paper-with-me

홈 › Papers

OMLT: Optimization & Machine Learning Toolkit

2022-02-04 · Francesco Ceccon, Jordan Jalving, Joshua Haddad, Alexander Thebelt, Calvin Tsay, Carl D. Laird, Ruth Misener

The optimization and machine learning toolkit (OMLT) is an open-source software package incorporating neural network and gradient-boosted tree surrogate models, which have been trained using machine learning, into larger optimization problems. We discuss the advances in optimization technology that made OMLT possible and show how OMLT seamlessly integrates with the algebraic modeling language Pyomo. We demonstrate how to use OMLT for solving decision-making problems in both computer science and engineering.

📄 PDF Abstract BibTeX arXiv:2202.02414

Code (1)

cog-imperial/omlt 공식 구현 tf

Tasks

Bayesian OptimisationBIG-bench Machine LearningDecision Making

Similar Papers 제목 키워드 기반

Conformal Prediction with Upper and Lower Bound Models

2025-03-06 · Miao Li, Michael Klamkin, Mathieu Tanneau, Reza Zandehshahvar 외

This paper studies a Conformal Prediction (CP) methodology for building prediction intervals in a regression setting, given only deterministic lower and upper bounds on the target variable. It proposes a new CP mechanism…

Conformal PredictionModel SelectionPredictionPrediction Intervals

Jensen: An Easily-Extensible C++ Toolkit for Production-Level Machine Learning and Convex Optimization

2018-07-17 · Rishabh Iyer, John T. Halloran, Kai Wei

This paper introduces Jensen, an easily extensible and scalable toolkit for production-level machine learning and convex optimization. Jensen implements a framework of convex (or loss) functions, convex optimization algo…

BIG-bench Machine Learningregression

Designing Machine Learning Pipeline Toolkit for AutoML Surrogate Modeling Optimization

2021-07-02 · Paulito P. Palmes, Akihiro Kishimoto, Radu Marinescu, Parikshit Ram 외

The pipeline optimization problem in machine learning requires simultaneous optimization of pipeline structures and parameter adaptation of their elements. Having an elegant way to express these structures can help lesse…

AutoMLBIG-bench Machine LearningManagement

OpenBox: A Python Toolkit for Generalized Black-box Optimization

2023-04-26 · Huaijun Jiang, Yu Shen, Yang Li, Beicheng Xu 외

Black-box optimization (BBO) has a broad range of applications, including automatic machine learning, experimental design, and database knob tuning. However, users still face challenges when applying BBO methods to their…

Experimental Design

YANMTT: Yet Another Neural Machine Translation Toolkit

2021-08-25 · Raj Dabre, Eiichiro Sumita

In this paper we present our open-source neural machine translation (NMT) toolkit called "Yet Another Neural Machine Translation Toolkit" abbreviated as YANMTT which is built on top of the Transformers library. Despite t…

Machine TranslationModel CompressionNMTTransfer Learning+1