Yatao A. Bian
Yatao A. Bian
Tencent AI Lab
Verified email at inf.ethz.ch - Homepage
Title
Cited by
Cited by
Year
Guarantees for Greedy Maximization of Non-submodular Functions with Applications
AA Bian, JM Buhmann, A Krause, S Tschiatschek
ICML 2017, 2017
1332017
Guaranteed non-convex optimization: Submodular maximization over continuous domains
AA Bian, B Mirzasoleiman, JM Buhmann, A Krause
AISTATS 2017, 2017
952017
CoLa: Communication-Efficient Decentralized Linear Learning
L He*, A Bian*, M Jaggi
NeurIPS 2018, 2018
60*2018
Continuous DR-submodular Maximization: Structure and Algorithms
A Bian, K Levy, A Krause, JM Buhmann
NIPS 2017, 486-496, 2017
422017
Optimal Continuous DR-Submodular Maximization and Applications to Provable Mean Field Inference
YA Bian, JM Buhmann, A Krause
ICML, 644-653, 2019
21*2019
A Distributed Second-Order Algorithm You Can Trust
C DŁnner, A Lucchi, M Gargiani, A Bian, T Hofmann, M Jaggi
ICML 2018, 2018
202018
Parallel Coordinate Descent Newton Method for Efficient -Regularized Loss Minimization
YA Bian, X Li, Y Liu, MH Yang
IEEE transactions on neural networks and learning systems 30 (11), 3233-3245, 2019
9*2019
Bundle CDN: A Highly Parallelized Approach for Large-Scale ℓ1-Regularized Logistic Regression
Y Bian, X Li, M Cao, Y Liu
Joint European Conference on Machine Learning and Knowledge Discovery in†…, 2013
92013
Model selection for gaussian process regression
NS Gorbach, AA Bian, B Fischer, S Bauer, JM Buhmann
German Conference on Pattern Recognition, 306-318, 2017
82017
Greedy maxcut algorithms and their information content
Y Bian, A Gronskiy, JM Buhmann
2015 IEEE Information Theory Workshop (ITW), 1-5, 2015
72015
Parallel coordinate descent Newton for large scale L1 regularized minimization
Y Bian, X Li, Y Liu
arXiv preprint arXiv:1306.4080, 2013
62013
Multi-View Graph Neural Networks for Molecular Property Prediction
H Ma, Y Bian, Y Rong, W Huang, T Xu, W Xie, G Ye, J Huang
Machine Learning for Molecules Workshop@NeurIPS 2020, 2020
5*2020
Self-Supervised Graph Transformer on Large-Scale Molecular Data
Y Rong*, Y Bian*, T Xu, W Xie, Y Wei, W Huang, J Huang
Advances in Neural Information Processing Systems 33, 2020
5*2020
Information-theoretic analysis of MaxCut algorithms.
Y Bian, A Gronskiy, JM Buhmann
ITA, 1-5, 2016
42016
Continuous submodular function maximization
Y Bian, JM Buhmann, A Krause
arXiv preprint arXiv:2006.13474, 2020
22020
Provable Non-Convex Optimization and Algorithm Validation via Submodularity
YA Bian
PhD thesis, ETH Zurich, 2019
22019
Parallelized annealed particle filter for real-time marker-less motion tracking via heterogeneous computing
Y Bian, X Zhao, J Song, Y Liu
Proceedings of the 21st International Conference on Pattern Recognition†…, 2012
22012
From Sets to Multisets: Provable Variational Inference for Probabilistic Integer Submodular Models
A Sahin, Y Bian, JM Buhmann, A Krause
ICML 2020, 2020
12020
Digitize Your Body and Action in 3-D at Over 10 FPS: Real Time Dense Voxel Reconstruction and Marker-less Motion Tracking via GPU Acceleration
J Song, Y Bian, J Yan, X Zhao, Y Liu
Champion technical report of AMD China Accelerated Computing Contest, 2011, 2013
12013
On Self-Distilling Graph Neural Network
Y Chen, Y Bian, X Xiao, Y Rong, T Xu, J Huang
arXiv preprint arXiv:2011.02255, 2020
2020
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