58 citations · 89 across the 14 of their papers we have counts for
7 papers · 1 filter
List-Decodable Sparse Mean Estimation
Shiwei Zeng, Jie Shen
Robust mean estimation is one of the most important problems in statistics: given a set of samples in where an fraction are drawn from some distribution and…
Semi-verified PAC Learning from the Crowd
Shiwei Zeng, Jie Shen
We study the problem of crowdsourced PAC learning of threshold functions. This is a challenging problem and only recently have query-efficient algorithms been established under the…
Sample-Optimal PAC Learning of Halfspaces with Malicious Noise
Jie Shen
We study efficient PAC learning of homogeneous halfspaces in in the presence of malicious noise of Valiant (1985). This is a challenging noise model and only until r…
On the Power of Localized Perceptron for Label-Optimal Learning of Halfspaces with Adversarial Noise
Jie Shen
We study {\em online} active learning of homogeneous halfspaces in with adversarial noise where the overall probability of a noisy label is constrained to be at most…
Efficient PAC Learning from the Crowd with Pairwise Comparisons
Shiwei Zeng, Jie Shen
We study crowdsourced PAC learning of threshold functions, where the labels are gathered from a pool of annotators some of whom may behave adversarially. This is yet a challenging…
One-Bit Compressed Sensing via One-Shot Hard Thresholding
Jie Shen
This paper concerns the problem of 1-bit compressed sensing, where the goal is to estimate a sparse signal from a few of its binary measurements. We study a non-convex sparsity-con…
Efficient active learning of sparse halfspaces with arbitrary bounded noise
Chicheng Zhang, Jie Shen, Pranjal Awasthi
We study active learning of homogeneous -sparse halfspaces in under the setting where the unlabeled data distribution is isotropic log-concave and each label is f…