Search Results for author: Yun Yang

Found 31 papers, 5 papers with code

Skyformer: Remodel Self-Attention with Gaussian Kernel and Nyström Method

1 code implementation NeurIPS 2021 Yifan Chen, Qi Zeng, Heng Ji, Yun Yang

Transformers are expensive to train due to the quadratic time and space complexity in the self-attention mechanism.

Learning Topic Models: Identifiability and Finite-Sample Analysis

no code implementations8 Oct 2021 Yinyin Chen, Shishuang He, Yun Yang, Feng Liang

Topic models provide a useful text-mining tool for learning, extracting and discovering latent structures in large text corpora.

Topic Models

Regret Lower Bound and Optimal Algorithm for High-Dimensional Contextual Linear Bandit

no code implementations23 Sep 2021 Ke Li, Yun Yang, Naveen N. Narisetty

This new lower bound unifies existing regret bound results that have different dependencies on T due to the use of different values of margin parameter $\alpha$ explicitly implied by their assumptions.

AdvDrop: Adversarial Attack to DNNs by Dropping Information

1 code implementation ICCV 2021 Ranjie Duan, Yuefeng Chen, Dantong Niu, Yun Yang, A. K. Qin, Yuan He

Human can easily recognize visual objects with lost information: even losing most details with only contour reserved, e. g. cartoon.

Adversarial Attack Adversarial Robustness

Skyformer: Remodel Self-Attention with Gaussian Kernel and Nystr\"om Method

1 code implementation NeurIPS 2021 Yifan Chen, Qi Zeng, Heng Ji, Yun Yang

Transformers are expensive to train due to the quadratic time and space complexity in the self-attention mechanism.

Adversarial Laser Beam: Effective Physical-World Attack to DNNs in a Blink

1 code implementation CVPR 2021 Ranjie Duan, Xiaofeng Mao, A. K. Qin, Yun Yang, Yuefeng Chen, Shaokai Ye, Yuan He

Though it is well known that the performance of deep neural networks (DNNs) degrades under certain light conditions, there exists no study on the threats of light beams emitted from some physical source as adversarial attacker on DNNs in a real-world scenario.

Adversarial Attack

Fast Statistical Leverage Score Approximation in Kernel Ridge Regression

no code implementations9 Mar 2021 Yifan Chen, Yun Yang

Nystr\"om approximation is a fast randomized method that rapidly solves kernel ridge regression (KRR) problems through sub-sampling the n-by-n empirical kernel matrix appearing in the objective function.

Accumulations of Projections--A Unified Framework for Random Sketches in Kernel Ridge Regression

no code implementations6 Mar 2021 Yifan Chen, Yun Yang

Building a sketch of an n-by-n empirical kernel matrix is a common approach to accelerate the computation of many kernel methods.

Multi-Knowledge Fusion for New Feature Generation in Generalized Zero-Shot Learning

no code implementations23 Feb 2021 Hongxin Xiang, Cheng Xie, Ting Zeng, Yun Yang

Suffering from the semantic insufficiency and domain-shift problems, most of existing state-of-the-art methods fail to achieve satisfactory results for Zero-Shot Learning (ZSL).

Generalized Zero-Shot Learning

Cross Knowledge-based Generative Zero-Shot Learning Approach with Taxonomy Regularization

no code implementations25 Jan 2021 Cheng Xie, Hongxin Xiang, Ting Zeng, Yun Yang, Beibei Yu, Qing Liu

CKL enables more relevant semantic features to be trained for semantic-to-visual feature embedding in ZSL, while Taxonomy Regularization (TR) significantly improves the intersections with unseen images with more generalized visual features generated from generative network.

Image Classification Zero-Shot Learning

MFL_COVID19: Quantifying Country-based Factors affecting Case Fatality Rate in Early Phase of COVID-19 Epidemic via Regularised Multi-task Feature Learning

no code implementations6 Sep 2020 Po Yang, Jun Qi, Xulong Wang, Yun Yang

The fused sparse group Lasso (FSGL) method allows the simultaneous selection of a common set of country-based factors for multiple time points of COVID-19 epidemic and also enables incorporating temporal smoothness of each factor over the whole early phase period.

Feature Selection Multi-Task Learning

Hyperspectral Images Classification Based on Multi-scale Residual Network

no code implementations26 Apr 2020 Xiangdong Zhang, Tengjun Wang, Yun Yang

Because hyperspectral remote sensing images contain a lot of redundant information and the data structure is highly non-linear, leading to low classification accuracy of traditional machine learning methods.

Classification General Classification +1

Distributed Estimation for Principal Component Analysis: an Enlarged Eigenspace Analysis

no code implementations5 Apr 2020 Xi Chen, Jason D. Lee, He Li, Yun Yang

To abandon this eigengap assumption, we consider a new route in our analysis: instead of exactly identifying the top-$L$-dim eigenspace, we show that our estimator is able to cover the targeted top-$L$-dim population eigenspace.

Cutoff for exact recovery of Gaussian mixture models

no code implementations5 Jan 2020 Xiaohui Chen, Yun Yang

We determine the information-theoretic cutoff value on separation of cluster centers for exact recovery of cluster labels in a $K$-component Gaussian mixture model with equal cluster sizes.

Statistical Inference in Mean-Field Variational Bayes

no code implementations4 Nov 2019 Wei Han, Yun Yang

We conduct non-asymptotic analysis on the mean-field variational inference for approximating posterior distributions in complex Bayesian models that may involve latent variables.

Variational Inference

Cutting the Unnecessary Long Tail: Cost-Effective Big Data Clustering in the Cloud

no code implementations22 Sep 2019 Dongwei Li, Shuliang Wang, Nan Gao, Qiang He, Yun Yang

A novel approach is proposed to achieve cost-effective big data clustering in the cloud.

Implicit Regularization via Hadamard Product Over-Parametrization in High-Dimensional Linear Regression

no code implementations22 Mar 2019 Peng Zhao, Yun Yang, Qiao-Chu He

We consider Hadamard product parametrization as a change-of-variable (over-parametrization) technique for solving least square problems in the context of linear regression.

Diffusion $K$-means clustering on manifolds: provable exact recovery via semidefinite relaxations

no code implementations11 Mar 2019 Xiaohui Chen, Yun Yang

We show that exact recovery of the localized diffusion $K$-means is fully adaptive to the local probability density and geometric structures of the underlying submanifolds.

On Statistical Optimality of Variational Bayes

no code implementations25 Dec 2017 Debdeep Pati, Anirban Bhattacharya, Yun Yang

The article addresses a long-standing open problem on the justification of using variational Bayes methods for parameter estimation.

Bayesian Inference

$α$-Variational Inference with Statistical Guarantees

no code implementations9 Oct 2017 Yun Yang, Debdeep Pati, Anirban Bhattacharya

We propose a family of variational approximations to Bayesian posterior distributions, called $\alpha$-VB, with provable statistical guarantees.

Variational Inference

Frequentist coverage and sup-norm convergence rate in Gaussian process regression

no code implementations16 Aug 2017 Yun Yang, Anirban Bhattacharya, Debdeep Pati

By developing a comparison inequality between two GPs, we provide exact characterization of frequentist coverage probabilities of Bayesian point-wise credible intervals and simultaneous credible bands of the regression function.

Statistical inference for high dimensional regression via Constrained Lasso

no code implementations17 Apr 2017 Yun Yang

The proposed estimator, called Constrained Lasso (CLasso) estimator, is obtained by simultaneously solving two estimating equations---one imposing a zero-bias constraint for the low-dimensional parameter and the other forming an $\ell_1$-penalized procedure for the high-dimensional nuisance parameter.

Bayesian model selection consistency and oracle inequality with intractable marginal likelihood

no code implementations2 Jan 2017 Yun Yang, Debdeep Pati

In this article, we investigate large sample properties of model selection procedures in a general Bayesian framework when a closed form expression of the marginal likelihood function is not available or a local asymptotic quadratic approximation of the log-likelihood function does not exist.

Gaussian Processes Model Selection

Communication-Efficient Distributed Statistical Inference

no code implementations25 May 2016 Michael. I. Jordan, Jason D. Lee, Yun Yang

CSL provides a communication-efficient surrogate to the global likelihood that can be used for low-dimensional estimation, high-dimensional regularized estimation and Bayesian inference.

Bayesian Inference

Joint estimation of quantile planes over arbitrary predictor spaces

no code implementations11 Jul 2015 Yun Yang, Surya Tokdar

In spite of the recent surge of interest in quantile regression, joint estimation of linear quantile planes remains a great challenge in statistics and econometrics.

On the Computational Complexity of High-Dimensional Bayesian Variable Selection

no code implementations29 May 2015 Yun Yang, Martin J. Wainwright, Michael. I. Jordan

We study the computational complexity of Markov chain Monte Carlo (MCMC) methods for high-dimensional Bayesian linear regression under sparsity constraints.

Variable Selection

Randomized sketches for kernels: Fast and optimal non-parametric regression

no code implementations25 Jan 2015 Yun Yang, Mert Pilanci, Martin J. Wainwright

Kernel ridge regression (KRR) is a standard method for performing non-parametric regression over reproducing kernel Hilbert spaces.

Minimax Optimal Bayesian Aggregation

no code implementations6 Mar 2014 Yun Yang, David B. Dunson

It is generally believed that ensemble approaches, which combine multiple algorithms or models, can outperform any single algorithm at machine learning tasks, such as prediction.

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