Jan Pfeifer — accepted AI-conference papers

2017

Deep Lattice Networks and Partial Monotonic Functions

Seungil You, David Ding, Kevin Canini, Jan Pfeifer, Maya Gupta

NeurIPS 2017poster

We propose learning deep models that are monotonic with respect to a user-specified set of inputs by alternating layers of linear embeddings, ensembles of lattices, and calibrators (piecewise linear functions), with appropriate constraints for monotonicity, and jointly training the resulting network…

Cited by 214 Source ↗PDF ↗code ↗Scholar ↗

2016

Fast and Flexible Monotonic Functions with Ensembles of Lattices

Mahdi Milani Fard, Kevin Canini, Andrew Cotter, Jan Pfeifer, Maya Gupta

NeurIPS 2016poster

For many machine learning problems, there are some inputs that are known to be positively (or negatively) related to the output, and in such cases training the model to respect that monotonic relationship can provide regularization, and makes the model more interpretable. However, flexible monotonic…

Cited by 95 Source ↗PDF ↗Scholar ↗