1 citations · 3 across the 11 of their papers we have counts for
12 papers
Multi-Rate Mixture of Experts for Accelerating Liquid Neural Network Training
Shilong Zong, Almuatazbellah Boker, Hoda Eldardiry
Multivariate time-series data often exhibit complex temporal dependencies, irregular sampling, and heterogeneous dynamics across multiple time scales, making accurate sequence mode…
Alleviating Community Fear in Disasters via Multi-Agent Actor-Critic Reinforcement Learning
Yashodhan D. Hakke, Almuatazbellah M. Boker, Lamine Mili +2
During disasters, cascading failures across power grids, communication networks, and social behavior amplify community fear and undermine cooperation. Existing cyber-physical-socia…
A Multi-directional Meta-Learning Framework for Class-Generalizable Anomaly Detection
Padmaksha Roy, Lamine Mili, Almuatazbellah Boker
In this paper, we address the problem of class-generalizable anomaly detection, where the objective is to develop a unified model by focusing our learning on the available normal d…
Accuracy, Memory Efficiency and Generalization: A Comparative Study on Liquid Neural Networks and Recurrent Neural Networks
Shilong Zong, Alex Bierly, Almuatazbellah Boker +1
This review aims to conduct a comparative analysis of liquid neural networks (LNNs) and traditional recurrent neural networks (RNNs) and their variants, such as long short-term mem…
Beyond Marginals: Learning Joint Spatio-Temporal Patterns for Multivariate Anomaly Detection
Padmaksha Roy, Almuatazbellah Boker, Lamine Mili
In this paper, we aim to improve multivariate anomaly detection (AD) by modeling the \textit{time-varying non-linear spatio-temporal correlations} found in multivariate time series…
In Search of a Lost Metric: Human Empowerment as a Pillar of Socially Conscious Navigation
Vasanth Reddy Baddam, Behdad Chalaki, Vaishnav Tadiparthi +4
In social robot navigation, traditional metrics like proxemics and behavior naturalness emphasize human comfort and adherence to social norms but often fail to capture an agent's a…
Learning Emergence of Interaction Patterns across Independent RL Agents in Multi-Agent Environments
Vasanth Reddy Baddam, Suat Gumussoy, Almuatazbellah Boker +1
Many real-world problems, such as controlling swarms of drones and urban traffic, naturally lend themselves to modeling as multi-agent reinforcement learning (RL) problems. However…
Data-Driven Near-Optimal Control of Nonlinear Systems Over Finite Horizon
Vasanth Reddy, Hoda Eldardiry, Almuatazbellah Boker
We examine the problem of two-point boundary optimal control of nonlinear systems over finite-horizon time periods with unknown model dynamics by employing reinforcement learning.…
Identification of Power System Oscillation Modes using Blind Source Separation based on Copula Statistic
Pooja Algikar, Lamine Mili, Mohsen Ben Hassine +3
The dynamics of a power system with large penetration of renewable energy resources are becoming more nonlinear due to the intermittence of these resources and the switching of the…
Singular Perturbation-based Reinforcement Learning of Two-Point Boundary Optimal Control Systems
Vasanth Reddy, Hoda Eldardiry, Almuatazbellah Boker
This work presents a technique for learning systems, where the learning process is guided by knowledge of the physics of the system. In particular, we solve the problem of the two-…
Convergence Rates of Distributed Consensus over Cluster Networks: A Two-Time-Scale Approach
Amit Dutta, Almuatazbellah M. Boker, Thinh T. Doan
We study the popular distributed consensus method over networks composed of a number of densely connected clusters with a sparse connection between them. In these cluster networks,…
Semi-global Output Feedback Stabilization of Non-Minimum Phase Nonlinear Systems
Almuatazbellah M. Boker, Hassan K. Khalil
We solve the problem of output feedback stabilization of a class of nonlinear systems, which may have unstable zero dynamics. We allow for any globally stabilizing full state feedb…