Search Results for author: Oktay Gunluk

Found 8 papers, 2 papers with code

Interpretable and Fair Boolean Rule Sets via Column Generation

no code implementations16 Nov 2021 Connor Lawless, Sanjeeb Dash, Oktay Gunluk, Dennis Wei

This paper considers the learning of Boolean rules in either disjunctive normal form (DNF, OR-of-ANDs, equivalent to decision rule sets) or conjunctive normal form (CNF, AND-of-ORs) as an interpretable model for classification.

Fairness

Fair Decision Rules for Binary Classification

no code implementations3 Jul 2021 Connor Lawless, Oktay Gunluk

In this paper we consider the problem of building Boolean rule sets in disjunctive normal form (DNF), an interpretable model for binary classification, subject to fairness constraints.

Classification Decision Making +1

Binary Matrix Factorisation and Completion via Integer Programming

1 code implementation25 Jun 2021 Reka A. Kovacs, Oktay Gunluk, Raphael A. Hauser

Binary matrix factorisation is an essential tool for identifying discrete patterns in binary data.

Binary Matrix Factorisation via Column Generation

no code implementations9 Nov 2020 Reka A. Kovacs, Oktay Gunluk, Raphael A. Hauser

Identifying discrete patterns in binary data is an important dimensionality reduction tool in machine learning and data mining.

Dimensionality Reduction

Multilabel Classification by Hierarchical Partitioning and Data-dependent Grouping

1 code implementation NeurIPS 2020 Shashanka Ubaru, Sanjeeb Dash, Arya Mazumdar, Oktay Gunluk

We then present a hierarchical partitioning approach that exploits the label hierarchy in large scale problems to divide up the large label space and create smaller sub-problems, which can then be solved independently via the grouping approach.

Classification General Classification

Low-Rank Boolean Matrix Approximation by Integer Programming

no code implementations13 Mar 2018 Reka Kovacs, Oktay Gunluk, Raphael Hauser

Low-rank approximations of data matrices are an important dimensionality reduction tool in machine learning and regression analysis.

Dimensionality Reduction

Globally Optimal Symbolic Regression

no code implementations29 Oct 2017 Vernon Austel, Sanjeeb Dash, Oktay Gunluk, Lior Horesh, Leo Liberti, Giacomo Nannicini, Baruch Schieber

In this study we introduce a new technique for symbolic regression that guarantees global optimality.

Optimal Generalized Decision Trees via Integer Programming

no code implementations10 Dec 2016 Oktay Gunluk, Jayant Kalagnanam, Minhan Li, Matt Menickelly, Katya Scheinberg

Decision trees have been a very popular class of predictive models for decades due to their interpretability and good performance on categorical features.

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