Search Results for author: Kaizheng Wang

Found 25 papers, 6 papers with code

Adaptive Transfer Clustering: A Unified Framework

1 code implementation28 Oct 2024 Yuqi Gu, Zhongyuan Lyu, Kaizheng Wang

We propose a general transfer learning framework for clustering given a main dataset and an auxiliary one about the same subjects.

Clustering Transfer Learning

Distribution-Free Predictive Inference under Unknown Temporal Drift

1 code implementation10 Jun 2024 Elise Han, Chengpiao Huang, Kaizheng Wang

Distribution-free prediction sets play a pivotal role in uncertainty quantification for complex statistical models.

Uncertainty Quantification

Credal Wrapper of Model Averaging for Uncertainty Estimation on Out-Of-Distribution Detection

no code implementations23 May 2024 Kaizheng Wang, Fabio Cuzzolin, Keivan Shariatmadar, David Moens, Hans Hallez

This paper presents an innovative approach, called credal wrapper, to formulating a credal set representation of model averaging for Bayesian neural networks (BNNs) and deep ensembles, capable of improving uncertainty estimation in classification tasks.

Out-of-Distribution Detection Out of Distribution (OOD) Detection

Model Assessment and Selection under Temporal Distribution Shift

1 code implementation13 Feb 2024 Elise Han, Chengpiao Huang, Kaizheng Wang

We investigate model assessment and selection in a changing environment, by synthesizing datasets from both the current time period and historical epochs.

Model Selection

A Stability Principle for Learning under Non-Stationarity

no code implementations27 Oct 2023 Chengpiao Huang, Kaizheng Wang

We develop a versatile framework for statistical learning in non-stationary environments.

Random-Set Neural Networks (RS-NN)

no code implementations11 Jul 2023 Shireen Kudukkil Manchingal, Muhammad Mubashar, Kaizheng Wang, Keivan Shariatmadar, Fabio Cuzzolin

RS-NN encodes the 'epistemic' uncertainty induced in machine learning by limited training sets via the size of the credal sets associated with the predicted belief functions.

Out of Distribution (OOD) Detection

Pseudo-Labeling for Kernel Ridge Regression under Covariate Shift

1 code implementation20 Feb 2023 Kaizheng Wang

We develop and analyze a principled approach to kernel ridge regression under covariate shift.

Imputation Missing Labels +2

Cascaded information enhancement and cross-modal attention feature fusion for multispectral pedestrian detection

no code implementations17 Feb 2023 Yang Yang, Kaixiong Xu, Kaizheng Wang

On the other hand, the cross-modal attention feature fusion module mines the features of both Color and Thermal modalities to complement each other, then the global features are constructed by adding the cross-modal complemented features element by element, which are attentionally weighted to achieve the effective fusion of the two modal features.

Pedestrian Detection

Learning Gaussian Mixtures Using the Wasserstein-Fisher-Rao Gradient Flow

no code implementations4 Jan 2023 Yuling Yan, Kaizheng Wang, Philippe Rigollet

Gaussian mixture models form a flexible and expressive parametric family of distributions that has found applications in a wide variety of applications.

Variable Clustering via Distributionally Robust Nodewise Regression

no code implementations15 Dec 2022 Kaizheng Wang, Xiao Xu, Xun Yu Zhou

We study a multi-factor block model for variable clustering and connect it to the regularized subspace clustering by formulating a distributionally robust version of the nodewise regression.

Clustering regression

An introduction to optimization under uncertainty -- A short survey

no code implementations1 Dec 2022 Keivan Shariatmadar, Kaizheng Wang, Calvin R. Hubbard, Hans Hallez, David Moens

The goal of this survey paper is to briefly touch upon the state of the art in a variety of different methods and refer the reader to other literature for more in-depth treatments of the topics discussed here.

Survey

Adaptive Data Fusion for Multi-task Non-smooth Optimization

no code implementations22 Oct 2022 Henry Lam, Kaizheng Wang, Yuhang Wu, Yichen Zhang

We study the problem of multi-task non-smooth optimization that arises ubiquitously in statistical learning, decision-making and risk management.

Decision Making Management

Adaptive and Robust Multi-Task Learning

1 code implementation10 Feb 2022 Yaqi Duan, Kaizheng Wang

We study the multi-task learning problem that aims to simultaneously analyze multiple datasets collected from different sources and learn one model for each of them.

Multi-Task Learning

Clustering a Mixture of Gaussians with Unknown Covariance

no code implementations4 Oct 2021 Damek Davis, Mateo Díaz, Kaizheng Wang

We investigate a clustering problem with data from a mixture of Gaussians that share a common but unknown, and potentially ill-conditioned, covariance matrix.

Clustering

Robust state and protection-level estimation within tightly coupled GNSS/INS navigation system

no code implementations19 Mar 2021 Shuchen Liu, Kaizheng Wang, Dirk Abel

In autonomous applications for mobility and transport, a high-rate and highly accurate vehicle-state estimation is achieved by fusing measurements of global navigation satellite systems (GNSS) and inertial sensors.

Fault Detection valid

An $\ell_p$ theory of PCA and spectral clustering

no code implementations24 Jun 2020 Emmanuel Abbe, Jianqing Fan, Kaizheng Wang

Principal Component Analysis (PCA) is a powerful tool in statistics and machine learning.

Clustering Community Detection

Efficient Clustering for Stretched Mixtures: Landscape and Optimality

no code implementations NeurIPS 2020 Kaizheng Wang, Yuling Yan, Mateo Díaz

This paper considers a canonical clustering problem where one receives unlabeled samples drawn from a balanced mixture of two elliptical distributions and aims for a classifier to estimate the labels.

Clustering

Some compact notations for concentration inequalities and user-friendly results

no code implementations31 Dec 2019 Kaizheng Wang

This paper presents compact notations for concentration inequalities and convenient results to streamline probabilistic analysis.

Communication-Efficient Accurate Statistical Estimation

no code implementations12 Jun 2019 Jianqing Fan, Yongyi Guo, Kaizheng Wang

In addition, we give the conditions under which the one-step CEASE estimator is statistically efficient.

Distributed Optimization

Robust high dimensional factor models with applications to statistical machine learning

no code implementations12 Aug 2018 Jianqing Fan, Kaizheng Wang, Yiqiao Zhong, Ziwei Zhu

Factor models are a class of powerful statistical models that have been widely used to deal with dependent measurements that arise frequently from various applications from genomics and neuroscience to economics and finance.

BIG-bench Machine Learning Model Selection +1

Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval and Matrix Completion

no code implementations ICML 2018 Cong Ma, Kaizheng Wang, Yuejie Chi, Yuxin Chen

Focusing on two statistical estimation problems, i. e. solving random quadratic systems of equations and low-rank matrix completion, we establish that gradient descent achieves near-optimal statistical and computational guarantees without explicit regularization.

Low-Rank Matrix Completion Retrieval

Spectral Method and Regularized MLE Are Both Optimal for Top-$K$ Ranking

no code implementations31 Jul 2017 Yuxin Chen, Jianqing Fan, Cong Ma, Kaizheng Wang

This paper is concerned with the problem of top-$K$ ranking from pairwise comparisons.

Factor-Adjusted Regularized Model Selection

1 code implementation27 Dec 2016 Jianqing Fan, Yuan Ke, Kaizheng Wang

This paper studies model selection consistency for high dimensional sparse regression when data exhibits both cross-sectional and serial dependency.

Methodology

Cannot find the paper you are looking for? You can Submit a new open access paper.