14 citations · 16 across the 5 of their papers we have counts for
6 papers
Fair Clustering with Minimum Representation Constraints
Connor Lawless, Oktay Gunluk
Clustering is a well-studied unsupervised learning task that aims to partition data points into a number of clusters. In many applications, these clusters correspond to real-world…
Recovering Dantzig-Wolfe Bounds by Cutting Planes
Rui Chen, Oktay Gunluk, Andrea Lodi
Dantzig-Wolfe (DW) decomposition is a well-known technique in mixed-integer programming (MIP) for decomposing and convexifying constraints to obtain potentially strong dual bounds.…
Online Decision Making with Fairness over Time
Rui Chen, Oktay Gunluk, Andrea Lodi +1
Online platforms increasingly rely on sequential decision-making algorithms to allocate resources, match users, or control exposure, while facing growing pressure to ensure fairnes…
Convexifying Multilinear Sets with Cardinality Constraints: Structural Properties, Nested Case and Extensions
Rui Chen, Sanjeeb Dash, Oktay Gunluk
The problem of minimizing a multilinear function of binary variables is a well-studied NP-hard problem. The set of solutions of the standard linearization of this problem is called…
On Capacity Models for Network Design
Alper Atamturk, Oktay Gunluk
In network design problems capacity constraints are modeled in three different ways depending on the application and the underlying technology for installing capacity: directed, bi…
Globally Optimal Symbolic Regression
Vernon Austel, Sanjeeb Dash, Oktay Gunluk +4
In this study we introduce a new technique for symbolic regression that guarantees global optimality. This is achieved by formulating a mixed integer non-linear program (MINLP) who…