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SUMMARY:Controlling Self-Landing Rockets Using CVXPY - Philipp Schiele\, S
 teven Diamond\, Eric Sager Luxenberg
DTSTART;TZID=America/Chicago:20230710T080000
DTEND;TZID=America/Chicago:20230710T120000
DTSTAMP:20261007T042807Z
UID:pretalx-2023-ZCUDYT@cfp.scipy.org
DESCRIPTION:In this tutorial\, attendees will learn hands-on how to optimi
 ze the trajectory of a self-landing rocket in a real-time simulated settin
 g using CVXPY\, a Python-embedded modeling language for convex optimizatio
 n. We integrate the optimization with the Kerbal Space Program\, to showca
 se a complete landing mission without human intervention\, ideally in one 
 piece. CVXPY allows solving complex problems declaratively\, letting conve
 x optimization find an optimal way of meeting target conditions with respe
 ct to an objective function. After solving the initial problem\, attendees
  will use a selection of advanced CVXPY features while making the example 
 gradually more realistic.
LOCATION:Classroom 104
URL:https://cfp.scipy.org/2023/talk/ZCUDYT/
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SUMMARY:Disciplined Saddle Programming - Philipp Schiele\, Eric Sager Luxe
 nberg
DTSTART;TZID=America/Chicago:20230712T135500
DTEND;TZID=America/Chicago:20230712T142500
DTSTAMP:20261007T042807Z
UID:pretalx-2023-NPG3NS@cfp.scipy.org
DESCRIPTION:Our recent work implements a domain-specific language called D
 isciplined Saddle Programming (DSP) in Python. It is available at https://
 github.com/cvxgrp/dsp. DSP allows specifying convex-concave saddle\, or mi
 nimax problems\, a class of convex optimization problems commonly used in 
 game theory\, machine learning\, and finance. One application for DSP is t
 o naturally describe and solve robust optimization problems. We show numer
 ous examples of these problems\, including robust regressions and economic
  applications. However\, this only represents a fraction of problems solva
 ble with DSP\, and we want to engage with the SciPy community to hear abou
 t further potential applications.
LOCATION:Zlotnik Ballroom
URL:https://cfp.scipy.org/2023/talk/NPG3NS/
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