Loog, Marco

1. An introduction to domain adaptation and transfer learning
   2018/12/31 by Kouw, Wouter M., Loog, Marco · 7 citations
   #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
2. The Shape of Learning Curves: a Review
   2021/03/19 by Tom J. Viering, Marco Loog, Viering, Tom +1 · 7 citations
   Computer Science · Decision Sciences · #Data Analysis with R #FOS: Computer and information sciences #Forecasting Techniques and Applications #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG)
3. Respecting Domain Relations: Hypothesis Invariance for Domain Generalization
   2020/10/15 by Ziqi Wang, Wang, Ziqi, Marco Loog +3 · 4 citations
   Computer Science · #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Multimodal Machine Learning Applications #Topic Modeling
4. How to Manipulate CNNs to Make Them Lie: the GradCAM Case
   2019/07/25 by Tom J. Viering, Ziqi Wang, Viering, Tom +5 · 4 citations
   Computer Science · #Adversarial Robustness in Machine Learning #Anomaly Detection Techniques and Applications #Computer Vision and Pattern Recognition (cs.CV) #Cryptography and Security (cs.CR) #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG)
5. Minimizers of the Empirical Risk and Risk Monotonicity
   2019/07/11 by Marco Loog, Loog, Marco, Tom J. Viering +3 · 2 citations
   Computer Science · #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Machine Learning and Data Classification
6. The Peaking Phenomenon in Semi-supervised Learning
   2016/10/17 by Jesse H. Krijthe, Marco Loog, Krijthe, Jesse H. +1 · 1 citation
   Computer Science · #FOS: Computer and information sciences #Face and Expression Recognition #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification #Neural Networks and Applications
7. Semi-Supervised Learning, Causality and the Conditional Cluster Assumption
   2019/05/28 by von Kügelgen, Julius, Mey, Alexander, Loog, Marco +1 · 1 citation
   #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Other Statistics (stat.OT)
8. Consistency and Finite Sample Behavior of Binary Class Probability\n Estimation
   2019/08/30 by Alexander Mey, Marco Loog, Mey, Alexander +1 · 1 citation
   Decision Sciences · Mathematics · #Advanced Statistical Methods and Models #Advanced Statistical Process Monitoring #FOS: Computer and information sciences #Forecasting Techniques and Applications #Machine Learning (cs.LG) #Machine Learning (stat.ML)
9. Making Learners (More) Monotone
   2019/11/25 by Viering, Tom J., Mey, Alexander, Loog, Marco · 1 citation
   #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
10. Black Magic in Deep Learning: How Human Skill Impacts Network Training
    2020/08/13 by Kanav Anand, Ziqi Wang, Anand, Kanav +5 · 1 citation
    Computer Science · #Computer Vision and Pattern Recognition (cs.CV) #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning and Data Classification #Stochastic Gradient Optimization Techniques
11. Social Processes: Self-Supervised Meta-Learning over Conversational Groups for Forecasting Nonverbal Social Cues
    2021/07/28 by Raman, Chirag, Hung, Hayley, Loog, Marco · 1 citation
    #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG)