Anastasios Kyrillidis

Tensors for Data Mining and Data Fusion

A Unified Algorithmic Framework for Block-Structured Optimization Involving Big Data: With applications in machine learning and signal processing

Multidimensional compressed sensing and their applications

Tensor Decomposition for Signal Processing and Machine Learning

Model Compression and Hardware Acceleration for Neural Networks: A Comprehensive Survey

Variable Metric Forward–Backward Algorithm for Minimizing the Sum of a Differentiable Function and a Convex Function

Generative Street Addresses from Satellite Imagery

Theory of Quantum System Certification

A Tucker Deep Computation Model for Mobile Multimedia Feature Learning

Fully Scalable Methods for Distributed Tensor Factorization

Edge Artificial Intelligence for 6G: Vision, Enabling Technologies, and Applications

Tensor Decompositions for Signal Processing Applications: From two-way to multiway component analysis

DeepGlobe 2018: A Challenge to Parse the Earth through Satellite Images

Breaking the Curse of Dimensionality Using Decompositions of Incomplete Tensors: Tensor-based scientific computing in big data analysis

Memory-efficient parallel computation of tensor and matrix products for big tensor decomposition

Model-Free Quantum Control with Reinforcement Learning

Parallel Randomly Compressed Cubes : A scalable distributed architecture for big tensor decomposition

Convex Optimization for Big Data: Scalable, randomized, and parallel algorithms for big data analytics

Majorization-Minimization Algorithms in Signal Processing, Communications, and Machine Learning

Nonconvex Optimization Meets Low-Rank Matrix Factorization: An Overview

Low-rank regularization and solution uniqueness in over-parameterized matrix sensing.

Location Estimation Using Crowdsourced Spatial Relations

Randomized Singular Value Projection

Multi-Way Compressed Sensing for Sparse Low-Rank Tensors

Validating and certifying stabilizer states

Composite Self-Concordant Minimization