Cheng Tang
Title
Cited by
Cited by
Year
When do random forests fail?
C Tang, D Garreau, U von Luxburg
NeurIPS, 2987-2997, 2018
312018
On Lloyd’s algorithm: new theoretical insights for clustering in practice
C Tang, C Monteleoni
Artificial Intelligence and Statistics, 1280-1289, 2016
202016
Convergence rate of stochastic k-means
C Tang, C Monteleoni
Artificial Intelligence and Statistics, 1495-1503, 2017
142017
Exponentially convergent stochastic k-PCA without variance reduction
C Tang
arXiv preprint arXiv:1904.01750, 2019
82019
Can topic modeling shed light on climate extremes?
C Tang, C Monteleoni
Computing in Science & Engineering 17 (6), 43-52, 2015
62015
On the convergence rate of stochastic gradient descent for strongly convex functions
C Tang, C Monteleoni
Regularization, optimization, kernels, and support vector machines, 159-175, 2015
42015
Detecting extreme events from climate time series via topic modeling
C Tang, C Monteleoni
Machine Learning and Data Mining Approaches to Climate Science, 207-215, 2015
42015
Demystifying overcomplete nonlinear auto-encoders: fast SGD convergence towards sparse representation from random initialization
C Tang, C Monteleoni
12018
Convergence analysis of stochastic gradient descent on strongly convex objective functions
C Tang, C Monteleoni
Proceedings of ROKS, 111-112, 2013
12013
Scalable constant k-means approximation via heuristics on well-clusterable data
C Tang, C Monteleoni
Poster Session of Learning faster from easy data II conference, Montreal, Canada, 0
1
Neural document expansion for ad-hoc information retrieval
C Tang, A Arnold
arXiv preprint arXiv:2012.14005, 2020
2020
Transforming Machine Learning Heuristics into Provable Algorithms: Classical, Stochastic, and Neural
C Tang
The George Washington University, 2018
2018
Seasonal prediction using unsupervised feature learning and regression
M Mohan, C Tang, C Monteleoni, T DelSole, B Cash
Proceedings of the Fifth International Workshop on Climate Informatics: CI 2015, 2015
2015
HOW FAR CAN WE EXPLOIT THE STRUCTURAL RICHNESS OF CLIMATE DATA?—A CASE STUDY
M Mohan, C Tang, C Monteleoni, T DelSole, B Cash
Scaling up Lloyd’s algorithm: stochastic and parallel block-wise optimization perspectives
C Tang, C Monteleoni
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Articles 1–15