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Philip S. Yu
299 publications
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134 publications
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∙ 08/04/2023

DIVERSIFY: A General Framework for Time Series Out-of-distribution Detection and Generalization

Time series remains one of the most challenging modalities in machine le...

0 Wang Lu, et al. ∙

∙ 06/30/2023

FedBone: Towards Large-Scale Federated Multi-Task Learning

Heterogeneous federated multi-task learning (HFMTL) is a federated learn...

0 Yiqiang Chen, et al. ∙

∙ 11/07/2022

FIXED: Frustratingly Easy Domain Generalization with Mixup

Domain generalization (DG) aims to learn a generalizable model from mult...

0 Wang Lu, et al. ∙

∙ 09/15/2022

Generalized Representations Learning for Time Series Classification

Time series classification is an important problem in real world. Due to...

0 Wang Lu, et al. ∙

∙ 09/01/2022

Towards Optimization and Model Selection for Domain Generalization: A Mixup-guided Solution

The distribution shifts between training and test data typically undermi...

0 Wang Lu, et al. ∙

∙ 07/25/2022

Domain-invariant Feature Exploration for Domain Generalization

Deep learning has achieved great success in the past few years. However,...

0 Wang Lu, et al. ∙

∙ 07/21/2022

Domain Generalization for Activity Recognition via Adaptive Feature Fusion

Human activity recognition requires the efforts to build a generalizable...

0 Xin Qin, et al. ∙

∙ 06/17/2022

MetaFed: Federated Learning among Federations with Cyclic Knowledge Distillation for Personalized Healthcare

Federated learning has attracted increasing attention to building models...

0 Yiqiang Chen, et al. ∙

∙ 06/14/2022

Semantic-Discriminative Mixup for Generalizable Sensor-based Cross-domain Activity Recognition

It is expensive and time-consuming to collect sufficient labeled data to...

0 Wang Lu, et al. ∙

∙ 01/03/2022

Adaptive Memory Networks with Self-supervised Learning for Unsupervised Anomaly Detection

Unsupervised anomaly detection aims to build models to effectively detec...

0 Yuxin Zhang, et al. ∙

∙ 12/01/2021

Federated Learning with Adaptive Batchnorm for Personalized Healthcare

There is a growing interest in applying machine learning techniques for ...

0 Yiqiang Chen, et al. ∙

∙ 07/27/2021

Unsupervised Deep Anomaly Detection for Multi-Sensor Time-Series Signals

Nowadays, multi-sensor technologies are applied in many fields, e.g., He...

17 Yuxin Zhang, et al. ∙

∙ 06/02/2021

FedHealth 2: Weighted Federated Transfer Learning via Batch Normalization for Personalized Healthcare

The success of machine learning applications often needs a large quantit...

0 Yiqiang Chen, et al. ∙

∙ 10/17/2020

Secure Weighted Aggregation in Federated Learning

Federated learning (FL) schemes enable multiple clients to jointly solve...

0 Jiale Guo, et al. ∙

∙ 07/17/2020

Learning to Match Distributions for Domain Adaptation

When the training and test data are from different distributions, domain...

11 Chaohui Yu, et al. ∙

∙ 01/29/2020

FOCUS: Dealing with Label Quality Disparity in Federated Learning

Ubiquitous systems with End-Edge-Cloud architecture are increasingly bei...

0 Yiqiang Chen, et al. ∙

∙ 09/18/2019

Transfer Learning with Dynamic Adversarial Adaptation Network

The recent advances in deep transfer learning reveal that adversarial le...

0 Chaohui Yu, et al. ∙

∙ 09/17/2019

Transfer Learning with Dynamic Distribution Adaptation

Transfer learning aims to learn robust classifiers for the target domain...

7 Jindong Wang, et al. ∙

∙ 07/22/2019

FedHealth: A Federated Transfer Learning Framework for Wearable Healthcare

With the rapid development of computing technology, wearable devices suc...

0 Yiqiang Chen, et al. ∙

∙ 07/05/2019

A Mobile Cloud Collaboration Fall Detection System Based on Ensemble Learning

Falls are one of the important causes of accidental or unintentional inj...

0 Tong Wu, et al. ∙

∙ 04/02/2019

Easy Transfer Learning By Exploiting Intra-domain Structures

Transfer learning aims at transferring knowledge from a well-labeled dom...

18 Jindong Wang, et al. ∙

∙ 07/20/2018

Deep Transfer Learning for Cross-domain Activity Recognition

Human activity recognition plays an important role in people's daily lif...

0 Jindong Wang, et al. ∙

∙ 07/19/2018

Visual Domain Adaptation with Manifold Embedded Distribution Alignment

Visual domain adaptation aims to learn robust classifiers for the target...

6 Jindong Wang, et al. ∙

∙ 07/02/2018

Balanced Distribution Adaptation for Transfer Learning

Transfer learning has achieved promising results by leveraging knowledge...

0 Jindong Wang, et al. ∙

∙ 06/26/2018

Cross-position Activity Recognition with Stratified Transfer Learning

Human activity recognition aims to recognize the activities of daily liv...

0 Yiqiang Chen, et al. ∙

∙ 12/25/2017

Stratified Transfer Learning for Cross-domain Activity Recognition

In activity recognition, it is often expensive and time-consuming to acq...

0 Jindong Wang, et al. ∙

∙ 07/12/2017

Deep Learning for Sensor-based Activity Recognition: A Survey

Sensor-based activity recognition seeks the profound high-level knowledg...

0 Jindong Wang, et al. ∙

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