b'Yang Lu'

research

∙ 04/30/2022

FEDIC: Federated Learning on Non-IID and Long-Tailed Data via Calibrated Distillation

Federated learning provides a privacy guarantee for generating good deep...

Xinyi Shang, et al. ∙

research

∙ 04/28/2022

Federated Learning on Heterogeneous and Long-Tailed Data via Classifier Re-Training with Federated Features

Federated learning (FL) provides a privacy-preserving solution for distr...

Xinyi Shang, et al. ∙

research

∙ 04/26/2022

Fast Successive-Cancellation Decoding of Polar Codes with Sequence Nodes

Due to the sequential nature of the successive-cancellation (SC) algorit...

Yang Lu, et al. ∙

research

∙ 02/17/2022

A Deep Learning Approach for Repairing Missing Activity Labels in Event Logs for Process Mining

Process mining is a relatively new subject that builds a bridge between ...

Yang Lu, et al. ∙

research

∙ 10/18/2021

A simple Bayesian state-space model for the collective risk model

The collective risk model (CRM) for frequency and severity is an importa...

Jae Youn Ahn, et al. ∙

research

∙ 09/16/2021

On the ordering of credibility factors

Traditional credibility analysis of risks in insurance is based on the r...

Jae Youn Ahn, et al. ∙

research

∙ 08/31/2021

AIP: Adversarial Iterative Pruning Based on Knowledge Transfer for Convolutional Neural Networks

With the increase of structure complexity, convolutional neural networks...

Jingfei Chang, et al. ∙

research

∙ 06/24/2021

A Novel Approach to Discover Switch Behaviours in Process Mining

Process mining is a relatively new subject which builds a bridge between...

Yang Lu, et al. ∙

research

∙ 04/29/2021

Digital Resistance during COVID-19: A Workflow Management System of Contactless Purchasing and Its Empirical Study of Customer Acceptance

The COVID-19 pandemic has stimulated the shift of work and life from the...

Yang Lu, et al. ∙

research

∙ 03/30/2021

A Novel Approach to Detect Redundant Activity Labels For More Representative Event Logs

The insights revealed from process mining heavily rely on the quality of...

Qifan Chen, et al. ∙

research

∙ 03/19/2021

A Robust and Accurate Approach to Detect Process Drifts from Event Streams

Business processes are bound to evolve as a form of adaption to changes,...

Yang Lu, et al. ∙

research

∙ 03/19/2021

Detecting and Understanding Branching Frequency Changes in Process Models

Business processes are continuously evolving in order to adapt to change...

Yang Lu, et al. ∙

research

∙ 03/19/2021

Discovering Redundant Activities in Event Logs for the Simplification of Process Models

Process mining acts as a valuable tool to analyse the behaviour of an or...

Qifan Chen, et al. ∙

research

∙ 03/03/2021

Self-Distribution Binary Neural Networks

In this work, we study the binary neural networks (BNNs) of which both t...

Ping Xue, et al. ∙

research

∙ 01/16/2021

ACP: Automatic Channel Pruning via Clustering and Swarm Intelligence Optimization for CNN

As the convolutional neural network (CNN) gets deeper and wider in recen...

Jingfei Chang, et al. ∙

research

∙ 11/16/2020

SIR Model with Stochastic Transmission

The Susceptible-Infected-Recovered (SIR) model is the cornerstone of epi...

Christian Gourieroux, et al. ∙

research

∙ 11/15/2020

Placement in Integrated Circuits using Cyclic Reinforcement Learning and Simulated Annealing

Physical design and production of Integrated Circuits (IC) is becoming i...

Dhruv Vashisht, et al. ∙

research

∙ 10/03/2020

UCP: Uniform Channel Pruning for Deep Convolutional Neural Networks Compression and Acceleration

To apply deep CNNs to mobile terminals and portable devices, many schola...

Jingfei Chang, et al. ∙

research

∙ 08/01/2020

Cyber-Resilient Transactive Energy System Design over Insecure Communication Links

In this paper, the privacy and security issues associated with transacti...

Yang Lu, et al. ∙

research

∙ 07/06/2020

Computational Complexity Characterization of Protecting Elections from Bribery

The bribery problem in election has received considerable attention in t...

Lin Chen, et al. ∙

research

∙ 02/03/2020

Robust saliency maps with decoy-enhanced saliency score

Saliency methods help to make deep neural network predictions more inter...

Yang Lu, et al. ∙

research

∙ 12/16/2019

On privacy preserving data release of linear dynamic networks

Distributed data sharing in dynamic networks is ubiquitous. It raises th...

Yang Lu, et al. ∙

research

∙ 09/22/2019

From Data Disclosure to Privacy Nudges: A Privacy-aware and User-centric Personal Data Management Framework

Although there are privacy-enhancing tools designed to protect users' on...

Yang Lu, et al. ∙

research

∙ 06/22/2019

Copula Density Estimation by Finite Mixture of Parametric Copula Densities

A Copula density estimation method that is based on a finite mixture of ...

Leming Qu, et al. ∙

research

∙ 05/24/2019

Multi-Scale Dual-Branch Fully Convolutional Network for Hand Parsing

Recently, fully convolutional neural networks (FCNs) have shown signific...

Yang Lu, et al. ∙

research

∙ 04/18/2019

ProductNet: a Collection of High-Quality Datasets for Product Representation Learning

ProductNet is a collection of high-quality product datasets for better p...

Chu Wang, et al. ∙

research

∙ 04/15/2019

Low-Power Computer Vision: Status, Challenges, Opportunities

Computer vision has achieved impressive progress in recent years. Meanwh...

Sergei Alyamkin, et al. ∙

research

∙ 01/29/2019

Bayes Imbalance Impact Index: A Measure of Class Imbalanced Dataset for Classification Problem

Recent studies have shown that imbalance ratio is not the only cause of ...

Yang Lu, et al. ∙

research

∙ 01/26/2019

Optimal Online Transmission Policy in Wireless Powered Networks with Urgency-aware Age of Information

This paper investigates the age of information (AoI) for a radio frequen...

Yang Lu, et al. ∙

research

∙ 12/31/2018

Large-Scale Object Detection of Images from Network Cameras in Variable Ambient Lighting Conditions

Computer vision relies on labeled datasets for training and evaluation i...

Caleb Tung, et al. ∙

research

∙ 10/03/2018

2018 Low-Power Image Recognition Challenge

The Low-Power Image Recognition Challenge (LPIRC, https://rebootingcompu...

Sergei Alyamkin, et al. ∙

research

∙ 05/01/2018

Privacy preserving distributed optimization using homomorphic encryption

This paper studies how a system operator and a set of agents securely ex...

Yang Lu, et al. ∙

research

∙ 09/26/2017

Learning Multi-grid Generative ConvNets by Minimal Contrastive Divergence

This paper proposes a minimal contrastive divergence method for learning...

Ruiqi Gao, et al. ∙

research

∙ 09/29/2016

Cooperative Training of Descriptor and Generator Networks

This paper studies the cooperative training of two probabilistic models ...

Jianwen Xie, et al. ∙

research

∙ 06/28/2016

Alternating Back-Propagation for Generator Network

This paper proposes an alternating back-propagation algorithm for learni...

Tian Han, et al. ∙

research

∙ 02/10/2016

A Theory of Generative ConvNet

We show that a generative random field model, which we call generative C...

Jianwen Xie, et al. ∙

research

∙ 12/19/2014

Generative Modeling of Convolutional Neural Networks

The convolutional neural networks (CNNs) have proven to be a powerful to...

Jifeng Dai, et al. ∙

research

∙ 11/09/2012

LAGE: A Java Framework to reconstruct Gene Regulatory Networks from Large-Scale Continues Expression Data

LAGE is a systematic framework developed in Java. The motivation of LAGE...

Yang Lu, et al. ∙

research

∙ 10/18/2012

LSBN: A Large-Scale Bayesian Structure Learning Framework for Model Averaging

The motivation for this paper is to apply Bayesian structure learning us...

Yang Lu, et al. ∙

Yang Lu

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