
A modular framework for objectbased saccadic decisions in dynamic scenes
Visually exploring the world around us is not a passive process. Instead...
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Exploring the Similarity of Representations in ModelAgnostic MetaLearning
In past years modelagnostic metalearning (MAML) has been one of the mo...
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Training Generative Networks with general Optimal Transport distances
We propose a new algorithm that uses an auxiliary Neural Network to calc...
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Joining Sound Event Detection and Localization Through Spatial Segregation
Identification and localization of sounds are both integral parts of com...
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The NIGENS General Sound Events Database
Computational auditory scene analysis is gaining interest in the last ye...
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NonDeterministic Policy Improvement Stabilizes Approximated Reinforcement Learning
This paper investigates a type of instability that is linked to the gree...
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Regression with Linear Factored Functions
Many applications that use empirically estimated functions face a curse ...
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Learning in Riemannian Orbifolds
Learning in Riemannian orbifolds is motivated by existing machine learni...
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Risksensitive Markov control processes
We introduce a general framework for measuring risk in the context of Ma...
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Probabilistic prototype models for attributed graphs
This contribution proposes a new approach towards developing a class of ...
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Extending Bron Kerbosch for Solving the Maximum Weight Clique Problem
This contribution extends the Bron Kerbosch algorithm for solving the ma...
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Accelerating Competitive Learning Graph Quantization
Vector quantization(VQ) is a lossy data compression technique from signa...
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Graph Quantization
Vector quantization(VQ) is a lossy data compression technique from signa...
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Elkan's kMeans for Graphs
This paper extends kmeans algorithms from the Euclidean domain to the d...
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A Necessary and Sufficient Condition for Graph Matching Being Equivalent to the Maximum Weight Clique Problem
This paper formulates a necessary and sufficient condition for a generic...
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Klaus Obermayer
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