Tianxiang Gao

According to our database, Tianxiang Gao authored at least 19 papers between 2012 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Wide Neural Networks as Gaussian Processes: Lessons from Deep Equilibrium Models.

Tianxiang Gao, Xiaokai Huo, Hailiang Liu, Hongyang Gao

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

On the optimization and generalization of overparameterized implicit neural networks.

Tianxiang Gao, Hongyang Gao

CoRR, 2022

Gradient Descent Optimizes Infinite-Depth ReLU Implicit Networks with Linear Widths.

Tianxiang Gao, Hongyang Gao

CoRR, 2022

A global convergence theory for deep ReLU implicit networks via over-parameterization.

Tianxiang Gao, Hailiang Liu, Jia Liu, Hridesh Rajan, Hongyang Gao

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Interactive Few-Shot Learning: Limited Supervision, Better Medical Image Segmentation.

Ruiwei Feng, Xiangshang Zheng, Tianxiang Gao, Jintai Chen, Wenzhe Wang, Danny Z. Chen, Jian Wu

IEEE Trans. Medical Imaging, 2021

Alternate Model Growth and Pruning for Efficient Training of Recommendation Systems.

Xiaocong Du, Bhargav Bhushanam, Jiecao Yu, Dhruv Choudhary, Tianxiang Gao, Sherman Wong, Louis Feng, Jongsoo Park, Yu Cao, Arun Kejariwal

Proceedings of the 20th IEEE International Conference on Machine Learning and Applications, 2021

On the Convergence of Randomized Bregman Coordinate Descent for Non-Lipschitz Composite Problems.

Tianxiang Gao, Songtao Lu, Jia Liu, Chris Chu

Proceedings of the IEEE International Conference on Acoustics, 2021

2020

Randomized Bregman Coordinate Descent Methods for Non-Lipschitz Optimization.

Tianxiang Gao, Songtao Lu, Jia Liu, Chris Chu

CoRR, 2020

A Forest from the Trees: Generation through Neighborhoods.

Yang Li, Tianxiang Gao, Junier Oliva

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Leveraging Two Reference Functions in Block Bregman Proximal Gradient Descent for Non-convex and Non-Lipschitz Problems.

Tianxiang Gao, Songtao Lu, Jia Liu, Chris Chu

CoRR, 2019

2018

DancingLines: An Analytical Scheme to Depict Cross-Platform Event Popularity.

Tianxiang Gao, Weiming Bao, Jinning Li, Xiaofeng Gao, Boyuan Kong, Yan Tang, Guihai Chen, Xuan Li

Proceedings of the Database and Expert Systems Applications, 2018

DID: Distributed Incremental Block Coordinate Descent for Nonnegative Matrix Factorization.

Tianxiang Gao, Chris Chu

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Extracting information from deep learning models for computational biology.

Tianxiang Gao

PhD thesis, 2017

2016

Degrees of Freedom in Deep Neural Networks.

Tianxiang Gao, Vladimir Jojic

Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

Minimum-volume-regularized weighted symmetric nonnegative matrix factorization for clustering.

Tianxiang Gao, Sigurdur Olofsson, Songtao Lu

Proceedings of the 2016 IEEE Global Conference on Signal and Information Processing, 2016

2015

Drug-induced mRNA Signatures Are Enriched for the Minority of Genes that Are Highly Heritable.

Tianxiang Gao, Petter Brodin, Mark M. Davis, Vladimir Jojic

Proceedings of the Biocomputing 2015: Proceedings of the Pacific Symposium, 2015

2014

Modelling relational statistics with Bayes Nets.

Oliver Schulte, Hassan Khosravi, Arthur E. Kirkpatrick, Tianxiang Gao, Yuke Zhu

Mach. Learn., 2014

2012

Learning compact Markov logic networks with decision trees.

Hassan Khosravi, Oliver Schulte, Jianfeng Hu, Tianxiang Gao

Mach. Learn., 2012

Random Regression for Bayes Nets Applied to Relational Data.

Oliver Schulte, Hassan Khosravi, Tianxiang Gao, Yuke Zhu

Proceedings of the 2nd International Workshop on Statistical Relational AI (StaRAI-12), 2012