Conferencia de Prof. Ivo Nowak
Title: Decomposition Methods for Optimization, Control and Machine Learning in Engineering
Speaker: Prof. Ivo Nowak, Hochschule für Angewandte Wissenschaften, Hamburg
Room: Salon de grados A (EII)
Date: Thursday, 18 of January 11.00 h.
Abstract:
We present new decomposition methods for globally solving complex optimization, control and machine learning problems in engineering.
The methods are based on a generate-and-solve approach and are implemented in the open-source frameworks Decogo and Decolearn.
Numerical results and possible extensions for complex planning, design and control applications are presented.
Short bio:
Ivo nowak is a full professor at Hochschule für Angewandte Wissenschaften in Hamburg. After his PhD at the Technical University Berlin, he worked for 10 years on algorithms for Mixed Integer Nonlinear Programming and their application in engineering problems at several universities. From 2004 he worked for 10 years a the systems department of Lufhansa on challenging scheduling and rostering problems. In 2014 he returned to academia and focuses on the potential for using decomposition in optimization algorithms and Machine Learning.
Title: Decomposition Methods for Optimization, Control and Machine Learning in Engineering
Speaker: Prof. Ivo Nowak, Hochschule für Angewandte Wissenschaften, Hamburg
Room: Salon de grados A (EII)
Date: Thursday, 18 of January 11.00 h.
Abstract:
We present new decomposition methods for globally solving complex optimization, control and machine learning problems in engineering.
The methods are based on a generate-and-solve approach and are implemented in the open-source frameworks Decogo and Decolearn.
Numerical results and possible extensions for complex planning, design and control applications are presented.
Short bio:
Ivo nowak is a full professor at Hochschule für Angewandte Wissenschaften in Hamburg. After his PhD at the Technical University Berlin, he worked for 10 years on algorithms for Mixed Integer Nonlinear Programming and their application in engineering problems at several universities. From 2004 he worked for 10 years a the systems department of Lufhansa on challenging scheduling and rostering problems. In 2014 he returned to academia and focuses on the potential for using decomposition in optimization algorithms and Machine Learning.
