139 citations · 725 across the 72 of their papers we have counts for
6 papers · 1 filter
Rates of Convergence for Large-scale Nearest Neighbor Classification
Xingye Qiao, Jiexin Duan, Guang Cheng
Nearest neighbor is a popular class of classification methods with many desirable properties. For a large data set which cannot be loaded into the memory of a single machine due to…
Adaptive Variational Bayesian Inference for Sparse Deep Neural Network
Jincheng Bai, Qifan Song, Guang Cheng
In this work, we focus on variational Bayesian inference on the sparse Deep Neural Network (DNN) modeled under a class of spike-and-slab priors. Given a pre-specified sparse DNN st…
Benefit of Interpolation in Nearest Neighbor Algorithms
Yue Xing, Qifan Song, Guang Cheng
The over-parameterized models attract much attention in the era of data science and deep learning. It is empirically observed that although these models, e.g. deep neural networks,…
A generalization of regularized dual averaging and its dynamics
Shih-Kang Chao, Guang Cheng
Excessive computational cost for learning large data and streaming data can be alleviated by using stochastic algorithms, such as stochastic gradient descent and its variants. Rece…
Enhancing Multi-model Inference with Natural Selection
Ching-Wei Cheng, Guang Cheng
Multi-model inference covers a wide range of modern statistical applications such as variable selection, model confidence set, model averaging and variable importance. The performa…
Bootstrapping Upper Confidence Bound
Botao Hao, Yasin Abbasi-Yadkori, Zheng Wen +1
Upper Confidence Bound (UCB) method is arguably the most celebrated one used in online decision making with partial information feedback. Existing techniques for constructing confi…