221 citations · 1k across the 45 of their papers we have counts for
50 papers
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…
Distributionally Robust Domain Adaptation
Akram S. Awad, George K. Atia
Domain Adaptation (DA) has recently received significant attention due to its potential to adapt a learning model across source and target domains with mismatched distributions. Si…
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…
Support Recovery of Periodic Mixtures with Nested Periodic Dictionaries
Pouria Saidi, George K. Atia
Periodic signals composed of periodic mixtures admit sparse representations in nested periodic dictionaries (NPDs). Therefore, their underlying hidden periods can be estimated by r…
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…
Inferring Probabilistic Reward Machines from Non-Markovian Reward Processes for Reinforcement Learning
Taylor Dohmen, Noah Topper, George Atia +3
The success of reinforcement learning in typical settings is predicated on Markovian assumptions on the reward signal by which an agent learns optimal policies. In recent years, th…
Coarse to Fine Two-Stage Approach to Robust Tensor Completion of Visual Data
Yicong He, George K. Atia
Tensor completion is the problem of estimating the missing values of high-order data from partially observed entries. Data corruption due to prevailing outliers poses major challen…
Controller Synthesis for Omega-Regular and Steady-State Specifications
Alvaro Velasquez, Ismail Alkhouri, Andre Beckus +2
Given a Markov decision process (MDP) and a linear-time (-regular or LTL) specification, the controller synthesis problem aims to compute the optimal policy that satisfies the s…
Patch Tracking-based Streaming Tensor Ring Completion for Visual Data Recovery
Yicong He, George K. Atia
Tensor completion aims to recover the missing entries of a partially observed tensor by exploiting its low-rank structure, and has been applied to visual data recovery. In applicat…
Steady-State Planning in Expected Reward Multichain MDPs
George K. Atia, Andre Beckus, Ismail Alkhouri +1
The planning domain has experienced increased interest in the formal synthesis of decision-making policies. This formal synthesis typically entails finding a policy which satisfies…
Robust Low-tubal-rank Tensor Completion based on Tensor Factorization and Maximum Correntopy Criterion
Yicong He, George K. Atia
The goal of tensor completion is to recover a tensor from a subset of its entries, often by exploiting its low-rank property. Among several useful definitions of tensor rank, the l…
Sketch-based community detection in evolving networks
Andre Beckus, George K. Atia
We consider an approach for community detection in time-varying networks. At its core, this approach maintains a small sketch graph to capture the essential community structure fou…
A Multi-criteria Approach for Fast and Outlier-aware Representative Selection from Manifolds
Mahlagha Sedghi, George Atia, Michael Georgiopoulos
The problem of representative selection amounts to sampling few informative exemplars from large datasets. This paper presents MOSAIC, a novel representative selection approach fro…
What is the maximum differential group delay achievable by a space-time wave packet in free space?
Murat Yessenov, Lam Mach, Basanta Bhaduri +5
The group velocity of 'space-time' wave packets propagation-invariant pulsed beams endowed with tight spatio-temporal spectral correlations can take on arbitrary values in…
Rediscovering Deep Neural Networks Through Finite-State Distributions
Amir Emad Marvasti, Ehsan Emad Marvasti, George Atia +1
We propose a new way of thinking about deep neural networks, in which the linear and non-linear components of the network are naturally derived and justified in terms of principles…
Interferometry-based modal analysis with finite aperture effects
Davood Mardani, Ayman F. Abouraddy, George K. Atia
We analyze the effects of aperture finiteness on interferograms recorded to unveil the modal content of optical beams in arbitrary basis using generalized interferometry. We develo…
Multi-modal Non-line-of-sight Passive Imaging
Andre Beckus, Alexandru Tamasan, George K. Atia
We consider the non-line-of-sight (NLOS) imaging of an object using the light reflected off a diffusive wall. The wall scatters incident light such that a lens is no longer useful…
Scalable and Robust Community Detection with Randomized Sketching
Mostafa Rahmani, Andre Beckus, Adel Karimian +1
This article explores and analyzes the unsupervised clustering of large partially observed graphs. We propose a scalable and provable randomized framework for clustering graphs gen…
A Game-Theoretic Framework for the Virtual Machines Migration Timing Problem
Ahmed H. Anwar, George Atia, Mina Guirguis
In a multi-tenant cloud, a number of Virtual Machines (VMs) are collocated on the same physical machine to optimize performance, power consumption and maximize profit. This, howeve…
On the inverse problem of source reconstruction from coherence measurements
Andre Beckus, Alexandru Tamasan, Aristide Dogariu +2
We consider an inverse source problem for partially coherent light propagating in the Fresnel regime. The data is the coherence of the field measured away from the source. The reco…
Detection of Brain Stimuli Using Ramanujan Periodicity Transforms
Pouria Saidi, Azadeh Vosoughi, George Atia
The ability to efficiently match the frequency of the brain's response to repetitive visual stimuli in real time is the basis for reliable SSVEP-based Brain-Computer-Interfacing (B…