1.1k citations · 2k across the 52 of their papers we have counts for
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Frugal Machine Learning
Mikhail Evchenko, Joaquin Vanschoren, Holger H. Hoos +2
Machine learning, already at the core of increasingly many systems and applications, is set to become even more ubiquitous with the rapid rise of wearable devices and the Internet…
From Strings to Data Science: a Practical Framework for Automated String Handling
John W. van Lith, Joaquin Vanschoren
Many machine learning libraries require that string features be converted to a numerical representation for the models to work as intended. Categorical string features can represen…
Cats, not CAT scans: a study of dataset similarity in transfer learning for 2D medical image classification
Irma van den Brandt, Floris Fok, Bas Mulders +2
Transfer learning is a commonly used strategy for medical image classification, especially via pretraining on source data and fine-tuning on target data. There is currently no cons…
Meta-Learning for Symbolic Hyperparameter Defaults
Pieter Gijsbers, Florian Pfisterer, Jan N. van Rijn +2
Hyperparameter optimization in machine learning (ML) deals with the problem of empirically learning an optimal algorithm configuration from data, usually formulated as a black-box…
Fixed-point Quantization of Convolutional Neural Networks for Quantized Inference on Embedded Platforms
Rishabh Goyal, Joaquin Vanschoren, Victor van Acht +1
Convolutional Neural Networks (CNNs) have proven to be a powerful state-of-the-art method for image classification tasks. One drawback however is the high computational complexity…
Hyperboost: Hyperparameter Optimization by Gradient Boosting surrogate models
Jeroen van Hoof, Joaquin Vanschoren
Bayesian Optimization is a popular tool for tuning algorithms in automatic machine learning (AutoML) systems. Current state-of-the-art methods leverage Random Forests or Gaussian p…
Theory-based Habit Modeling for Enhancing Behavior Prediction
Chao Zhang, Joaquin Vanschoren, Arlette van Wissen +3
Psychological theories of habit posit that when a strong habit is formed through behavioral repetition, it can trigger behavior automatically in the same environment. Given the rec…
A comparison of optimisation algorithms for high-dimensional particle and astrophysics applications
The DarkMachines High Dimensional Sampling Group, Csaba Balázs, Melissa van Beekveld +18
Optimisation problems are ubiquitous in particle and astrophysics, and involve locating the optimum of a complicated function of many parameters that may be computationally expensi…