
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...
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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,...
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Detecting and Understanding Branching Frequency Changes in Process Models
Business processes are continuously evolving in order to adapt to change...
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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...
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SelfDistribution Binary Neural Networks
In this work, we study the binary neural networks (BNNs) of which both t...
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ACP: Automatic Channel Pruning via Clustering and Swarm Intelligence Optimization for CNN
As the convolutional neural network (CNN) gets deeper and wider in recen...
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SIR Model with Stochastic Transmission
The SusceptibleInfectedRecovered (SIR) model is the cornerstone of epi...
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Placement in Integrated Circuits using Cyclic Reinforcement Learning and Simulated Annealing
Physical design and production of Integrated Circuits (IC) is becoming i...
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UCP: Uniform Channel Pruning for Deep Convolutional Neural Networks Compression and Acceleration
To apply deep CNNs to mobile terminals and portable devices, many schola...
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CyberResilient Transactive Energy System Design over Insecure Communication Links
In this paper, the privacy and security issues associated with transacti...
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Computational Complexity Characterization of Protecting Elections from Bribery
The bribery problem in election has received considerable attention in t...
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Robust saliency maps with decoyenhanced saliency score
Saliency methods help to make deep neural network predictions more inter...
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On privacy preserving data release of linear dynamic networks
Distributed data sharing in dynamic networks is ubiquitous. It raises th...
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From Data Disclosure to Privacy Nudges: A Privacyaware and Usercentric Personal Data Management Framework
Although there are privacyenhancing tools designed to protect users' on...
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Copula Density Estimation by Finite Mixture of Parametric Copula Densities
A Copula density estimation method that is based on a finite mixture of ...
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MultiScale DualBranch Fully Convolutional Network for Hand Parsing
Recently, fully convolutional neural networks (FCNs) have shown signific...
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ProductNet: a Collection of HighQuality Datasets for Product Representation Learning
ProductNet is a collection of highquality product datasets for better p...
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LowPower Computer Vision: Status, Challenges, Opportunities
Computer vision has achieved impressive progress in recent years. Meanwh...
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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 ...
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Optimal Online Transmission Policy in Wireless Powered Networks with Urgencyaware Age of Information
This paper investigates the age of information (AoI) for a radio frequen...
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LargeScale Object Detection of Images from Network Cameras in Variable Ambient Lighting Conditions
Computer vision relies on labeled datasets for training and evaluation i...
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2018 LowPower Image Recognition Challenge
The LowPower Image Recognition Challenge (LPIRC, https://rebootingcompu...
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Privacy preserving distributed optimization using homomorphic encryption
This paper studies how a system operator and a set of agents securely ex...
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Learning Multigrid Generative ConvNets by Minimal Contrastive Divergence
This paper proposes a minimal contrastive divergence method for learning...
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Cooperative Training of Descriptor and Generator Networks
This paper studies the cooperative training of two probabilistic models ...
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Alternating BackPropagation for Generator Network
This paper proposes an alternating backpropagation algorithm for learni...
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A Theory of Generative ConvNet
We show that a generative random field model, which we call generative C...
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Generative Modeling of Convolutional Neural Networks
The convolutional neural networks (CNNs) have proven to be a powerful to...
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LAGE: A Java Framework to reconstruct Gene Regulatory Networks from LargeScale Continues Expression Data
LAGE is a systematic framework developed in Java. The motivation of LAGE...
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LSBN: A LargeScale Bayesian Structure Learning Framework for Model Averaging
The motivation for this paper is to apply Bayesian structure learning us...
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Yang Lu
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