Meetings/Workshops on Probability and Statistics, Game Theory in the United States (USA)

Institute for Pure and Applied Mathematics (IPAM) at UCLA

As algorithmic decisions and likelihood predictions reach ever more deeply, and with increasing consequence, into our lives, there is an increasing mandate that they be “fair”. Who counts? Machine learning algorithms learn from training data; when these are biased so are the algorithms they produce. The workshop will examine sources of sex and gender bias in data, with emphases on impoverished women; women of color; trans and non-binary persons; and older women. This program is preceded by a Graduate Summer School on Algorithmic Fairness organized by Cynthia Dwork, and Guy Rothblum (Weizmann Institute of Science).

JSM Is … One of the Largest Statistical Events in the World — More than 6,500 attendees from 52 countries; 600+ sessions, including invited, topic-contributed, contributed, and poster; More than 1,000 student attendees; 75+ employers hiring for more than 200 positions; 80+ exhibitors; and 13 participating societies. It is also one of the broadest, with topics ranging from statistical applications to methodology and theory to the expanding boundaries of statistics, such as analytics and data science. JSM also offers a unique opportunity for statisticians in academia, industry, and government to exchange ideas and explore opportunities for collaboration. Beginning statisticians (including current students) can learn from and interact with senior members of the profession.

Texas A&M University, College Station, TX

The goal of this in-person conference is to bring together researchers studying nonsmooth spaces from different perspectives, facilitating the exchange of ideas, problems, and mathematical techniques. Perspectives coming from probability, analysis on metric spaces, and Banach space theory are of particular emphasis. Interactions among these different fields have already proven exceptionally fruitful. For example, a famous fractal space constructed by Laakso to answer a purely metric measure theoretic question inspired a similar construction (pictured above) eventually used to characterize superreflexivity in Banach spaces. Later, uniform q-convexity, a quantitative refinement of superreflexivity, was metrically characterizing using Markov convexity – a measurement of the diffusivity of Markov processes in a metric space. Together with many more examples, these show how shared geometric objects play important roles in each subject while being viewed through different lenses. More interactions of this type will be necessary to solve important open problems, such as analyst’s traveling salesman-type problems and metric characterizations of other Banach properties.

Geometry and Topology,    Analysis

Held every 3 years, ICOSDA provides a platform for researchers and practitioners to share and discuss recent advances in distribution theory and its applications. The conference encourages opportunities for research collaborations.

American Statistical Association

American Statistical Association

American Statistical Association (ASA)