Timezone: »
Multiple instance learning (MIL) is a variation of supervised learning where a single class label is assigned to a bag of instances. In this paper, we state the MIL problem as learning the Bernoulli distribution of the bag label where the bag label probability is fully parameterized by neural networks. Furthermore, we propose a neural network-based permutation-invariant aggregation operator that corresponds to the attention mechanism. Notably, an application of the proposed attention-based operator provides insight into the contribution of each instance to the bag label. We show empirically that our approach achieves comparable performance to the best MIL methods on benchmark MIL datasets and it outperforms other methods on a MNIST-based MIL dataset and two real-life histopathology datasets without sacrificing interpretability.
Author Information
Maximilian Ilse (University of Amsterdam)
Jakub Tomczak (Qualcomm AI Research)
Max Welling (University of Amsterdam)
Related Events (a corresponding poster, oral, or spotlight)
-
2018 Oral: Attention-based Deep Multiple Instance Learning »
Fri Jul 13th 02:30 -- 02:40 PM Room A6
More from the Same Authors
-
2020 Poster: Involutive MCMC: a Unifying Framework »
Kirill Neklyudov · Max Welling · Evgenii Egorov · Dmitry Vetrov -
2019 Workshop: Joint Workshop on On-Device Machine Learning & Compact Deep Neural Network Representations (ODML-CDNNR) »
Sujith Ravi · Zornitsa Kozareva · Lixin Fan · Max Welling · Yurong Chen · Werner Bailer · Brian Kulis · Haoji Hu · Jonathan Dekhtiar · Yingyan Lin · Diana Marculescu -
2019 Workshop: Theoretical Physics for Deep Learning »
Jaehoon Lee · Jeffrey Pennington · Yasaman Bahri · Max Welling · Surya Ganguli · Joan Bruna -
2019 Poster: Emerging Convolutions for Generative Normalizing Flows »
Emiel Hoogeboom · Rianne Van den Berg · Max Welling -
2019 Oral: Emerging Convolutions for Generative Normalizing Flows »
Emiel Hoogeboom · Rianne Van den Berg · Max Welling -
2019 Poster: Gauge Equivariant Convolutional Networks and the Icosahedral CNN »
Taco Cohen · Maurice Weiler · Berkay Kicanaoglu · Max Welling -
2019 Oral: Gauge Equivariant Convolutional Networks and the Icosahedral CNN »
Taco Cohen · Maurice Weiler · Berkay Kicanaoglu · Max Welling -
2018 Poster: Neural Relational Inference for Interacting Systems »
Thomas Kipf · Ethan Fetaya · Kuan-Chieh Wang · Max Welling · Richard Zemel -
2018 Oral: Neural Relational Inference for Interacting Systems »
Thomas Kipf · Ethan Fetaya · Kuan-Chieh Wang · Max Welling · Richard Zemel