lacks a reliab…
Non-Stationary Bandit Learning via Predictive Sampling
Yueyang Liu, Xu Kuang, Benjamin Van Roy
Thompson sampling has proven effective across a wide range of stationary bandit environments. However, as we demonstrate in this paper, it can perform poorly when applied to non-st…
Gaussian Imagination in Bandit Learning
Yueyang Liu, Adithya M. Devraj, Benjamin Van Roy +1
Assuming distributions are Gaussian often facilitates computations that are otherwise intractable. We study the performance of an agent that attains a bounded information ratio wit…
Robust Convergence in Federated Learning through Label-wise Clustering
Hunmin Lee, Yueyang Liu, Donghyun Kim +1
Non-IID dataset and heterogeneous environment of the local clients are regarded as a major issue in Federated Learning (FL), causing a downturn in the convergence without achieving…
AED: An black-box NLP classifier model attacker
Yueyang Liu, Yan Huang, Zhipeng Cai
Deep Neural Networks (DNNs) have been successful in solving real-world tasks in domains such as connected and automated vehicles, disease, and job hiring. However, their implicatio…