38 citations · 63 across the 7 of their papers we have counts for
8 papers
Cardinality-Regularized Hawkes-Granger Model
Tsuyoshi Idé, Georgios Kollias, Dzung T. Phan +1
We propose a new sparse Granger-causal learning framework for temporal event data. We focus on a specific class of point processes called the Hawkes process. We begin by pointing o…
Directed Graph Auto-Encoders
Georgios Kollias, Vasileios Kalantzis, Tsuyoshi Idé +2
We introduce a new class of auto-encoders for directed graphs, motivated by a direct extension of the Weisfeiler-Leman algorithm to pairs of node labels. The proposed model learns…
Projection techniques to update the truncated SVD of evolving matrices
Vassilis Kalantzis, Georgios Kollias, Shashanka Ubaru +3
This paper considers the problem of updating the rank-k truncated Singular Value Decomposition (SVD) of matrices subject to the addition of new rows and/or columns over time. Such…
Accelerating Physics-Based Simulations Using Neural Network Proxies: An Application in Oil Reservoir Modeling
Jiri Navratil, Alan King, Jesus Rios +3
We develop a proxy model based on deep learning methods to accelerate the simulations of oil reservoirs--by three orders of magnitude--compared to industry-strength physics-based P…
Low rank methods for multiple network alignment
Huda Nassar, Georgios Kollias, Ananth Grama +1
Multiple network alignment is the problem of identifying similar and related regions in a given set of networks. While there are a large number of effective techniques for pairwise…
Provably convergent acceleration in factored gradient descent with applications in matrix sensing
Tayo Ajayi, David Mildebrath, Anastasios Kyrillidis +3
We present theoretical results on the convergence of \emph{non-convex} accelerated gradient descent in matrix factorization models with -norm loss. The purpose of this work…
MXNET-MPI: Embedding MPI parallelism in Parameter Server Task Model for scaling Deep Learning
Amith R Mamidala, Georgios Kollias, Chris Ward +1
Existing Deep Learning frameworks exclusively use either Parameter Server(PS) approach or MPI parallelism. In this paper, we discuss the drawbacks of such approaches and propose a…
Spectral Efficient and Energy Aware Clustering in Cellular Networks
Georgios Kollias, Ferran Adelantado, Christos Verikoukis
The current and envisaged increase of cellular traffic poses new challenges to Mobile Network Operators (MNO), who must densify their Radio Access Networks (RAN) while maintaining…