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Podcast: Data Nation
IDSS faculty and industry experts unpack how data can be used to lead, mislead, manipulate, and inform the public’s viewpoints and decisions. Season 2 has begun!
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MicroMasters in Statistics and Data Science
Learn data science methods and tools, get hands-on training in data analysis and machine learning, and find opportunities in a growing field. Watch our latest informational webinar.
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Data Science and Machine Learning: Making Data-Driven Decisions
This 10-week online program covers statistics and Python foundations, machine learning, prediction, recommendation systems, and more.
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Nonparametric Bayesian Statistics
Bayesian nonparametrics provides modeling solutions by replacing the finite-dimensional prior distributions of classical Bayesian analysis with infinite-dimensional stochastic processes.
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Causal inference and applications to learning gene regulatory networks
Causal inference: Geometry of conditional independence structures for 3-node directed Gaussian graphical models.
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Combinatorial learning with set functions
Learning problems that involve combinatorial objects are ubiquitous – they include the prediction of graphs, assignments, rankings, trees, groups of discrete labels or preferred sets of a user; the expression of prior structural knowledge for regularization, the identification of sets of important variables, or…
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Online Learning
In this line of research, we develop strategies to optimize utility in dynamic environments in an optimal and efficient fashion.
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Statistical and Computational Tradeoffs
Computational limitations of statistical problems have largely been ignored or simply overcome by ad hoc relaxations techniques.