150 citations · 200 across the 14 of their papers we have counts for
18 papers
Demonstrating Interoperable Channel State Feedback Compression with Machine Learning
Dani Korpi, Rachel Wang, Jerry Wang +20
Neural network-based compression and decompression of channel state feedback has been one of the most widely studied applications of machine learning (ML) in wireless networks. Var…
Fair Allocation in Crowd-Sourced Systems
Mishal Assif P K, William Kennedy, Iraj Saniee
In this paper, we address the problem of fair sharing of the total value of a crowd-sourced network system between major participants (founders) and minor participants (crowd) usin…
Efficient Deep Learning of GMMs
Shirin Jalali, Carl Nuzman, Iraj Saniee
We show that a collection of Gaussian mixture models (GMMs) in can be optimally classified using neurons in a neural network with two hidden layers (deep neural netw…
Linear Time Clustering for High Dimensional Mixtures of Gaussian Clouds
Dan Kushnir, Shirin Jalali, Iraj Saniee
Clustering mixtures of Gaussian distributions is a fundamental and challenging problem that is ubiquitous in various high-dimensional data processing tasks. While state-of-the-art…
A New Family of Near-metrics for Universal Similarity
Chu Wang, Iraj Saniee, William S. Kennedy +1
We propose a family of near-metrics based on local graph diffusion to capture similarity for a wide class of data sets. These quasi-metametrics, as their names suggest, dispense wi…
Quantifying the Benefits of Infrastructure Sharing
Matthew Andrews, Milan Bradonjic, Iraj Saniee
We analyze the benefits of network sharing between telecommunications operators. Sharing is seen as one way to speed the roll out of expensive technologies such as 5G since it allo…
Scaling of random walk betweenness in networks
O. Narayan, I. Saniee
The betweenness centrality of graphs using random walk paths instead of geodesics is studied. A scaling collapse with no adjustable parameters is obtained as the graph size is…
Fast approximation algorithms for -centres in large -hyperbolic graphs
Katherine Edwards, W. Sean Kennedy, Iraj Saniee
We provide a quasilinear time algorithm for the -center problem with an additive error less than or equal to 3 times the input graph's hyperbolic constant. Specifically, for the…
A Geometric Distance Oracle for Large Real-World Graphs
Deepak Ajwani, W. Sean Kennedy, Alessandra Sala +1
Many graph processing algorithms require determination of shortest-path distances between arbitrary numbers of node pairs. Since computation of exact distances between all node-pai…
Bootstrap Percolation on Periodic Trees
Milan Bradonjić, Iraj Saniee
We study bootstrap percolation with the threshold parameter and the initial probability on infinite periodic trees that are defined as follows. Each node of a tree ha…
Congestion Due to Random Walk Routing
Onuttom Narayan, Iraj Saniee, Vladimir Marbukh
In this paper we derive an analytical expression for the mean load at each node of an arbitrary undirected graph for the uniform multicommodity flow problem under random walk routi…
On the Hyperbolicity of Large-Scale Networks
W. Sean Kennedy, Onuttom Narayan, Iraj Saniee
Through detailed analysis of scores of publicly available data sets corresponding to a wide range of large-scale networks, from communication and road networks to various forms of…
Scaling of Congestion in Small World Networks
Iraj Saniee, Gabriel H. Tucci
In this report we show that in a planar exponentially growing network consisting of nodes, congestion scales as independently of how flows may be routed. This…
Bootstrap Percolation on Random Geometric Graphs
Milan Bradonjić, Iraj Saniee
Bootstrap percolation has been used effectively to model phenomena as diverse as emergence of magnetism in materials, spread of infection, diffusion of software viruses in computer…
Spectral analysis of communication networks using Dirichlet eigenvalues
Alexander Tsiatas, Iraj Saniee, Onuttom Narayan +1
The spectral gap of the graph Laplacian with Dirichlet boundary conditions is computed for the graphs of several communication networks at the IP-layer, which are subgraphs of the…
Lack of Hyperbolicity in Asymptotic Erdös--Renyi Sparse Random Graphs
Onuttom Narayan, Iraj Saniee, Gabriel H. Tucci
In this work we prove that the giant component of the Erdös--Renyi random graph for c a constant greater than 1 (sparse regime), is not Gromov -hyperbolic for any pos…
The Large Scale Curvature of Networks
Onuttom Narayan, Iraj Saniee
Understanding key structural properties of large scale networks are crucial for analyzing and optimizing their performance, and improving their reliability and security. Here we sh…
Scaling of load in communications networks
Onuttom Narayan, Iraj Saniee
We show that the load at each node in a preferential attachment network scales as a power of the degree of the node. For a network whose degree distribution is p(k) ~ k^(-gamma), w…