5 papers
Learning Distributions from Multiple Data Providers
Jon Kleinberg, Amin Saberi, Xizhi Tan +1
Motivated by learning from heterogeneous and overlapping data providers, we study a stylized model of distribution learning from restricted conditional samples. The goal is to lear…
On Language Generation in the Limit with Bounded Memory
Jon Kleinberg, Anay Mehrotra, Amin Saberi +1
We study language generation in the limit under bounded memory. In this task, a learner observes examples from an unknown target language one at a time and must eventually output o…
Local Limits of Small World Networks
Yeganeh Alimohammadi, Senem Işık, Amin Saberi
Small-world networks, known for high local clustering and short path lengths, are a fundamental structure in many real-world systems, including social, biological, and technologica…
A Local Graph Limits Perspective on Sampling-Based GNNs
Yeganeh Alimohammadi, Luana Ruiz, Amin Saberi
We propose a theoretical framework for training Graph Neural Networks (GNNs) on large input graphs via training on small, fixed-size sampled subgraphs. This framework is applicable…
Locality-Aware Graph-Rewiring in GNNs
Federico Barbero, Ameya Velingker, Amin Saberi +2
Graph Neural Networks (GNNs) are popular models for machine learning on graphs that typically follow the message-passing paradigm, whereby the feature of a node is updated recursiv…