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TOP. Volume 32, Issue 3 is now available online. Special Issue on Mathematical Optimization and Machine Learning.

• https://link.springer.com/journal/11750/volumes-and-issues/32-3

  

  Volume 32, Issue 3

  October 2024

  Special Issue on Mathematical Optimization and Machine Learning

  9 articles in this issue

  1. Guest editorial to the Special Issue on Machine Learning and Mathematical Optimization in TOP-Transactions in Operations Research

     • Emilio Carrizosa
     • Dolores Romero Morales

     Editorial22 October 2024Pages: 351 - 353

  2. Predicting the demographics of Twitter users with programmatic weak supervision

     • Jonathan Tonglet
     • Astrid Jehoul
     • Bart Baesens

     Original Paper08 February 2024Pages: 354 - 390

     

  3. Mixed-integer quadratic optimization and iterative clustering techniques for semi-supervised support vector machines

     • Jan Pablo Burgard
     • Maria Eduarda Pinheiro
     • Martin Schmidt

     Original PaperOpen access16 May 2024Pages: 391 - 428

     

  4. Disagreement amongst counterfactual explanations: how transparency can be misleading

     • Dieter Brughmans
     • Lissa Melis
     • David Martens

     Original PaperOpen access08 May 2024Pages: 429 - 462

     

  5. Adapting support vector optimisation algorithms to textual gender classification

     • Javier Gomez
     • Cesar Alfaro
     • Raul Moreno

     Original PaperOpen access13 April 2024Pages: 463 - 488

     

  6. Learning-assisted optimization for transmission switching

     • Salvador Pineda
     • Juan Miguel Morales
     • Asunción Jiménez-Cordero

     Original PaperOpen access10 April 2024Pages: 489 - 516

     

  7. Bolstering stochastic gradient descent with model building

     • Ş. İlker Birbil
     • Özgür Martin
     • Figen Öztoprak

     Original PaperOpen access15 April 2024Pages: 517 - 536

     

  8. Gaining insight into crew rostering instances through ML-based sequential assignment

     • Philippe Racette
     • Frédéric Quesnel
     • François Soumis

     Original Paper25 June 2024Pages: 537 - 578

     

  9. Tuning parameters of deep neural network training algorithms pays off: a computational study

     • Corrado Coppola
     • Lorenzo Papa
     • Laura Palagi

     Original PaperOpen access17 September 2024Pages: 579 - 620

     
  Posted on 2024-11-20 by Sarah Fores