Software & Data Sets

SMB: A stochastic gradient descent variant based on model building for training deep learning models.

OptiCL: An end-to-end framework for mixed-integer optimization with data-driven learned constraints. (by H. Wiberg and D. Maragno)

DPRMS: Python codes to reproduce our results in our paper on differential privacy in multi-party resource sharing.

Rule Discovery: Python packages for rule extraction (RUX) and rule generation (RUG) algorithms for interpretable classification.

DPAccGradMethods: Code package to reproduce our results on differentially private accelerated optimization algorithms.

Rule Covering: Python packages for two algorithms for interpretation of trained random forests and boosting of decision trees.

PMBSolve: An optimization solver for unconstrained differentiable problems.

HAMSI-MF: Hessian approximated multiple subsets iteration algorithm for matrix factorization.

EM-Optimizer: A Python implementation of the Electromagnetism-like Mechanism for global optimization (by M. K. Öztürk).

Simple Kernels: A repository for low-dimensional interpretable kernels based on anchor point selection from datasets.

Temporal Bin Packing: A set of test instances for temporal bin packing problem.

Terms of Service: A dataset of terms of service agreements of 251 251 cryptocurrency exchanges.

Data Money: A dataset of white papers of top 100 cryptocurrencies and their blockchains.

SUMAG: Data sets and scripts for the academic collaboration network of Turkey (by S. Aydın).