63 citations · 88 across the 9 of their papers we have counts for
13 papers
On Cyclic Solutions to the Min-Max Latency Multi-Robot Patrolling Problem
Peyman Afshani, Mark de Berg, Kevin Buchin +7
We consider the following surveillance problem: Given a set of sites in a metric space and a set of robots with the same maximum speed, compute a patrol schedule of min…
Continual and Sliding Window Release for Private Empirical Risk Minimization
Lauren Watson, Abhirup Ghosh, Benedek Rozemberczki +1
It is difficult to continually update private machine learning models with new data while maintaining privacy. Data incur increasing privacy loss -- as measured by differential pri…
PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models
Benedek Rozemberczki, Paul Scherer, Yixuan He +8
We present PyTorch Geometric Temporal a deep learning framework combining state-of-the-art machine learning algorithms for neural spatiotemporal signal processing. The main goal of…
Chickenpox Cases in Hungary: a Benchmark Dataset for Spatiotemporal Signal Processing with Graph Neural Networks
Benedek Rozemberczki, Paul Scherer, Oliver Kiss +2
Recurrent graph convolutional neural networks are highly effective machine learning techniques for spatiotemporal signal processing. Newly proposed graph neural network architectur…
Twitch Gamers: a Dataset for Evaluating Proximity Preserving and Structural Role-based Node Embeddings
Benedek Rozemberczki, Rik Sarkar
Proximity preserving and structural role-based node embeddings have become a prime workhorse of applied graph mining. Novel node embedding techniques are often tested on a restrict…
The Shapley Value of Classifiers in Ensemble Games
Benedek Rozemberczki, Rik Sarkar
What is the value of an individual model in an ensemble of binary classifiers? We answer this question by introducing a class of transferable utility cooperative games called \text…
Heterogeneous Interventions Reduce the Spread of COVID-19 in Simulations on Real Mobility Data
Haotian Wang, Abhirup Ghosh, Jiaxin Ding +2
Major interventions have been introduced worldwide to slow down the spread of the SARS-CoV-2 virus. Large-scale lockdowns of human movements are effective in reducing the spread, b…
Stability Enhanced Privacy and Applications in Private Stochastic Gradient Descent
Lauren Watson, Benedek Rozemberczki, Rik Sarkar
Private machine learning involves addition of noise while training, resulting in lower accuracy. Intuitively, greater stability can imply greater privacy and improve this privacy-u…
Little Ball of Fur: A Python Library for Graph Sampling
Benedek Rozemberczki, Oliver Kiss, Rik Sarkar
Sampling graphs is an important task in data mining. In this paper, we describe Little Ball of Fur a Python library that includes more than twenty graph sampling algorithms. Our go…
Approximation Algorithms for Multi-Robot Patrol-Scheduling with Min-Max Latency
Peyman Afshani, Mark De Berg, Kevin Buchin +7
We consider the problem of finding patrol schedules for robots to visit a given set of sites in a metric space. Each robot has the same maximum speed and the goal is to min…
Fast Sequence-Based Embedding with Diffusion Graphs
Benedek Rozemberczki, Rik Sarkar
A graph embedding is a representation of graph vertices in a low-dimensional space, which approximately preserves properties such as distances between nodes. Vertex sequence-based…
Multi-scale Attributed Node Embedding
Benedek Rozemberczki, Carl Allen, Rik Sarkar
We present network embedding algorithms that capture information about a node from the local distribution over node attributes around it, as observed over random walks following an…
GEMSEC: Graph Embedding with Self Clustering
Benedek Rozemberczki, Ryan Davies, Rik Sarkar +1
Modern graph embedding procedures can efficiently process graphs with millions of nodes. In this paper, we propose GEMSEC -- a graph embedding algorithm which learns a clustering o…