Unraveling the Key Components of OOD Generalization via Diversification

no code implementations • 26 Dec 2023 • Harold Benoit, Liangze Jiang, Andrei Atanov, Oğuzhan Fatih Kar, Mattia Rigotti, Amir Zamir

We show that (1) diversification methods are highly sensitive to the distribution of the unlabeled data used for diversification and can underperform significantly when away from a method-specific sweet spot.

Distributed Adaptive Time-Varying Convex Optimization for Multi-agent Systems

no code implementations • 20 Oct 2023 • Liangze Jiang, Zhengguang Wu, Lei Wang

A new class of adaptive algorithms are proposed to solve time-varying convex optimization problems.

TF-GNN: Graph Neural Networks in TensorFlow

1 code implementation • 7 Jul 2022 • Oleksandr Ferludin, Arno Eigenwillig, Martin Blais, Dustin Zelle, Jan Pfeifer, Alvaro Sanchez-Gonzalez, Wai Lok Sibon Li, Sami Abu-El-Haija, Peter Battaglia, Neslihan Bulut, Jonathan Halcrow, Filipe Miguel Gonçalves de Almeida, Pedro Gonnet, Liangze Jiang, Parth Kothari, Silvio Lattanzi, André Linhares, Brandon Mayer, Vahab Mirrokni, John Palowitch, Mihir Paradkar, Jennifer She, Anton Tsitsulin, Kevin Villela, Lisa Wang, David Wong, Bryan Perozzi

TensorFlow-GNN (TF-GNN) is a scalable library for Graph Neural Networks in TensorFlow.

Graph Sampling

Test-Time Robust Personalization for Federated Learning

1 code implementation • 22 May 2022 • Liangze Jiang, Tao Lin

Personalized FL additionally adapts the global model to different clients, achieving promising results on consistent local training and test distributions.

Federated Learning