← Search

Matthias Mitterreiter

4 accepted papers

2023

Why Capsule Neural Networks Do Not Scale: Challenging the Dynamic Parse-Tree Assumption

AAAI 2023technical

Capsule neural networks replace simple, scalar-valued neurons with vector-valued capsules. They are motivated by the pattern recognition system in the human brain, where complex objects are decomposed into a hierarchy of simpler object parts. Such a hierarchy is referred to as a parse-tree. Conceptu…

Cited by 9SourcePDFScholar
2021

Method of Moments for Topic Models with Mixed Discrete and Continuous Features

IJCAI 2021poster

Topic models are characterized by a latent class variable that represents the different topics. Traditionally, their observable variables are modeled as discrete variables like, for instance, in the prototypical latent Dirichlet allocation (LDA) topic model. In LDA, words in text documents are enco…

Cited by 1SourcePDFScholar
2019

GENO -- GENeric Optimization for Classical Machine Learning

NeurIPS 2019poster

Although optimization is the longstanding, algorithmic backbone of machine learning new models still require the time-consuming implementation of new solvers. As a result, there are thousands of implementations of optimization algorithms for machine learning problems. A natural question is, if it is…

Cited by 31SourcePDFScholar
2018

Computing Higher Order Derivatives of Matrix and Tensor Expressions

NeurIPS 2018poster

Optimization is an integral part of most machine learning systems and most numerical optimization schemes rely on the computation of derivatives. Therefore, frameworks for computing derivatives are an active area of machine learning research. Surprisingly, as of yet, no existing framework is capable…