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∙ 07/25/2023

Federated Distributionally Robust Optimization with Non-Convex Objectives: Algorithm and Analysis

Distributionally Robust Optimization (DRO), which aims to find an optima...

0 Yang Jiao, et al. ∙

∙ 03/08/2023

Privacy-preserving and Uncertainty-aware Federated Trajectory Prediction for Connected Autonomous Vehicles

Deep learning is the method of choice for trajectory prediction for auto...

0 Muzi Peng, et al. ∙

∙ 12/20/2022

Asynchronous Distributed Bilevel Optimization

Bilevel optimization plays an essential role in many machine learning ta...

0 Yang Jiao, et al. ∙

∙ 10/14/2022

Distributed Distributionally Robust Optimization with Non-Convex Objectives

Distributionally Robust Optimization (DRO), which aims to find an optima...

0 Yang Jiao, et al. ∙

∙ 05/09/2022

Deep Federated Anomaly Detection for Multivariate Time Series Data

Despite the fact that many anomaly detection approaches have been develo...

0 Wei Zhu, et al. ∙

∙ 01/24/2022

Ordinal-Quadruplet: Retrieval of Missing Classes in Ordinal Time Series

In this paper, we propose an ordered time series classification framewor...

0 Jurijs Nazarovs, et al. ∙

∙ 11/30/2021

Hierarchical Prototype Networks for Continual Graph Representation Learning

Despite significant advances in graph representation learning, little at...

0 Xikun Zhang, et al. ∙

∙ 07/29/2021

Convolutional Transformer based Dual Discriminator Generative Adversarial Networks for Video Anomaly Detection

Detecting abnormal activities in real-world surveillance videos is an im...

0 Xinyang Feng, et al. ∙

∙ 04/08/2021

FACESEC: A Fine-grained Robustness Evaluation Framework for Face Recognition Systems

We present FACESEC, a framework for fine-grained robustness evaluation o...

0 Liang Tong, et al. ∙

∙ 03/26/2021

Unsupervised Document Embedding via Contrastive Augmentation

We present a contrasting learning approach with data augmentation techni...

14 Dongsheng Luo, et al. ∙

∙ 03/03/2021

Dynamic Gaussian Mixture based Deep Generative Model For Robust Forecasting on Sparse Multivariate Time Series

Forecasting on sparse multivariate time series (MTS) aims to model the p...

5 Yinjun Wu, et al. ∙

∙ 10/04/2020

TimeAutoML: Autonomous Representation Learning for Multivariate Irregularly Sampled Time Series

Multivariate time series (MTS) data are becoming increasingly ubiquitous...

19 Yang Jiao, et al. ∙

∙ 12/18/2019

Asymmetrical Hierarchical Networks with Attentive Interactions for Interpretable Review-Based Recommendation

Recently, recommender systems have been able to emit substantially impro...

0 Xin Dong, et al. ∙

∙ 11/20/2018

A Deep Neural Network for Unsupervised Anomaly Detection and Diagnosis in Multivariate Time Series Data

Nowadays, multivariate time series data are increasingly collected in va...

0 Chuxu Zhang, et al. ∙

∙ 12/12/2017

Detecting Low Rating Android Apps Before They Have Reached the Market

Driven by the popularity of the Android system, Android app markets enjo...

0 Ding Li, et al. ∙

∙ 04/07/2017

A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction

The Nonlinear autoregressive exogenous (NARX) model, which predicts the ...

0 Yao Qin, et al. ∙

∙ 02/21/2017

Exemplar-Centered Supervised Shallow Parametric Data Embedding

Metric learning methods for dimensionality reduction in combination with...

0 Martin Renqiang Min, et al. ∙

∙ 08/16/2016

A Shallow High-Order Parametric Approach to Data Visualization and Compression

Explicit high-order feature interactions efficiently capture essential s...

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