555 citations · 2.5k across the 105 of their papers we have counts for
11 papers · 1 filter
A Non-Asymptotic Analysis of Oversmoothing in Graph Neural Networks
Xinyi Wu, Zhengdao Chen, William Wang +1
Oversmoothing is a central challenge of building more powerful Graph Neural Networks (GNNs). While previous works have only demonstrated that oversmoothing is inevitable when the n…
Model Predictive Control via On-Policy Imitation Learning
Kwangjun Ahn, Zakaria Mhammedi, Horia Mania +2
In this paper, we leverage the rapid advances in imitation learning, a topic of intense recent focus in the Reinforcement Learning (RL) literature, to develop new sample complexity…
Link Partitioning on Simplicial Complexes Using Higher-Order Laplacians
Xinyi Wu, Arnab Sarker, Ali Jadbabaie
Link partitioning is a popular approach in network science used for discovering overlapping communities by identifying clusters of strongly connected links. Current link partitioni…
Generalizing Homophily to Simplicial Complexes
Arnab Sarker, Natalie Northrup, Ali Jadbabaie
Group interactions occur frequently in social settings, yet their properties beyond pairwise relationships in network models remain unexplored. In this work, we study homophily, th…
On Convergence of Gradient Descent Ascent: A Tight Local Analysis
Haochuan Li, Farzan Farnia, Subhro Das +1
Gradient Descent Ascent (GDA) methods are the mainstream algorithms for minimax optimization in generative adversarial networks (GANs). Convergence properties of GDA have drawn sig…
Gradient Descent for Low-Rank Functions
Romain Cosson, Ali Jadbabaie, Anuran Makur +2
Several recent empirical studies demonstrate that important machine learning tasks, e.g., training deep neural networks, exhibit low-rank structure, where the loss function varies…