32 citations · 140 across the 32 of their papers we have counts for
12 papers · 1 filter
Efficient Dynamic Algorithms for Graph Neural Networks with Non-Linear Propagation
Kiarash Banihashem, MohammadTaghi Hajiaghayi, Mahdi JafariRaviz +2
Graph Neural Networks (GNNs) are widely used for representation learning on graphs, but most methods assume static topologies, making them inefficient on evolving networks where ed…
On Classification Thresholds for Graph Attention with Edge Features
Kimon Fountoulakis, Dake He, Silvio Lattanzi +3
The recent years we have seen the rise of graph neural networks for prediction tasks on graphs. One of the dominant architectures is graph attention due to its ability to make pred…
Active Learning of Classifiers with Label and Seed Queries
Marco Bressan, Nicolò Cesa-Bianchi, Silvio Lattanzi +2
We study exact active learning of binary and multiclass classifiers with margin. Given an -point set , we want to learn any unknown classifier on who…
TF-GNN: Graph Neural Networks in TensorFlow
Oleksandr Ferludin, Arno Eigenwillig, Martin Blais +24
TensorFlow-GNN (TF-GNN) is a scalable library for Graph Neural Networks in TensorFlow. It is designed from the bottom up to support the kinds of rich heterogeneous graph data that…
Near-Optimal Correlation Clustering with Privacy
Vincent Cohen-Addad, Chenglin Fan, Silvio Lattanzi +4
Correlation clustering is a central problem in unsupervised learning, with applications spanning community detection, duplicate detection, automated labelling and many more. In the…
On Margin-Based Cluster Recovery with Oracle Queries
Marco Bressan, Nicolò Cesa-Bianchi, Silvio Lattanzi +1
We study an active cluster recovery problem where, given a set of points and an oracle answering queries like "are these two points in the same cluster?", the task is to recove…
Exact Recovery of Clusters in Finite Metric Spaces Using Oracle Queries
Marco Bressan, Nicolò Cesa-Bianchi, Silvio Lattanzi +1
We investigate the problem of exact cluster recovery using oracle queries. Previous results show that clusters in Euclidean spaces that are convex and separated with a margin can b…
Fast and Accurate -means++ via Rejection Sampling
Vincent Cohen-Addad, Silvio Lattanzi, Ashkan Norouzi-Fard +2
-means++ \cite{arthur2007k} is a widely used clustering algorithm that is easy to implement, has nice theoretical guarantees and strong empirical performance. Despite its wide a…
InstantEmbedding: Efficient Local Node Representations
Ştefan Postăvaru, Anton Tsitsulin, Filipe Miguel Gonçalves de Almeida +3
In this paper, we introduce InstantEmbedding, an efficient method for generating single-node representations using local PageRank computations. We theoretically prove that our appr…
Exact Recovery of Mangled Clusters with Same-Cluster Queries
Marco Bressan, Nicolò Cesa-Bianchi, Silvio Lattanzi +1
We study the cluster recovery problem in the semi-supervised active clustering framework. Given a finite set of input points, and an oracle revealing whether any two points lie in…
Submodular Streaming in All its Glory: Tight Approximation, Minimum Memory and Low Adaptive Complexity
Ehsan Kazemi, Marko Mitrovic, Morteza Zadimoghaddam +2
Streaming algorithms are generally judged by the quality of their solution, memory footprint, and computational complexity. In this paper, we study the problem of maximizing a mono…
Fair Clustering Through Fairlets
Flavio Chierichetti, Ravi Kumar, Silvio Lattanzi +1
We study the question of fair clustering under the {\em disparate impact} doctrine, where each protected class must have approximately equal representation in every cluster. We for…