
Deep Graph Matching Consensus
This work presents a twostage neural architecture for learning and refi...
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Travel Time Prediction using TreeBased Ensembles
In this paper, we consider the task of predicting travel times between t...
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Hierarchical Graph Representation Learning with Differentiable Pooling
Recently, graph neural networks (GNNs) have revolutionized the field of ...
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SplineCNN: Fast Geometric Deep Learning with Continuous BSpline Kernels
We present Splinebased Convolutional Neural Networks (SplineCNNs), a va...
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The True Destination of EGO is Multilocal Optimization
Efficient global optimization is a popular algorithm for the optimizatio...
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SurrogateAssisted Partial Orderbased Evolutionary Optimisation
In this paper, we propose a novel approach (SAPEO) to support the surviv...
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Price and Profit Awareness in Recommender Systems
Academic research in the field of recommender systems mainly focuses on ...
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A Unifying View of Explicit and Implicit Feature Maps for Structured Data: Systematic Studies of Graph Kernels
Nonlinear kernel methods can be approximated by fast linear ones using ...
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Personalized and situationaware multimodal route recommendations: the FAVOUR algorithm
Route choice in multimodal networks shows a considerable variation betwe...
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Faster Kernels for Graphs with Continuous Attributes via Hashing
While stateoftheart kernels for graphs with discrete labels scale wel...
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StruClus: Structural Clustering of LargeScale Graph Databases
We present a structural clustering algorithm for largescale datasets of...
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Learning Modulo Theories for preference elicitation in hybrid domains
This paper introduces CLEO, a novel preference elicitation algorithm cap...
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Averaged Hausdorff Approximations of Pareto Fronts based on Multiobjective Estimation of Distribution Algorithms
In the a posteriori approach of multiobjective optimization the Pareto f...
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Machine Learning meets DataDriven Journalism: Boosting International Understanding and Transparency in News Coverage
Migration crisis, climate change or tax havens: Global challenges need g...
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On Valid Optimal Assignment Kernels and Applications to Graph Classification
The success of kernel methods has initiated the design of novel positive...
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Mixin Composition Synthesis based on Intersection Types
We present a method for synthesizing compositions of mixins using type i...
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Approximating the Spectrum of a Graph
The spectrum of a network or graph G=(V,E) with adjacency matrix A, cons...
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The Symbolic Interior Point Method
A recent trend in probabilistic inference emphasizes the codification of...
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Prophet Secretary for Combinatorial Auctions and Matroids
The secretary and the prophet inequality problems are central to the fie...
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Solving rankconstrained semidefinite programs in exact arithmetic
We consider the problem of minimizing a linear function over an affine s...
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MIP Formulations for the Steiner Forest Problem
The Steiner Forest problem is among the fundamental network design probl...
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Confidentiality enforcement by hybrid control of information flows
An information owner, possessing diverse data sources, might want to off...
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New Integer Linear Programming Models for the Vertex Coloring Problem
The vertex coloring problem asks for the minimum number of colors that c...
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On Maximum Common Subgraph Problems in SeriesParallel Graphs
The complexity of the maximum common connected subgraph problem in parti...
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Inference for HeavyTailed MaxRenewal Processes
Maxrenewal processes, or Continuous Time Random Maxima, assume that eve...
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Recognizing Cuneiform Signs Using Graph Based Methods
The cuneiform script constitutes one of the earliest systems of writing ...
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Inference for Continuous Time Random Maxima with HeavyTailed Waiting Times
In many complex systems of interest, interarrival times between events ...
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Towards Advanced Phenotypic Mutations in Cartesian Genetic Programming
Cartesian Genetic Programming is often used with a point mutation as the...
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Introduction to Iltis: An Interactive, WebBased System for Teaching Logic
Logic is a foundation for many modern areas of computer science. In arti...
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Reachability and Distances under Multiple Changes
Recently it was shown that the transitive closure of a directed graph ca...
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Peaks Over Threshold for Bursty Time Series
In many complex systems studied in statistical physics, interarrival ti...
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Evolving Mario Levels in the Latent Space of a Deep Convolutional Generative Adversarial Network
Generative Adversarial Networks (GANs) are a machine learning approach c...
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The Crossing Number of SinglePairSeqShellable Drawings of Complete Graphs
The HararyHill Conjecture states that for n≥ 3 every drawing of K_n has...
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On Coresets for Logistic Regression
Coresets are one of the central methods to facilitate the analysis of la...
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Classification Uncertainty of Deep Neural Networks Based on Gradient Information
We study the quantification of uncertainty of Convolutional Neural Netwo...
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A note on blockandbridge preserving maximum common subgraph algorithms for outerplanar graphs
Schietgat, Ramon and Bruynooghe proposed a polynomialtime algorithm for...
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Group Equivariant Capsule Networks
We present group equivariant capsule networks, a framework to introduce ...
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A Flow Formulation for Horizontal Coordinate Assignment with Prescribed Width
We consider the coordinate assignment phase of the well known Sugiyama f...
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Hierarchical Graph Representation Learning withDifferentiable Pooling
Recently, graph neural networks (GNNs) have revolutionized the field of ...
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Expolring Architectures for CNNBased Word Spotting
The goal in word spotting is to retrieve parts of document images which ...
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A First Analysis of Kernels for Krigingbased Optimization in Hierarchical Search Spaces
Many realworld optimization problems require significant resources for ...
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The Crossing Number of SemiPairShellable Drawings of Complete Graphs
The HararyHill Conjecture states that for n≥ 3 every drawing of K_n has...
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Turning Big data into tiny data: Constantsize coresets for kmeans, PCA and projective clustering
We develop and analyze a method to reduce the size of a very large set o...
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Optimal designs for frequentist model averaging
We consider the problem of designing experiments for the estimation of a...
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Probabilistic embeddings of the Fréchet distance
The Fréchet distance is a popular distance measure for curves which natu...
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Optimal designs for twolevel main effects models on a restricted design region
We develop Doptimal designs for linear main effects models on a subset ...
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Strong Coresets for kMedian and Subspace Approximation: Goodbye Dimension
We obtain the first strong coresets for the kmedian and subspace approx...
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Weisfeiler and Leman Go Neural: Higherorder Graph Neural Networks
In recent years, graph neural networks (GNNs) have emerged as a powerful...
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A TheoryBased Evaluation of Nearest Neighbor Models Put Into Practice
In the knearest neighborhood model (kNN), we are given a set of points...
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Faster kMedoids Clustering: Improving the PAM, CLARA, and CLARANS Algorithms
Clustering nonEuclidean data is difficult, and one of the most used alg...
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TU Dortmund
TU Dortmund University is a university in Dortmund, North RhineWestphalia, Germany with over 35,000 students, and over 6,000 staff including 300 professors, offering around 80 Bachelor's and master's degree programs.