b'Peng Zhao'

research

∙ 08/26/2022

Dynamic Regret of Online Markov Decision Processes

We investigate online Markov Decision Processes (MDPs) with adversariall...

Peng Zhao, et al. ∙

research

∙ 08/18/2022

Matrix Quantile Factor Model

In this paper, we introduce a matrix quantile factor model for matrix se...

Xin-bing Kong, et al. ∙

research

∙ 07/05/2022

Adapting to Online Label Shift with Provable Guarantees

The standard supervised learning paradigm works effectively when trainin...

Yong Bai, et al. ∙

research

∙ 06/02/2022

FACM: Correct the Output of Deep Neural Network with Middle Layers Features against Adversarial Samples

In the strong adversarial attacks against deep neural network (DNN), the...

Xiangyuan Yang, et al. ∙

research

∙ 06/02/2022

Mask-Guided Divergence Loss Improves the Generalization and Robustness of Deep Neural Network

Deep neural network (DNN) with dropout can be regarded as an ensemble mo...

Xiangyuan Yang, et al. ∙

research

∙ 05/19/2022

Enhancing the Transferability of Adversarial Examples via a Few Queries

Due to the vulnerability of deep neural networks, the black-box attack h...

Xiangyuan Yang, et al. ∙

research

∙ 05/05/2022

Contrastive Multi-view Hyperbolic Hierarchical Clustering

Hierarchical clustering recursively partitions data at an increasingly f...

Fangfei Lin, et al. ∙

research

∙ 02/12/2022

Corralling a Larger Band of Bandits: A Case Study on Switching Regret for Linear Bandits

We consider the problem of combining and learning over a set of adversar...

Haipeng Luo, et al. ∙

research

∙ 02/12/2022

Adaptive Bandit Convex Optimization with Heterogeneous Curvature

We consider the problem of adversarial bandit convex optimization, that ...

Haipeng Luo, et al. ∙

research

∙ 01/30/2022

No-Regret Learning in Time-Varying Zero-Sum Games

Learning from repeated play in a fixed two-player zero-sum game is a cla...

Mengxiao Zhang, et al. ∙

research

∙ 12/29/2021

Adaptivity and Non-stationarity: Problem-dependent Dynamic Regret for Online Convex Optimization

We investigate online convex optimization in non-stationary environments...

Peng Zhao, et al. ∙

research

∙ 12/14/2021

EMDS-6: Environmental Microorganism Image Dataset Sixth Version for Image Denoising, Segmentation, Feature Extraction, Classification and Detection Methods Evaluation

Environmental microorganisms (EMs) are ubiquitous around us and have an ...

Peng Zhao, et al. ∙

research

∙ 10/11/2021

EMDS-7: Environmental Microorganism Image Dataset Seventh Version for Multiple Object Detection Evaluation

The Environmental Microorganism Image Dataset Seventh Version (EMDS-7) i...

Hechen Yang, et al. ∙

research

∙ 07/16/2021

A Comparison of Deep Learning Classification Methods on Small-scale Image Data set: from Convolutional Neural Networks to Visual Transformers

In recent years, deep learning has made brilliant achievements in image ...

Peng Zhao, et al. ∙

research

∙ 06/22/2021

A Comparison for Patch-level Classification of Deep Learning Methods on Transparent Images: from Convolutional Neural Networks to Visual Transformers

Nowadays, analysis of transparent images in the field of computer vision...

Hechen Yang, et al. ∙

research

∙ 06/04/2021

Optimal Rates of (Locally) Differentially Private Heavy-tailed Multi-Armed Bandits

In this paper we study the problem of stochastic multi-armed bandits (MA...

Youming Tao, et al. ∙

research

∙ 06/03/2021

A Comparison for Anti-noise Robustness of Deep Learning Classification Methods on a Tiny Object Image Dataset: from Convolutional Neural Network to Visual Transformer and Perfo

Image classification has achieved unprecedented advance with the the rap...

Ao Chen, et al. ∙

research

∙ 03/22/2021

Large Motion Video Super-Resolution with Dual Subnet and Multi-Stage Communicated Upsampling

Video super-resolution (VSR) aims at restoring a video in low-resolution...

Hongying Liu, et al. ∙

research

∙ 03/15/2021

Modeling Multivariate Cyber Risks: Deep Learning Dating Extreme Value Theory

Modeling cyber risks has been an important but challenging task in the d...

Mingyue Zhang Wu, et al. ∙

research

∙ 03/09/2021

Non-stationary Linear Bandits Revisited

In this note, we revisit non-stationary linear bandits, a variant of sto...

Peng Zhao, et al. ∙

research

∙ 02/07/2021

Non-stationary Online Learning with Memory and Non-stochastic Control

We study the problem of Online Convex Optimization (OCO) with memory, wh...

Peng Zhao, et al. ∙

research

∙ 10/09/2020

Latent Dirichlet Allocation Model Training with Differential Privacy

Latent Dirichlet Allocation (LDA) is a popular topic modeling technique ...

Fangyuan Zhao, et al. ∙

research

∙ 08/24/2020

A Single Frame and Multi-Frame Joint Network for 360-degree Panorama Video Super-Resolution

Spherical videos, also known as 360 (panorama) videos, can be viewed wit...

Hongying Liu, et al. ∙

research

∙ 07/25/2020

Video Super Resolution Based on Deep Learning: A comprehensive survey

In recent years, deep learning has made great progress in the fields of ...

Hongying Liu, et al. ∙

research

∙ 07/22/2020

Storage Fit Learning with Feature Evolvable Streams

Feature evolvable learning has been widely studied in recent years where...

Bo-Jian Hou, et al. ∙

research

∙ 07/07/2020

Dynamic Regret of Convex and Smooth Functions

We investigate online convex optimization in non-stationary environments...

Peng Zhao, et al. ∙

research

∙ 06/10/2020

Improved Analysis for Dynamic Regret of Strongly Convex and Smooth Functions

In this paper, we present an improved analysis for dynamic regret of str...

Peng Zhao, et al. ∙

research

∙ 05/04/2020

CDC: Classification Driven Compression for Bandwidth Efficient Edge-Cloud Collaborative Deep Learning

The emerging edge-cloud collaborative Deep Learning (DL) paradigm aims a...

Yuanrui Dong, et al. ∙

research

∙ 02/16/2020

Bayesian Spatial Homogeneity Pursuit Regression for Count Value Data

Spatial regression models are ubiquitous in many different areas such as...

Peng Zhao, et al. ∙

research

∙ 02/05/2020

Exploratory Machine Learning with Unknown Unknowns

In conventional supervised learning, a training dataset is given with gr...

Yu-Jie Zhang, et al. ∙

research

∙ 10/21/2019

An Unbiased Risk Estimator for Learning with Augmented Classes

In this paper, we study the problem of learning with augmented classes (...

Yu-Jie Zhang, et al. ∙

research

∙ 07/29/2019

Bandit Convex Optimization in Non-stationary Environments

Bandit Convex Optimization (BCO) is a fundamental framework for modeling...

Peng Zhao, et al. ∙

research

∙ 03/22/2019

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

We consider Hadamard product parametrization as a change-of-variable (ov...

Peng Zhao, et al. ∙

research

∙ 01/17/2019

Background subtraction on depth videos with convolutional neural networks

Background subtraction is a significant component of computer vision sys...

Xueying Wang, et al. ∙

research

∙ 12/16/2018

Auto-tuning Neural Network Quantization Framework for Collaborative Inference Between the Cloud and Edge

Recently, deep neural networks (DNNs) have been widely applied in mobile...

Guangli Li, et al. ∙

research

∙ 09/08/2018

Handling Concept Drift via Model Reuse

In many real-world applications, data are often collected in the form of...

Peng Zhao, et al. ∙

research

∙ 06/08/2017

Distribution-Free One-Pass Learning

In many large-scale machine learning applications, data are accumulated ...

Peng Zhao, et al. ∙

Peng Zhao

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