Oberwolfach Publications
http://publications.mfo.de:80
The DSpace digital repository system captures, stores, indexes, preserves, and distributes digital research material.Wed, 12 Aug 2020 09:16:11 GMT2020-08-12T09:16:11ZOberwolfach Publicationshttp://publications.mfo.de/themes/Mirage2/images/apple-touch-icon.png
http://publications.mfo.de:80
Maximal Quaternion Orders in Quadratic Extensions- in Hurwitz’s Diaries
http://publications.mfo.de/handle/mfo/3768
Maximal Quaternion Orders in Quadratic Extensions- in Hurwitz’s Diaries
Oswald, Nicola; Steuding, Jörn
We present and comment on some unpublished work of Adolf Hurwitz on quaternion arithmetic from his diaries.
Mon, 03 Aug 2020 00:00:00 GMThttp://publications.mfo.de/handle/mfo/37682020-08-03T00:00:00ZOswald, NicolaSteuding, JörnWe present and comment on some unpublished work of Adolf Hurwitz on quaternion arithmetic from his diaries.Hopf Algebras in Combinatorics, Volume 2
http://publications.mfo.de/handle/mfo/3767
Hopf Algebras in Combinatorics, Volume 2
Grinberg, Darij; Reiner, Victor
Thu, 30 Jul 2020 00:00:00 GMThttp://publications.mfo.de/handle/mfo/37672020-07-30T00:00:00ZGrinberg, DarijReiner, VictorHopf Algebras in Combinatorics, Volume 1
http://publications.mfo.de/handle/mfo/3766
Hopf Algebras in Combinatorics, Volume 1
Grinberg, Darij; Reiner, Victor
Wed, 29 Jul 2020 00:00:00 GMThttp://publications.mfo.de/handle/mfo/37662020-07-29T00:00:00ZGrinberg, DarijReiner, VictorHow Quantum Information can Improve Social Welfare
http://publications.mfo.de/handle/mfo/3765
How Quantum Information can Improve Social Welfare
Groisman, Berry; Mc Gettrick, Michael; Mhalla, Mehdi; Pawlowski, Marcin
In [2, 18, 5, 19, 4] it has been shown that quantum resources can allow us
to achieve a family of equilibria that can have sometimes a better social welfare,
while guaranteeing privacy. We use graph games to propose a way to build non-
cooperative games from graph states, and we show how to achieve an unlimited
improvement with quantum advice compared to classical advice.
Thu, 16 Jul 2020 00:00:00 GMThttp://publications.mfo.de/handle/mfo/37652020-07-16T00:00:00ZGroisman, BerryMc Gettrick, MichaelMhalla, MehdiPawlowski, MarcinIn [2, 18, 5, 19, 4] it has been shown that quantum resources can allow us
to achieve a family of equilibria that can have sometimes a better social welfare,
while guaranteeing privacy. We use graph games to propose a way to build non-
cooperative games from graph states, and we show how to achieve an unlimited
improvement with quantum advice compared to classical advice.Differentialgeometrie im Grossen
http://publications.mfo.de/handle/mfo/3763
Differentialgeometrie im Grossen
The topics discussed at the meeting reflected current trends in global differential geometry. These topics included complex geometry, Einstein metrics, geometric flows, metric geometry and manifolds satisfying curvature bounds.
Tue, 01 Jan 2019 00:00:00 GMThttp://publications.mfo.de/handle/mfo/37632019-01-01T00:00:00ZThe topics discussed at the meeting reflected current trends in global differential geometry. These topics included complex geometry, Einstein metrics, geometric flows, metric geometry and manifolds satisfying curvature bounds.Algebraic K-theory
http://publications.mfo.de/handle/mfo/3762
Algebraic K-theory
Algebraic $K$-theory has seen a fruitful development during the last three
years. Part of this recent progress was driven by the use of $\infty$-categories and
related techniques originally developed in algebraic topology. On the other hand we have
seen continuing progress based on motivic homotopy theory which has been an important
theme in relation to
algebraic $K$-theory for twenty years.
Tue, 01 Jan 2019 00:00:00 GMThttp://publications.mfo.de/handle/mfo/37622019-01-01T00:00:00ZAlgebraic $K$-theory has seen a fruitful development during the last three
years. Part of this recent progress was driven by the use of $\infty$-categories and
related techniques originally developed in algebraic topology. On the other hand we have
seen continuing progress based on motivic homotopy theory which has been an important
theme in relation to
algebraic $K$-theory for twenty years.Statistical Methodology and Theory for Functional and Topological Data
http://publications.mfo.de/handle/mfo/3761
Statistical Methodology and Theory for Functional and Topological Data
The workshop focuses on the statistical analysis of complex data which cannot be represented as realizations of finite-dimensional random vectors. An example of such data are functional data. They arise in a variety of climate, biological, medical, physical and engineering problems, where the observations can be represented by curves and surfaces. Fast advances in technology continuously produce a deluge of bigger data with even more complex structures such as arteries in the brain, bones of a human body or social networks. This has sparked enormous interest in more general statistical problems where the random observations are elements of abstract topological spaces.
The workshop will stimulate development of new statistical methods for these types of data and will be an ideal platform for discussing their theoretical properties (e.g. asymptotic optimality), computational performance, and new exciting applications in areas such as machine learning, image analysis, biometrics and econometrics.
Tue, 01 Jan 2019 00:00:00 GMThttp://publications.mfo.de/handle/mfo/37612019-01-01T00:00:00ZThe workshop focuses on the statistical analysis of complex data which cannot be represented as realizations of finite-dimensional random vectors. An example of such data are functional data. They arise in a variety of climate, biological, medical, physical and engineering problems, where the observations can be represented by curves and surfaces. Fast advances in technology continuously produce a deluge of bigger data with even more complex structures such as arteries in the brain, bones of a human body or social networks. This has sparked enormous interest in more general statistical problems where the random observations are elements of abstract topological spaces.
The workshop will stimulate development of new statistical methods for these types of data and will be an ideal platform for discussing their theoretical properties (e.g. asymptotic optimality), computational performance, and new exciting applications in areas such as machine learning, image analysis, biometrics and econometrics.Logarithmic Enumerative Geometry and Mirror Symmetry
http://publications.mfo.de/handle/mfo/3760
Logarithmic Enumerative Geometry and Mirror Symmetry
The new field of log enumerative geometry has formed at the crossroads
of mirror symmetry, Gromov-Witten theory and log geometry.
This workshop has been the first to promote this field and bring
together the junior and senior experts of this quickly evolving topic.
Spontaneous exchange, unforeseen mutual benefit as well as having each
participant give a presentation allowed for novel progress and insight.
Tue, 01 Jan 2019 00:00:00 GMThttp://publications.mfo.de/handle/mfo/37602019-01-01T00:00:00ZThe new field of log enumerative geometry has formed at the crossroads
of mirror symmetry, Gromov-Witten theory and log geometry.
This workshop has been the first to promote this field and bring
together the junior and senior experts of this quickly evolving topic.
Spontaneous exchange, unforeseen mutual benefit as well as having each
participant give a presentation allowed for novel progress and insight.Mixed-integer Nonlinear Optimization: a hatchery for modern mathematics
http://publications.mfo.de/handle/mfo/3759
Mixed-integer Nonlinear Optimization: a hatchery for modern mathematics
The second MFO Oberwolfach Workshop on Mixed-Integer Nonlinear Programming (MINLP) took place between 2nd and 8th June 2019. MINLP refers to one of the hardest Mathematical Programming (MP) problem classes, involving both nonlinear functions as well as continuous and integer decision variables. MP is a formal language for describing optimization problems, and is traditionally part of Operations Research (OR), which is itself at the intersection of mathematics, computer science, engineering and econometrics. The scientific program has covered the three announced areas (hierarchies of approximation, mixed-integer nonlinear optimal control, and dealing with uncertainties) with a variety of tutorials, talks, short research announcements, and a special "open problems'' session.
Tue, 01 Jan 2019 00:00:00 GMThttp://publications.mfo.de/handle/mfo/37592019-01-01T00:00:00ZThe second MFO Oberwolfach Workshop on Mixed-Integer Nonlinear Programming (MINLP) took place between 2nd and 8th June 2019. MINLP refers to one of the hardest Mathematical Programming (MP) problem classes, involving both nonlinear functions as well as continuous and integer decision variables. MP is a formal language for describing optimization problems, and is traditionally part of Operations Research (OR), which is itself at the intersection of mathematics, computer science, engineering and econometrics. The scientific program has covered the three announced areas (hierarchies of approximation, mixed-integer nonlinear optimal control, and dealing with uncertainties) with a variety of tutorials, talks, short research announcements, and a special "open problems'' session.Foundations and New Horizons for Causal Inference
http://publications.mfo.de/handle/mfo/3758
Foundations and New Horizons for Causal Inference
While causal inference is established in some disciplines such as econometrics and biostatistics, it is only starting to emerge as a
valuable tool in areas such as machine learning and artificial intelligence. The mathematical foundations of causal inference are fragmented at present.
The aim of the workshop "Foundations and new horizons for causal inference" was to
unify existing approaches and mathematical foundations as well as exchange ideas between different fields.
We regard this workshop as successful in that
it brought together researchers from different disciplines
who
were able to
learn from each other not only about
different formulations of related problems,
but also about solutions and methods that exist
in the different fields.
Tue, 01 Jan 2019 00:00:00 GMThttp://publications.mfo.de/handle/mfo/37582019-01-01T00:00:00ZWhile causal inference is established in some disciplines such as econometrics and biostatistics, it is only starting to emerge as a
valuable tool in areas such as machine learning and artificial intelligence. The mathematical foundations of causal inference are fragmented at present.
The aim of the workshop "Foundations and new horizons for causal inference" was to
unify existing approaches and mathematical foundations as well as exchange ideas between different fields.
We regard this workshop as successful in that
it brought together researchers from different disciplines
who
were able to
learn from each other not only about
different formulations of related problems,
but also about solutions and methods that exist
in the different fields.