20 citations · 48 across the 11 of their papers we have counts for
14 papers · 1 filter
Model-Free Robust Average-Reward Reinforcement Learning
Yue Wang, Alvaro Velasquez, George Atia +2
Robust Markov decision processes (MDPs) address the challenge of model uncertainty by optimizing the worst-case performance over an uncertainty set of MDPs. In this paper, we focus…
Scalable and Robust Tensor Ring Decomposition for Large-scale Data
Yicong He, George K. Atia
Tensor ring (TR) decomposition has recently received increased attention due to its superior expressive performance for high-order tensors. However, the applicability of traditiona…
Robust Average-Reward Markov Decision Processes
Yue Wang, Alvaro Velasquez, George Atia +2
In robust Markov decision processes (MDPs), the uncertainty in the transition kernel is addressed by finding a policy that optimizes the worst-case performance over an uncertainty…
On the Robustness of AlphaFold: A COVID-19 Case Study
Ismail Alkhouri, Sumit Jha, Andre Beckus +5
Protein folding neural networks (PFNNs) such as AlphaFold predict remarkably accurate structures of proteins compared to other approaches. However, the robustness of such networks…
A Differentiable Approach to Combinatorial Optimization using Dataless Neural Networks
Ismail R. Alkhouri, George K. Atia, Alvaro Velasquez
The success of machine learning solutions for reasoning about discrete structures has brought attention to its adoption within combinatorial optimization algorithms. Such approache…
BOSS: Bidirectional One-Shot Synthesis of Adversarial Examples
Ismail R. Alkhouri, Alvaro Velasquez, George K. Atia
The design of additive imperceptible perturbations to the inputs of deep classifiers to maximize their misclassification rates is a central focus of adversarial machine learning. A…