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Jeff Calder. Albert and Dorothy Marden Professor. School of Mathematics. University of Minnesota. 538 Vincent Hall. Phone: 612-626-1324. Email: jwcalder at umn dot edu. News. In the Fall 2023/Spring 2024 I will teach a new sequence of courses Math 5465/5466: Mathematics of Machine Learning and Data Analysis.
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2022. Poisson learning: Graph based semi-supervised learning at very low label rates. J Calder, B Cook, M Thorpe, D Slepcev. International Conference on Machine Learning, 1306-1316. , 2020. 87. 2020. The game theoretic p-Laplacian and semi-supervised learning with few labels. J Calder.
It is particularly exciting when this kind of analysis leads to new algorithms with performance guarantees. Research Website. Jeffrey Calder is a Associate Professor in The department of School of Mathematics. at the University of Minnesota.
- Graph-Based Learning
- Prediction with Expert Advice
- Mathematics and Anthropology
- Continuum Limits For Data Peeling
A major focus of my current research is graph-based learning. A graph structure encodes interdependencies among constituents, such as social media users, images or video sequences, or physical or biological agents, and provides a convenient representation for high dimensional data. Common tasks in graph-based learning include clustering (i.e., grou...
Prediction with expert advice refers to problems in online machine learning where a player synthesizes advice from many experts to make predictions in real-time. Together with Nadejda Drenska, we studied prediction with expert advice against an adversarial environment that controls the gains of the experts and is making their choices to ensure the ...
I am also interested in practical applications of machine learning to problems in science and engineering, and have begun a collaboration with Peter Olver and PhD candidate Katrina Yezzi-Woodley from the Department of Anthropology. A major open question for anthropologists is whether the geometry of broken bone fragments contains sufficient informa...
Many problems in science and engineering involve the sorting, or ordering, of large amounts of data, which can be challenging in the context of big data problems. There is a wide class of such sorting algorithms, called data peeling, that work by repeatedly peeling away extremal points. Different notions of extremality lead to different notions of ...
jcalder@umn.edu. Jeff's Webpage. Jeff Calder is an Associate Professor of Mathematics at the University of Minnesota. His research involves interactions between partial differential equations (PDE), numerical schemes, applied probability, and computer science.
Jeffrey Calder. Associate Professor, School of Mathematics. jwcalder@umn.edu (612) 626-1324. 538 Vincent Hall. Research Website. Maria-Carme Calderer. Professor ...
