Ryo Kimura

In the third lecture of the #cpaior2024 Master Class, Tamás Terlaky talks about the challenges of designing quantum interior point method algorithms for solving linear and semidefinite optimization formulations #orms

Wrapping up the #cpaior2024 Master Class, @bernalde talks about solving larger and more difficult optimization problems in quantum computers by means of decomposition algorithms

LocalSolver was pleased to sponsor the 6th edition of #YinzOr! This conference was an opportunity for Léa Blaise, Optimization Scientist at LocalSolver, to introduce the students to #LocalSolver by showing them all the key components of the solver. #optimization #orms

Anthony Karahalios of @teppercmu has won Best Student Paper at the International Conference on the Integration of Constraint Programming, Artificial Intelligence and Operations Research. The work focuses on the capacitated vehicle routing problem. cmu.is/CPAIOR

Why isn’t the optimal solution of my MILP model something else? Anton Korikov talks about finding the closest objective function that would result in the user’s expectations matching how the optimal solution should look like (a counterfactual) — #cpaior2023 best paper award!

Anthony Karahalios talks at #cpaior2023 about solving the capacitated vehicle routing problem through decision disgraceful by using column elimination — #cpaior2023 best student paper award!

In today’s keynote at #cpaior2023, Rodrigo Acuna Agost talks about opportunities for leveraging AI and OR techniques in the travel industry #orms

Rebecca Gentzel talks at #cpaior2023 about introducing optimization and computing bounds in Haddock, which is a language and architecture for compiling decision diagrams in a more seamless way; more info about it here: andrew.cmu.edu/user/vanhoeve/…

Mind blowing start for the second day of #mip2023 with @SophieHuiberts talking about the unacknowledged contribution of women and people from minoritized groups to the solution of the first linear programming problem as computers of the Mathematical Tables Project #orms

WHY do we divide by n-1 when computing the sample variance? I've never seen this way of explaining this concept anywhere else. Read on if you want a completely new way of looking at this.

Wish you knew more about Statistics and Data Science? Here are my TEN best book recommendations for learners at every level.

In case you missed @CalvinTsay's tweet, we have just released a survey along with @gmunoz_m and Joey Huchette on polyhedral theory in deep learning: arxiv.org/abs/2305.00241 This thread covers the main points, why we did this, and why you should care about it. Read along! #orms

"The Little Book of Deep Learning" Consider this as a beta version rough on the edges. Comments are welcome. fleuret.org/public/lbdl.pdf @unige_en @sciences_UNIGE

Interesting talk on agility and resilience in supply chains by Deshpande, Agrawal, and Cohen at @2023_analytics #orms #2023Analytics #bigdata #supplychain #supplychainmanagement

“The more you know how an analytics model work, the less you expect it to.” Taher Jamshidi is conducting am entire #2023analytics presentation based on aphorisms about the profession and getting the audience feedback!

Attending a very interesting tutorial by Alison Cozad and Zed Dean on how to embed machine learning models in optimization models using @gurobi, which was inspired by third-party frameworks such as JANOS (@Ivey_Huang) and OMLT (@CalvinTsay) #2023analytics #orms

On to the next #2023analytics workshop: @PrincetonDotCom is distilling the process by which they determine the problem that needs to be solved — as opposed to the one which the client brought to them in the first place! #orms

A simple algorithm to decide whether to use ChatGPT, based on my recent article (lnkd.in/eeZ5YNJh)

Daniel de Roux presenting his PhD thesis proposal on semidefinite programming! #orms