TU Eindhoven

∙ Eindhoven , Netherlands ∙ 0 followers

The Eindhoven University of Technology, abbr. TU/e, is a technical university in the Netherlands, operating in English.

Causal Discovery from Incomplete Data: A Deep Learning Approach

As systems are getting more autonomous with the development of artificia...
01/15/2020 ∙ by Yuhao Wang, et al. ∙ 127 ∙ share

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A Survey of Crowdsourcing in Medical Image Analysis

Rapid advances in image processing capabilities have been seen across ma...
02/25/2019 ∙ by Silas Ørting, et al. ∙ 28 ∙ share

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Topological Insights in Sparse Neural Networks

Sparse neural networks are effective approaches to reduce the resource r...
06/24/2020 ∙ by Shiwei Liu, et al. ∙ 24 ∙ share

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Resource-Efficient Neural Networks for Embedded Systems

While machine learning is traditionally a resource intensive task, embed...
01/07/2020 ∙ by Wolfgang Roth, et al. ∙ 21 ∙ share

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An empirical study on hyperparameter tuning of decision trees

Machine learning algorithms often contain many hyperparameters whose val...
12/05/2018 ∙ by Rafael Gomes Mantovani, et al. ∙ 18 ∙ share

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Solving the Order Batching and Sequencing Problem using Deep Reinforcement Learning

In e-commerce markets, on time delivery is of great importance to custom...
06/16/2020 ∙ by Bram Cals, et al. ∙ 18 ∙ share

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Learning with Delayed Synaptic Plasticity

The plasticity property of biological neural networks allows them to per...
03/22/2019 ∙ by Anil Yaman, et al. ∙ 12 ∙ share

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Back to the Future -- Sequential Alignment of Text Representations

Language evolves over time in many ways relevant to natural language pro...
09/08/2019 ∙ by Johannes Bjerva, et al. ∙ 10 ∙ share

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Dual Embedding Expansion for Vehicle Re-identification

Vehicle re-identification plays a crucial role in the management of tran...
04/18/2020 ∙ by Clint Sebastian, et al. ∙ 10 ∙ share

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PDE-based Group Equivariant Convolutional Neural Networks

We present a PDE-based framework that generalizes Group equivariant Conv...
01/24/2020 ∙ by Bart Smets, et al. ∙ 8 ∙ share

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Semantic Foreground Inpainting from Weak Supervision

Semantic scene understanding is an essential task for self-driving vehic...
09/10/2019 ∙ by Chenyang Lu, et al. ∙ 7 ∙ share

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Hallucinating Beyond Observation: Learning to Complete with Partial Observation and Unpaired Prior Knowledge

We propose a novel single-step training strategy that allows convolution...
07/23/2019 ∙ by Chenyang Lu, et al. ∙ 6 ∙ share

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Multi-task Self-Supervised Learning for Human Activity Detection

Deep learning methods are successfully used in applications pertaining t...
07/27/2019 ∙ by Aaqib Saeed, et al. ∙ 6 ∙ share

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Approximation Algorithms for Multi-Robot Patrol-Scheduling with Min-Max Latency

We consider the problem of finding patrol schedules for k robots to visi...
05/05/2020 ∙ by Peyman Afshani, et al. ∙ 5 ∙ share

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A Deep Neural Model Of Emotion Appraisal

Emotional concepts play a huge role in our daily life since they take pa...
08/01/2018 ∙ by Pablo Barros, et al. ∙ 4 ∙ share

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Deep Unfolded Robust PCA with Application to Clutter Suppression in Ultrasound

Contrast enhanced ultrasound is a radiation-free imaging modality which ...
11/20/2018 ∙ by Oren Solomon, et al. ∙ 4 ∙ share

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Machine Learning based Simulation Optimisation for Trailer Management

In many situations, simulation models are developed to handle complex re...
07/17/2019 ∙ by Dylan Rijnen, et al. ∙ 3 ∙ share

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Synthetic Elastography using B-mode Ultrasound through a Deep Fully-Convolutional Neural Network

Shear-wave elastography (SWE) permits local estimation of tissue elastic...
08/09/2019 ∙ by R. R. Wildeboer, et al. ∙ 2 ∙ share

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Mining Non-Redundant Sets of Generalizing Patterns from Sequence Databases

Sequential pattern mining techniques extract patterns corresponding to f...
12/12/2017 ∙ by Niek Tax, et al. ∙ 0 ∙ share

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Discovering More Precise Process Models from Event Logs by Filtering Out Chaotic Activities

Process Discovery is concerned with the automatic generation of a proces...
11/03/2017 ∙ by Niek Tax, et al. ∙ 0 ∙ share

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Evolutionary Training of Sparse Artificial Neural Networks: A Network Science Perspective

Through the success of deep learning, Artificial Neural Networks (ANNs) ...
07/15/2017 ∙ by Decebal Constantin Mocanu, et al. ∙ 0 ∙ share

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Weakly supervised training of deep convolutional neural networks for overhead pedestrian localization in depth fields

Overhead depth map measurements capture sufficient amount of information...
06/09/2017 ∙ by Alessandro Corbetta, et al. ∙ 0 ∙ share

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Meta-QSAR: a large-scale application of meta-learning to drug design and discovery

We investigate the learning of quantitative structure activity relations...
09/12/2017 ∙ by Ivan Olier, et al. ∙ 0 ∙ share

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Subjectively Interesting Subgroup Discovery on Real-valued Targets

Deriving insights from high-dimensional data is one of the core problems...
10/12/2017 ∙ by Jefrey Lijffijt, et al. ∙ 0 ∙ share

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Predictive Business Process Monitoring with LSTM Neural Networks

Predictive business process monitoring methods exploit logs of completed...
12/07/2016 ∙ by Niek Tax, et al. ∙ 0 ∙ share

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Guided Interaction Exploration in Artifact-centric Process Models

Artifact-centric process models aim to describe complex processes as a c...
06/07/2017 ∙ by Maikel L. van Eck, et al. ∙ 0 ∙ share

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Generating Time-Based Label Refinements to Discover More Precise Process Models

Process mining is a research field focused on the analysis of event data...
05/25/2017 ∙ by Niek Tax, et al. ∙ 0 ∙ share

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Mining Process Model Descriptions of Daily Life through Event Abstraction

Process mining techniques focus on extracting insight in processes from ...
05/25/2017 ∙ by Niek Tax, et al. ∙ 0 ∙ share

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Event Stream-Based Process Discovery using Abstract Representations

The aim of process discovery, originating from the area of process minin...
04/25/2017 ∙ by Sebastiaan J. van Zelst, et al. ∙ 0 ∙ share

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The Generalized Cross Validation Filter

Generalized cross validation (GCV) is one of the most important approach...
06/08/2017 ∙ by Giulio Bottegal, et al. ∙ 0 ∙ share

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Retinal Microaneurysms Detection using Local Convergence Index Features

Retinal microaneurysms are the earliest clinical sign of diabetic retino...
07/21/2017 ∙ by Behdad Dashtbozorg, et al. ∙ 0 ∙ share

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Design and Processing of Invertible Orientation Scores of 3D Images for Enhancement of Complex Vasculature

The enhancement and detection of elongated structures in noisy image dat...
07/07/2017 ∙ by M. H. J. Janssen, et al. ∙ 0 ∙ share

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Heuristic Approaches for Generating Local Process Models through Log Projections

Local Process Model (LPM) discovery is focused on the mining of a set of...
10/10/2016 ∙ by Niek Tax, et al. ∙ 0 ∙ share

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Transfer Learning by Asymmetric Image Weighting for Segmentation across Scanners

Supervised learning has been very successful for automatic segmentation ...
03/15/2017 ∙ by Veronika Cheplygina, et al. ∙ 0 ∙ share

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Classification of COPD with Multiple Instance Learning

Chronic obstructive pulmonary disease (COPD) is a lung disease where ear...
03/15/2017 ∙ by Veronika Cheplygina, et al. ∙ 0 ∙ share

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Automatic Emphysema Detection using Weakly Labeled HRCT Lung Images

A method for automatically quantifying emphysema regions using High-Reso...
06/07/2017 ∙ by Isabel Pino Peña, et al. ∙ 0 ∙ share

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On Generation of Time-based Label Refinements

Process mining is a research field focused on the analysis of event data...
09/12/2016 ∙ by Niek Tax, et al. ∙ 0 ∙ share

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Left/Right Hand Segmentation in Egocentric Videos

Wearable cameras allow people to record their daily activities from a us...
07/21/2016 ∙ by Alejandro Betancourt, et al. ∙ 0 ∙ share

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Log-based Evaluation of Label Splits for Process Models

Process mining techniques aim to extract insights in processes from even...
06/23/2016 ∙ by Niek Tax, et al. ∙ 0 ∙ share

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A new kernel-based approach to system identification with quantized output data

In this paper we introduce a novel method for linear system identificati...
10/03/2016 ∙ by Giulio Bottegal, et al. ∙ 0 ∙ share

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Energy Disaggregation for Real-Time Building Flexibility Detection

Energy is a limited resource which has to be managed wisely, taking into...
05/06/2016 ∙ by Elena Mocanu, et al. ∙ 0 ∙ share

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Retrieving challenging vessel connections in retinal images by line co-occurrence statistics

Natural images contain often curvilinear structures, which might be disc...
10/20/2016 ∙ by Samaneh Abbasi-Sureshjani, et al. ∙ 0 ∙ share

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Predictive User Modeling with Actionable Attributes

Different machine learning techniques have been proposed and used for mo...
12/23/2013 ∙ by Indre Zliobaite, et al. ∙ 0 ∙ share

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Cutting out the middleman: measuring nuclear area in histopathology slides without segmentation

The size of nuclei in histological preparations from excised breast tumo...
06/20/2016 ∙ by Mitko Veta, et al. ∙ 0 ∙ share

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Estimating 3D Trajectories from 2D Projections via Disjunctive Factored Four-Way Conditional Restricted Boltzmann Machines

Estimation, recognition, and near-future prediction of 3D trajectories b...
04/20/2016 ∙ by Decebal Constantin Mocanu, et al. ∙ 0 ∙ share

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Template Matching via Densities on the Roto-Translation Group

We propose a template matching method for the detection of 2D image obje...
03/10/2016 ∙ by Erik J. Bekkers, et al. ∙ 0 ∙ share

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Analysis of Vessel Connectivities in Retinal Images by Cortically Inspired Spectral Clustering

Retinal images provide early signs of diabetic retinopathy, glaucoma, an...
12/21/2015 ∙ by Marta Favali, et al. ∙ 0 ∙ share

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Improving Fiber Alignment in HARDI by Combining Contextual PDE Flow with Constrained Spherical Deconvolution

We propose two strategies to improve the quality of tractography results...
06/23/2015 ∙ by J. M. Portegies, et al. ∙ 0 ∙ share

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Invertible Orientation Scores of 3D Images

The enhancement and detection of elongated structures in noisy image dat...
05/28/2015 ∙ by Michiel Janssen, et al. ∙ 0 ∙ share

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Relevance As a Metric for Evaluating Machine Learning Algorithms

In machine learning, the choice of a learning algorithm that is suitable...
03/28/2013 ∙ by Aravind Kota Gopalakrishna, et al. ∙ 0 ∙ share

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