Active learning for human action recognition with Gaussian Processes. - Xianghang Liu; Jian Zhang 002 (ICIP, 2011)

Learning as MAP Inference in Discrete Graphical Models. - Xianghang Liu; James Petterson; Tibério S. Caetano (NIPS, 2012)

Projecting Ising Model Parameters for Fast Mixing. - Justin Domke; Xianghang Liu (NIPS, 2013)

Projecting Markov Random Field Parameters for Fast Mixing. - Xianghang Liu; Justin Domke (NIPS, 2014)

Bayesian Models for Structured Sparse Estimation via Set Cover Prior. - Xianghang Liu; Xinhua Zhang; Tibério S. Caetano (ECML/PKDD (2), 2014)

New Algorithms for Graphical Models and Their Applications in Learning. - Xianghang Liu (2015)

Online Meta-Learning for Model Update Aggregation in Federated Learning for Click-Through Rate Prediction. - Xianghang Liu; Bartlomiej Twardowski; Tri Kurniawan Wijaya (CoRR, 2022)

FedFNN: Faster Training Convergence Through Update Predictions in Federated Recommender Systems. - Francesco Fabbri; Xianghang Liu; Jack R. McKenzie; Bartlomiej Twardowski; Tri Kurniawan Wijaya (CoRR, 2023)