b'Xingyu Li'

research

∙ 08/30/2023

AnoVL: Adapting Vision-Language Models for Unified Zero-shot Anomaly Localization

Contrastive Language-Image Pre-training (CLIP) models have shown promisi...

0 Hanqiu Deng, et al. ∙

research

∙ 08/29/2023

Advancing Adversarial Robustness Through Adversarial Logit Update

Deep Neural Networks are susceptible to adversarial perturbations. Adver...

0 Hao Xuan, et al. ∙

research

∙ 08/07/2023

AdaER: An Adaptive Experience Replay Approach for Continual Lifelong Learning

Continual lifelong learning is an machine learning framework inspired by...

0 Xingyu Li, et al. ∙

research

∙ 08/07/2023

G-Mix: A Generalized Mixup Learning Framework Towards Flat Minima

Deep neural networks (DNNs) have demonstrated promising results in vario...

0 Xingyu Li, et al. ∙

research

∙ 06/20/2023

BMAD: Benchmarks for Medical Anomaly Detection

Anomaly detection (AD) is a fundamental research problem in machine lear...

0 Jinan Bao, et al. ∙

research

∙ 06/16/2023

Inspire creativity with ORIBA: Transform Artists' Original Characters into Chatbots through Large Language Model

This research delves into the intersection of illustration art and artif...

0 Yuqian Sun, et al. ∙

research

∙ 05/03/2023

DPSeq: A Novel and Efficient Digital Pathology Classifier for Predicting Cancer Biomarkers using Sequencer Architecture

In digital pathology tasks, transformers have achieved state-of-the-art ...

0 Min Cen, et al. ∙

research

∙ 04/24/2023

Synthetic Datasets for Autonomous Driving: A Survey

Autonomous driving techniques have been flourishing in recent years whil...

0 Zhihang Song, et al. ∙

research

∙ 03/18/2023

Whole-slide-imaging Cancer Metastases Detection and Localization with Limited Tumorous Data

Recently, various deep learning methods have shown significant successes...

0 Yinsheng He, et al. ∙

research

∙ 02/21/2023

Time to Embrace Natural Language Processing (NLP)-based Digital Pathology: Benchmarking NLP- and Convolutional Neural Network-based Deep Learning Pipelines

NLP-based computer vision models, particularly vision transformers, have...

0 Min Cen, et al. ∙

research

∙ 12/23/2022

RMove: Recommending Move Method Refactoring Opportunities using Structural and Semantic Representations of Code

Incorrect placement of methods within classes is a typical code smell ca...

0 Di Cui, et al. ∙

research

∙ 10/26/2022

Improving Adversarial Robustness with Self-Paced Hard-Class Pair Reweighting

Deep Neural Networks are vulnerable to adversarial attacks. Among many d...

0 Pengyue Hou, et al. ∙

research

∙ 08/16/2022

On the Convergence of Multi-Server Federated Learning with Overlapping Area

Multi-server Federated learning (FL) has been considered as a promising ...

0 Zhe Qu, et al. ∙

research

∙ 06/06/2022

Generalized Federated Learning via Sharpness Aware Minimization

Federated Learning (FL) is a promising framework for performing privacy-...

0 Zhe Qu, et al. ∙

research

∙ 05/31/2022

A robust and lightweight deep attention multiple instance learning algorithm for predicting genetic alterations

Deep-learning models based on whole-slide digital pathology images (WSIs...

0 Bangwei Guo, et al. ∙

research

∙ 05/18/2022

Global Contrast Masked Autoencoders Are Powerful Pathological Representation Learners

Based on digital whole slide scanning technique, artificial intelligence...

0 Hao Quan, et al. ∙

research

∙ 05/01/2022

DDDM: a Brain-Inspired Framework for Robust Classification

Despite their outstanding performance in a broad spectrum of real-world ...

0 Xiyuan Chen, et al. ∙

research

∙ 04/30/2022

SHAPE: An Unified Approach to Evaluate the Contribution and Cooperation of Individual Modalities

As deep learning advances, there is an ever-growing demand for models ca...

0 Pengbo Hu, et al. ∙

research

∙ 04/24/2022

Colorectal cancer survival prediction using deep distribution based multiple-instance learning

Several deep learning algorithms have been developed to predict survival...

0 Xingyu Li, et al. ∙

research

∙ 03/31/2022

Optimize Deep Learning Models for Prediction of Gene Mutations Using Unsupervised Clustering

Deep learning has become the mainstream methodological choice for analyz...

0 Zihan Chen, et al. ∙

research

∙ 02/20/2022

A Unified Nonparametric Test of Transformations on Distribution Functions with Nuisance Parameters

This paper proposes a simple unified approach to testing transformations...

0 Xingyu Li, et al. ∙

research

∙ 01/26/2022

Anomaly Detection via Reverse Distillation from One-Class Embedding

Knowledge distillation (KD) achieves promising results on the challengin...

0 Hanqiu Deng, et al. ∙

research

∙ 01/08/2022

LoMar: A Local Defense Against Poisoning Attack on Federated Learning

Federated learning (FL) provides a high efficient decentralized machine ...

9 Xingyu Li, et al. ∙

research

∙ 01/03/2022

Improving Feature Extraction from Histopathological Images Through A Fine-tuning ImageNet Model

Due to lack of annotated pathological images, transfer learning has been...

15 Xingyu Li, et al. ∙

research

∙ 12/22/2021

FedLGA: Towards System-Heterogeneity of Federated Learning via Local Gradient Approximation

Federated Learning (FL) is a decentralized machine learning architecture...

0 Xingyu Li, et al. ∙

research

∙ 11/21/2021

Denoised Internal Models: a Brain-Inspired Autoencoder against Adversarial Attacks

Despite its great success, deep learning severely suffers from robustnes...

0 Kaiyuan Liu, et al. ∙

research

∙ 11/05/2021

A Retrospective Analysis using Deep-Learning Models for Prediction of Survival Outcome and Benefit of Adjuvant Chemotherapy in Stage II/III Colorectal Cancer

Most early-stage colorectal cancer (CRC) patients can be cured by surger...

22 Xingyu Li, et al. ∙

research

∙ 08/23/2021

CoverTheFace: face covering monitoring and demonstrating using deep learning and statistical shape analysis

Wearing a mask is a strong protection against the COVID-19 pandemic, eve...

16 Yixin Hu, et al. ∙

research

∙ 03/28/2021

On the limits of algorithmic prediction across the globe

The impact of predictive algorithms on people's lives and livelihoods ha...

0 Xingyu Li, et al. ∙

research

∙ 02/12/2021

Blind stain separation using model-aware generative learning and its applications on fluorescence microscopy images

Multiple stains are usually used to highlight biological substances in b...

0 Xingyu Li, et al. ∙

research

∙ 02/12/2021

Stragglers Are Not Disaster: A Hybrid Federated Learning Algorithm with Delayed Gradients

Federated learning (FL) is a new machine learning framework which trains...

0 Xingyu Li, et al. ∙

research

∙ 10/05/2020

Learning with Instance-Dependent Label Noise: A Sample Sieve Approach

Human-annotated labels are often prone to noise, and the presence of suc...

1 Hao Cheng, et al. ∙

research

∙ 07/24/2020

Stain Style Transfer of Histopathology Images Via Structure-Preserved Generative Learning

Computational histopathology image diagnosis becomes increasingly popula...

0 Hanwen Liang, et al. ∙

research

∙ 04/24/2020

How Much Off-The-Shelf Knowledge Is Transferable From Natural Images To Pathology Images?

Deep learning has achieved a great success in natural image classificati...

0 Xingyu Li, et al. ∙

research

∙ 07/02/2019

Analysis of the Synergy between Modularity and Autonomy in an Artificial Intelligence Based Fleet Competition

A novel approach is provided for evaluating the benefits and burdens fro...

0 Xingyu Li, et al. ∙

research

∙ 02/22/2019

Discriminative Pattern Mining for Breast Cancer Histopathology Image Classification via Fully Convolutional Autoencoder

Accurate diagnosis of breast cancer in histopathology images is challeng...

16 Xingyu Li, et al. ∙

research

∙ 02/05/2019

End-to-End Open-Domain Question Answering with BERTserini

We demonstrate an end-to-end question answering system that integrates B...

0 Wei Yang, et al. ∙

research

∙ 11/09/2018

Analysis of Fleet Modularity in an Artificial Intelligence-Based Attacker-Defender Game

Because combat environments change over time and technology upgrades are...

0 Xingyu Li, et al. ∙

Xingyu Li

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