WEBINAR / EVENT
[Podcast] Data Science Based Decisions: Mixed-Integer Programming
Learn how machine learning and optimization can complement each other; the former making predictions about likely future business outcomes, and the latter suggesting appropriate actions to take in order to take advantage of these outcomes.
November 07 2019
WEBINAR / EVENT
[Podcast] Data Science Based Decisions: Mixed-Integer Programming
Learn how machine learning and optimization can complement each other; the former making predictions about likely future business outcomes, and the latter suggesting appropriate actions to take in order to take advantage of these outcomes.
November 07 2019
WEBINAR / EVENT
[Podcast] Data Science Based Decisions: Mixed-Integer Programming
Learn how machine learning and optimization can complement each other; the former making predictions about likely future business outcomes, and the latter suggesting appropriate actions to take in order to take advantage of these outcomes.
November 07 2019
This latest Data Science Central podcast traces the history of mixed-integer programming (MIP), noting several parallels with machine learning. In the process, we briefly discuss the impact that MIP has had on a number of application domains and why this powerful technology should be a part of every data scientist’s analytics toolkit.
Hosted by:
Rafael Knuth, Contributing Editor – Data Science Central
This latest Data Science Central podcast traces the history of mixed-integer programming (MIP), noting several parallels with machine learning. In the process, we briefly discuss the impact that MIP has had on a number of application domains and why this powerful technology should be a part of every data scientist’s analytics toolkit.
Hosted by:
Rafael Knuth, Contributing Editor – Data Science Central
This latest Data Science Central podcast traces the history of mixed-integer programming (MIP), noting several parallels with machine learning. In the process, we briefly discuss the impact that MIP has had on a number of application domains and why this powerful technology should be a part of every data scientist’s analytics toolkit.
Hosted by:
Rafael Knuth, Contributing Editor – Data Science Central
Speakers
Meet Your Expert Speaker
Learn from the best in the industry, bringing years of experience and groundbreaking insights to the forefront of AI personalization.
Edward Rothberg
Chairman of the Board and Co-Founder
Dr. Rothberg has served in senior leadership positions in optimization software companies for more than twenty years. Prior to his role as Gurobi Chief Scientist and Chairman of the Board, Dr. Rothberg held the Gurobi CEO position from 2015 - 2022 and the COO position from the co-founding of Gurobi in 2008 to 2015. Prior to co-founding Gurobi, he led the ILOG CPLEX team. Dr. Edward Rothberg has a BS in Mathematical and Computational Science from Stanford University, and an MS and PhD in Computer Science, also from Stanford University. Dr. Rothberg has published numerous papers in the fields of linear algebra, parallel computing, and mathematical programming. He is one of the world's leading experts in sparse Cholesky factorization and computational linear, integer, and quadratic programming. He is particularly well known for his work in parallel sparse matrix factorization, and in heuristics for mixed integer programming.
Speakers
Meet Your Expert Speaker
Learn from the best in the industry, bringing years of experience and groundbreaking insights to the forefront of AI personalization.
Edward Rothberg
Chairman of the Board and Co-Founder
Dr. Rothberg has served in senior leadership positions in optimization software companies for more than twenty years. Prior to his role as Gurobi Chief Scientist and Chairman of the Board, Dr. Rothberg held the Gurobi CEO position from 2015 - 2022 and the COO position from the co-founding of Gurobi in 2008 to 2015. Prior to co-founding Gurobi, he led the ILOG CPLEX team. Dr. Edward Rothberg has a BS in Mathematical and Computational Science from Stanford University, and an MS and PhD in Computer Science, also from Stanford University. Dr. Rothberg has published numerous papers in the fields of linear algebra, parallel computing, and mathematical programming. He is one of the world's leading experts in sparse Cholesky factorization and computational linear, integer, and quadratic programming. He is particularly well known for his work in parallel sparse matrix factorization, and in heuristics for mixed integer programming.
Speakers
Meet Your Expert Speaker
Learn from the best in the industry, bringing years of experience and groundbreaking insights to the forefront of AI personalization.
Chairman of the Board and Co-Founder
Edward Rothberg
Dr. Rothberg has served in senior leadership positions in optimization software companies for more than twenty years. Prior to his role as Gurobi Chief Scientist and Chairman of the Board, Dr. Rothberg held the Gurobi CEO position from 2015 - 2022 and the COO position from the co-founding of Gurobi in 2008 to 2015. Prior to co-founding Gurobi, he led the ILOG CPLEX team. Dr. Edward Rothberg has a BS in Mathematical and Computational Science from Stanford University, and an MS and PhD in Computer Science, also from Stanford University. Dr. Rothberg has published numerous papers in the fields of linear algebra, parallel computing, and mathematical programming. He is one of the world's leading experts in sparse Cholesky factorization and computational linear, integer, and quadratic programming. He is particularly well known for his work in parallel sparse matrix factorization, and in heuristics for mixed integer programming.
