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Tianxiang Gao
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2020 – today
- 2024
- [j4]Tianxiang Gao, Zijian Hong, Yixing Tan, Lizhuo Sun, Yichen Wei
, Jianwei Ma
HC-MVSNet: A probability sampling-based multi-view-stereo network with hybrid cascade structure for 3D reconstruction. Pattern Recognit. Lett. 185: 59-65 (2024) - 2023
- [c12]Tianxiang Gao, Xiaokai Huo, Hailiang Liu, Hongyang Gao:
Wide Neural Networks as Gaussian Processes: Lessons from Deep Equilibrium Models. NeurIPS 2023 - [i11]Tianxiang Gao, Xiaokai Huo, Hailiang Liu, Hongyang Gao:
Wide Neural Networks as Gaussian Processes: Lessons from Deep Equilibrium Models. CoRR abs/2310.10767 (2023) - 2022
- [c11]Tianxiang Gao, Hailiang Liu, Jia Liu, Hridesh Rajan, Hongyang Gao:
A global convergence theory for deep ReLU implicit networks via over-parameterization. ICLR 2022 - [i10]Tianxiang Gao, Hongyang Gao:
Gradient Descent Optimizes Infinite-Depth ReLU Implicit Networks with Linear Widths. CoRR abs/2205.07463 (2022) - [i9]Tianxiang Gao, Hongyang Gao:
On the optimization and generalization of overparameterized implicit neural networks. CoRR abs/2209.15562 (2022) - 2021
- [j3]Ruiwei Feng
Interactive Few-Shot Learning: Limited Supervision, Better Medical Image Segmentation. IEEE Trans. Medical Imaging 40(10): 2575-2588 (2021) - [c10]Tianxiang Gao, Songtao Lu, Jia Liu, Chris Chu:
On the Convergence of Randomized Bregman Coordinate Descent for Non-Lipschitz Composite Problems. ICASSP 2021: 5549-5553 - [c9]Xiaocong Du, Bhargav Bhushanam, Jiecao Yu, Dhruv Choudhary, Tianxiang Gao, Sherman Wong, Louis Feng, Jongsoo Park, Yu Cao, Arun Kejariwal:
Alternate Model Growth and Pruning for Efficient Training of Recommendation Systems. ICMLA 2021: 1421-1428 - [i8]Xiaocong Du, Bhargav Bhushanam, Jiecao Yu, Dhruv Choudhary, Tianxiang Gao, Sherman Wong, Louis Feng, Jongsoo Park, Yu Cao, Arun Kejariwal:
Alternate Model Growth and Pruning for Efficient Training of Recommendation Systems. CoRR abs/2105.01064 (2021) - [i7]Tianxiang Gao, Hailiang Liu, Jia Liu, Hridesh Rajan, Hongyang Gao:
A global convergence theory for deep ReLU implicit networks via over-parameterization. CoRR abs/2110.05645 (2021) - 2020
- [c8]Yang Li, Tianxiang Gao, Junier Oliva:
A Forest from the Trees: Generation through Neighborhoods. AAAI 2020: 4755-4762 - [i6]Tianxiang Gao, Songtao Lu, Jia Liu, Chris Chu:
Randomized Bregman Coordinate Descent Methods for Non-Lipschitz Optimization. CoRR abs/2001.05202 (2020)
2010 – 2019
- 2019
- [i5]Yang Li, Tianxiang Gao, Junier Oliva:
A Forest from the Trees: Generation through Neighborhoods. CoRR abs/1902.01435 (2019) - [i4]Tianxiang Gao, Songtao Lu, Jia Liu, Chris Chu:
Leveraging Two Reference Functions in Block Bregman Proximal Gradient Descent for Non-convex and Non-Lipschitz Problems. CoRR abs/1912.07527 (2019) - 2018
- [c7]Tianxiang Gao, Chris Chu:
DID: Distributed Incremental Block Coordinate Descent for Nonnegative Matrix Factorization. AAAI 2018: 2991-2998 - [c6]Tianxiang Gao, Weiming Bao, Jinning Li, Xiaofeng Gao, Boyuan Kong, Yan Tang, Guihai Chen
DancingLines: An Analytical Scheme to Depict Cross-Platform Event Popularity. DEXA (1) 2018: 283-299 - [i3]Tianxiang Gao, Chris Chu:
DID: Distributed Incremental Block Coordinate Descent for Nonnegative Matrix Factorization. CoRR abs/1802.08938 (2018) - 2017
- [b1]Tianxiang Gao:
Extracting information from deep learning models for computational biology. University of North Carolina, Chapel Hill, USA, 2017 - [i2]Tianxiang Gao, Weiming Bao, Jinning Li, Xiaofeng Gao, Boyuan Kong, Yan Tang, Guihai Chen, Xuan Li:
DancingLines: An Analytical Scheme to Depict Cross-Platform Event Popularity. CoRR abs/1712.08550 (2017) - 2016
- [c5]Tianxiang Gao, Sigurdur Olofsson, Songtao Lu:
Minimum-volume-regularized weighted symmetric nonnegative matrix factorization for clustering. GlobalSIP 2016: 247-251 - [c4]Tianxiang Gao, Vladimir Jojic:
Degrees of Freedom in Deep Neural Networks. UAI 2016 - [i1]Tianxiang Gao, Vladimir Jojic:
Degrees of Freedom in Deep Neural Networks. CoRR abs/1603.09260 (2016) - 2015
- [c3]Tianxiang Gao, Petter Brodin, Mark M. Davis, Vladimir Jojic:
Drug-induced mRNA Signatures Are Enriched for the Minority of Genes that Are Highly Heritable. Pacific Symposium on Biocomputing 2015: 395-406 - 2014
- [j2]Oliver Schulte, Hassan Khosravi
Modelling relational statistics with Bayes Nets. Mach. Learn. 94(1): 105-125 (2014) - 2012
- [j1]Hassan Khosravi
Learning compact Markov logic networks with decision trees. Mach. Learn. 89(3): 257-277 (2012) - [c2]Oliver Schulte, Hassan Khosravi, Tianxiang Gao, Yuke Zhu:
Random Regression for Bayes Nets Applied to Relational Data. StarAI@UAI 2012 - 2011
- [c1]Hassan Khosravi, Oliver Schulte, Jianfeng Hu, Tianxiang Gao:
Learning Compact Markov Logic Networks with Decision Trees. ILP 2011: 20-25
Coauthor Index
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