
Adversarial Deep Embedded Clustering: on a better tradeoff between Feature Randomness and Feature Drift
Clustering using deep autoencoders has been thoroughly investigated in r...
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Identifying Irregular Power Usage by Turning Predictions into Holographic Spatial Visualizations
Power grids are critical infrastructure assets that face nontechnical l...
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Is Big Data Sufficient for a Reliable Detection of NonTechnical Losses?
Nontechnical losses (NTL) occur during the distribution of electricity ...
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AWard_pe̱ṯa̱: Effective hierarchical clustering using the Minkowski metric and a fast k means initialisation
In this paper we make two novel contributions to hierarchical clustering...
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GalaxyX: A Novel Approach for Multiclass Classification in an Open Universe
Classification is a fundamental task in machine learning and artificial ...
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Efficient Partial Order CDCL Using Assertion Level Choice Heuristics
We previously designed Partial Order Conflict Driven Clause Learning (PO...
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Graphical Probabilistic Routing Model for OBS Networks with Realistic Traffic Scenario
Burst contention is a wellknown challenging problem in Optical Burst Sw...
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Spatial point processes intensity estimation with a diverging number of covariates
Feature selection procedures for spatial point processes parametric inte...
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An Efficient Bayesian Robust Principal Component Regression
Principal component regression is a linear regression model with princip...
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PGR: A Graph Repository of Protein 3DStructures
Graph theory and graph mining constitute rich fields of computational te...
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On the Reduction of Biases in Big Data Sets for the Detection of Irregular Power Usage
In machine learning, a bias occurs whenever training sets are not repres...
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Bayesian inference for bivariate ranks
A recommender system based on ranks is proposed, where an expert's ranki...
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What Should You Know Before Developing a Service Identification Approach
In this paper, we answer a set of research questions that are required t...
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Identifying KDM Model of JSP Pages
In this report, we propose our approach that identifies a KDM model of J...
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A Static Program Slicing Approach for Output Stream Objects in JEE Applications
In this paper, we propose a program slicing approach for the output stre...
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How to Implement Dependencies in Server Pages of JEE Web Applications
Java Enterprise Edition (JEE) applications are implemented in terms of a...
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Bayesian Nonparametrics for Directional Statistics
A density basis of the trigonometric polynomials, suitable for mixture m...
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On generalized Lyndon words
A generalized lexicographical order on infinite words is defined by choo...
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A Claim Score for Dynamic Claim Counts Modeling
We develop a claim score based on the BonusMalus approach proposed by [...
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Sequence to Sequence Learning for Query Expansion
Using sequence to sequence algorithms for query expansion has not been e...
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Secondorder variational equations for spatial point processes with a view to pair correlation function estimation
Secondorder variational type equations for spatial point processes are ...
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The median of a jittered Poisson distribution
Let N_λ and U be two independent random variables respectively distribut...
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Fairwashing: the risk of rationalization
Blackbox explanation is the problem of explaining how a machine learnin...
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Privacy of trajectory microdata : a survey
We survey the literature on the privacy of trajectory microdata, i.e., ...
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Some variations on Lyndon words
In this paper we compare two finite words u and v by the lexicographical...
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Joint Learning of PreTrained and Random Units for Domain Adaptation in PartofSpeech Tagging
Finetuning neural networks is widely used to transfer valuable knowledg...
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On Byzantine Fault Tolerance in MultiMaster Kubernertes Clusters
Docker container virtualization technology is being widely adopted in cl...
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Joint Caching and Resource Allocation in D2DAssisted Wireless HetNet
5G networks are required to provide very fast and reliable communication...
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Quasiautomatic semigroups
A quasiautomatic semigroup is defi0ned by a finite set of generators, a...
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Agnostic data debiasing through a local sanitizer learnt from an adversarial network approach
The widespread use of automated decision processes in many areas of our ...
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Multiplicative Models for Recurrent Language Modeling
Recently, there has been interest in multiplicative recurrent neural net...
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Optimal transport on large networks a practitioner guide
This article presents a set of tools for the modeling of a spatial alloc...
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Learning Fair Rule Lists
The widespread use of machine learning models, especially within the con...
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Efficient and Robust Estimation of Linear Regression with Normal Errors
Linear regression with normally distributed errors  including particula...
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Supporting supervised learning in fungal Biosynthetic Gene Cluster discovery: new benchmark datasets
Fungal Biosynthetic Gene Clusters (BGCs) of secondary metabolites are cl...
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Reinforcement Learning in Economics and Finance
Reinforcement learning algorithms describe how an agent can learn an opt...
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A class of copulae associated with Brownian motion processes and their maxima
The main objective of this paper consists in creating a new class of cop...
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On the Applicability of ML Fairness Notions
MLbased predictive systems are increasingly used to support decisions w...
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Online publication of court records: circumventing the privacytransparency tradeoff
The open data movement is leading to the massive publishing of court rec...
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Costsensitive Multiclass AdaBoost for Understanding Driving Behavior with Telematics
Powered with telematics technology, insurers can now capture a wide rang...
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Bit Error Rate Analysis for Reconfigurable Intelligent Surfaces with Phase Errors
In this paper, we analyze the error probability of reconfigurable intell...
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Eternal kdomination on graphs
Eternal domination is a dynamic process by which a graph is protected fr...
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Exploring the Representational Power of Graph Autoencoder
While representation learning has yielded a great success on many graph ...
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Predicting Drought and Subsidence Risks in France
The economic consequences of drought episodes are increasingly important...
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