Sotabase

Career

· Postdoctoral Researcher, ETH Zurich2022–
· Postdoctoral Researcher, University of Pennsylvania2019–2022
· PhD in Computer Science, Zhejiang University2014–2019
· Bachelor of Science in Computer Science, Zhejiang University2010–2014

Publications (51)

Hessian Aided Policy Gradient
International Conference on Machine Learning · 2019
88
cited
The application of a novel neural network in the detection of phishing websites
Journal of Ambient Intelligence and Humanized Computing · 2018
72
cited
An Agnostic Approach to Federated Learning with Class Imbalance
International Conference on Learning Representations · 2022
67
cited
One Sample Stochastic Frank-Wolfe
International Conference on Artificial Intelligence and Statistics · 2019
66
cited
Towards More Efficient Stochastic Decentralized Learning: Faster Convergence and Sparse Communication
International Conference on Machine Learning · 2018
60
cited
A novel approach for mobile malware classification and detection in Android systems
Multimedia tools and applications · 2018
47
cited
A Decentralized Proximal Point-type Method for Saddle Point Problems
arXiv.org · 2019
33
cited
Efficient Projection-Free Online Methods with Stochastic Recursive Gradient
AAAI Conference on Artificial Intelligence · 2019
33
cited
Complexities in Projection-Free Stochastic Non-convex Minimization
International Conference on Artificial Intelligence and Statistics · 2019
28
cited
Self-Consistency of the Fokker-Planck Equation
Annual Conference Computational Learning Theory · 2022
25
cited
Stochastic Conditional Gradient++
SIAM Journal on Optimization · 2019
23
cited
Tensor Completion with Side Information: A Riemannian Manifold Approach
International Joint Conference on Artificial Intelligence · 2017
22
cited
Share Your Representation Only: Guaranteed Improvement of the Privacy-Utility Tradeoff in Federated Learning
International Conference on Learning Representations · 2023
21
cited
JUMP: A Joint Predictor for User Click and Dwell Time
2018
20
cited
Multitask Metric Learning: Theory and Algorithm
International Conference on Artificial Intelligence and Statistics · 2019
20
cited
A deep learning method for Chinese singer identification
Tsinghua Science and Technology · 2019
18
cited
Adaptive Variance Reducing for Stochastic Gradient Descent
International Joint Conference on Artificial Intelligence · 2016
17
cited
Arrhythmia recognition and classification through deep learning-based approach
Int. J. Comput. Sci. Eng. · 2019
14
cited
Sinkhorn Natural Gradient for Generative Models
Neural Information Processing Systems · 2020
14
cited
Stochastic Continuous Greedy ++: When Upper and Lower Bounds Match
Neural Information Processing Systems · 2019
13
cited
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