Smart "Predict, then Optimize"

22 October 2017

Papers citing "Smart "Predict, then Optimize""

25 / 75 papers shown

Title
Mixed-Integer Optimization with Constraint Learning Donato Maragno H. Wiberg Dimitris Bertsimas Ş. Birbil D. Hertog Adejuyigbe O. Fajemisin 59 50 0 04 Nov 2021
Integrated Conditional Estimation-Optimization Sirui Chen Paul Grigas Zuo‐Jun Max Shen CML 35 25 0 24 Oct 2021
Predictive machine learning for prescriptive applications: a coupled training-validating approach E. Mortaz A. Vinel 13 3 0 22 Oct 2021
Optimization with Constraint Learning: A Framework and Survey Adejuyigbe O. Fajemisin Donato Maragno D. Hertog 58 47 0 05 Oct 2021
Risk Bounds and Calibration for a Smart Predict-then-Optimize Method Heyuan Liu Paul Grigas UQCV 22 20 0 19 Aug 2021
Prescribing net demand for two-stage electricity generation scheduling J. Morales Miguel Angel Muñoz S. Pineda 23 14 0 02 Aug 2021
Predictive and Prescriptive Performance of Bike-Sharing Demand Forecasts for Inventory Management Daniele Gammelli Yihua Wang Dennis Prak Filipe Rodrigues Stefan Minner Francisco Câmara Pereira AI4TS 18 36 0 28 Jul 2021
Distributionally Robust Prescriptive Analytics with Wasserstein Distance Tianyu Wang Ningyuan Chen Chun Wang 15 6 0 10 Jun 2021
Markdowns in E-Commerce Fresh Retail: A Counterfactual Prediction and Multi-Period Optimization Approach Junhao Hua Ling Yan Huan Xu Cheng Yang 11 16 0 18 May 2021
Causal Decision Making and Causal Effect Estimation Are Not the Same... and Why It Matters Carlos Fernández-Loría F. Provost CML 13 43 0 08 Apr 2021
Neuro-Symbolic Constraint Programming for Structured Prediction Paolo Dragone Stefano Teso Andrea Passerini 27 18 0 31 Mar 2021
Application-Driven Learning: A Closed-Loop Prediction and Optimization Approach Applied to Dynamic Reserves and Demand Forecasting J. Garcia A. Street Tito Homem-de-Mello F. Muñoz 24 10 0 26 Feb 2021
Achieving Efficiency in Black Box Simulation of Distribution Tails with Self-structuring Importance Samplers Anand Deo Karthyek Murthy 25 10 0 14 Feb 2021
Demand Forecasting for Platelet Usage: from Univariate Time Series to Multivariate Models M. Motamedi Jessica Dawson Na Li D. Down N. Heddle AI4TS 21 20 0 06 Jan 2021
Forecasting: theory and practice F. Petropoulos D. Apiletti Vassilios Assimakopoulos M. Z. Babai Devon K. Barrow ... J. Arenas Xiaoqian Wang R. L. Winkler Alisa Yusupova F. Ziel AI4TS 36 363 0 04 Dec 2020
Contrastive Losses and Solution Caching for Predict-and-Optimize Maxime Mulamba Jayanta Mandi Michelangelo Diligenti M. Lombardi Víctor Bucarey Tias Guns 29 48 0 10 Nov 2020
Fast Rates for Contextual Linear Optimization Yichun Hu Nathan Kallus Xiaojie Mao OffRL 34 41 0 05 Nov 2020
Decision-Aware Conditional GANs for Time Series Data He Sun Zhun Deng Hui Chen David C. Parkes CML AI4TS 27 17 0 26 Sep 2020
Stochastic Optimization Forests Nathan Kallus Xiaojie Mao 32 48 0 17 Aug 2020
Automatically Learning Compact Quality-aware Surrogates for Optimization Problems Kai Wang Bryan Wilder Andrew Perrault Milind Tambe 21 28 0 18 Jun 2020
Learning Linear Programs from Optimal Decisions Yingcong Tan Daria Terekhov Andrew Delong 30 28 0 16 Jun 2020
Lossless Compression of Deep Neural Networks Thiago Serra Abhinav Kumar Srikumar Ramalingam 24 56 0 01 Jan 2020
Smart Predict-and-Optimize for Hard Combinatorial Optimization Problems Jaynta Mandi Emir Demirović Peter Stuckey Tias Guns 15 143 0 22 Nov 2019
Strong mixed-integer programming formulations for trained neural networks Ross Anderson Joey Huchette Christian Tjandraatmadja J. Vielma 19 251 0 20 Nov 2018
A simpler approach to obtaining an O(1/t) convergence rate for the projected stochastic subgradient method Simon Lacoste-Julien Mark W. Schmidt Francis R. Bach 128 259 0 10 Dec 2012