Search Results for author: Yang Ning

Found 21 papers, 1 papers with code

Inference with non-differentiable surrogate loss in a general high-dimensional classification framework

no code implementations20 May 2024 Muxuan Liang, Yang Ning, Maureen A Smith, Ying-Qi Zhao

In this work, we propose a kernel-smoothed decorrelated score to construct hypothesis testing and interval estimations for the linear decision rule estimated using a piece-wise linear surrogate loss, which has a discontinuous gradient and non-regular Hessian.


Two-stage Hypothesis Tests for Variable Interactions with FDR Control

no code implementations31 Aug 2022 Jingyi Duan, Yang Ning, Xi Chen, Yong Chen

In many scenarios such as genome-wide association studies where dependences between variables commonly exist, it is often of interest to infer the interaction effects in the model.

Vocal Bursts Valence Prediction

Treatment Effect Estimation with Unobserved and Heterogeneous Confounding Variables

no code implementations29 Jul 2022 Kevin Jiang, Yang Ning

The estimation of the treatment effect is often biased in the presence of unobserved confounding variables which are commonly referred to as hidden variables.

Optimal Variable Clustering for High-Dimensional Matrix Valued Data

no code implementations24 Dec 2021 Inbeom Lee, Siyi Deng, Yang Ning

To extract the information from the dependence structure for clustering, we propose a new latent variable model for the features arranged in matrix form, with some unknown membership matrices representing the clusters for the rows and columns.

Clustering Vocal Bursts Intensity Prediction

Exponential Family Graphical Models: Correlated Replicates and Unmeasured Confounders, with Applications to fMRI Data

no code implementations9 Dec 2020 Yanxin Jin, Yang Ning, Kean Ming Tan

Motivated by functional magnetic resonance imaging (fMRI) studies, we propose a novel method for constructing brain connectivity networks with correlated replicates and latent effects.


Optimal and Safe Estimation for High-Dimensional Semi-Supervised Learning

no code implementations28 Nov 2020 Siyi Deng, Yang Ning, Jiwei Zhao, Heping Zhang

Our goal is to investigate when and how the unlabeled data can be exploited to improve the estimation of the regression parameters of linear model in light of the fact that such linear models may be misspecified in data analysis.

regression Vocal Bursts Intensity Prediction

Doubly Robust Semiparametric Difference-in-Differences Estimators with High-Dimensional Data

no code implementations7 Sep 2020 Yang Ning, Sida Peng, Jing Tao

This paper proposes a doubly robust two-stage semiparametric difference-in-difference estimator for estimating heterogeneous treatment effects with high-dimensional data.

valid Vocal Bursts Intensity Prediction

Regularized Training and Tight Certification for Randomized Smoothed Classifier with Provable Robustness

no code implementations17 Feb 2020 Huijie Feng, Chunpeng Wu, Guoyang Chen, Weifeng Zhang, Yang Ning

In this work, we derive a new regularized risk, in which the regularizer can adaptively encourage the accuracy and robustness of the smoothed counterpart when training the base classifier.

Nonregular and Minimax Estimation of Individualized Thresholds in High Dimension with Binary Responses

no code implementations26 May 2019 Huijie Feng, Yang Ning, Jiwei Zhao

Statistically, we show that the finite sample error bound for estimating $\theta$ in $\ell_2$ norm is $(s\log d/n)^{\beta/(2\beta+1)}$, where $d$ is the dimension of $\theta$, $s$ is the sparsity level, $n$ is the sample size and $\beta$ is the smoothness of the conditional density of $X$ given the response $Y$ and the covariates $Z$.

Robust Estimation of Causal Effects via High-Dimensional Covariate Balancing Propensity Score

no code implementations20 Dec 2018 Yang Ning, Sida Peng, Kosuke Imai

We first use a class of penalized M-estimators for the propensity score and outcome models.


High-Dimensional Inference for Cluster-Based Graphical Models

no code implementations13 Jun 2018 Carson Eisenach, Florentina Bunea, Yang Ning, Claudiu Dinicu

We employ model assisted clustering, in which the clusters contain features that are similar to the same unobserved latent variable.

Clustering Vocal Bursts Intensity Prediction

Adaptive Estimation in Structured Factor Models with Applications to Overlapping Clustering

no code implementations23 Apr 2017 Xin Bing, Florentina Bunea, Yang Ning, Marten Wegkamp

This work introduces a novel estimation method, called LOVE, of the entries and structure of a loading matrix A in a sparse latent factor model X = AZ + E, for an observable random vector X in Rp, with correlated unobservable factors Z \in RK, with K unknown, and independent noise E. Each row of A is scaled and sparse.


High Dimensional EM Algorithm: Statistical Optimization and Asymptotic Normality

no code implementations NeurIPS 2015 Zhaoran Wang, Quanquan Gu, Yang Ning, Han Liu

We provide a general theory of the expectation-maximization (EM) algorithm for inferring high dimensional latent variable models.

Vocal Bursts Intensity Prediction

A Unified Theory of Confidence Regions and Testing for High Dimensional Estimating Equations

no code implementations30 Oct 2015 Matey Neykov, Yang Ning, Jun S. Liu, Han Liu

Our main theoretical contribution is to establish a unified Z-estimation theory of confidence regions for high dimensional problems.


Local and Global Inference for High Dimensional Nonparanormal Graphical Models

no code implementations9 Feb 2015 Quanquan Gu, Yuan Cao, Yang Ning, Han Liu

Due to the presence of unknown marginal transformations, we propose a pseudo likelihood based inferential approach.

Vocal Bursts Intensity Prediction

A General Theory of Hypothesis Tests and Confidence Regions for Sparse High Dimensional Models

no code implementations30 Dec 2014 Yang Ning, Han Liu

Specifically, we propose a decorrelated score function to handle the impact of high dimensional nuisance parameters.

High Dimensional Expectation-Maximization Algorithm: Statistical Optimization and Asymptotic Normality

no code implementations30 Dec 2014 Zhaoran Wang, Quanquan Gu, Yang Ning, Han Liu

We provide a general theory of the expectation-maximization (EM) algorithm for inferring high dimensional latent variable models.

Vocal Bursts Intensity Prediction

On Semiparametric Exponential Family Graphical Models

no code implementations30 Dec 2014 Zhuoran Yang, Yang Ning, Han Liu

We propose a new class of semiparametric exponential family graphical models for the analysis of high dimensional mixed data.

Two-sample testing

Testing and Confidence Intervals for High Dimensional Proportional Hazards Model

no code implementations16 Dec 2014 Ethan X. Fang, Yang Ning, Han Liu

This paper proposes a decorrelation-based approach to test hypotheses and construct confidence intervals for the low dimensional component of high dimensional proportional hazards models.

Model Selection Vocal Bursts Intensity Prediction

A Likelihood Ratio Framework for High Dimensional Semiparametric Regression

no code implementations6 Dec 2014 Yang Ning, Tianqi Zhao, Han Liu

(i) We develop a regularized statistical chromatography approach to infer the parameter of interest under the proposed semiparametric generalized linear model without the need of estimating the unknown base measure function.

regression Selection bias +1

High Dimensional Semiparametric Latent Graphical Model for Mixed Data

1 code implementation29 Apr 2014 Jianqing Fan, Han Liu, Yang Ning, Hui Zou

Theoretically, the proposed methods achieve the same rates of convergence for both precision matrix estimation and eigenvector estimation, as if the latent variables were observed.

feature selection Vocal Bursts Intensity Prediction

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