Maxim Fedotov
I am a Ph.D. student in the Statistics, Probability and Machine Learning Research Group at Universitat Pompeu Fabra under the supervision of David Rossell and Gábor Lugosi.
I have broad research interests including high-dimensional inference, approximate inference and computation, interpretable machine learning, probabilistic guarantees, learning theory in general. I find particularly exciting blending statistical theory and optimization in methods with wide prospects for application.
Projects
- Projected Information Criteria for Variable Selection (with Gábor Lugosi and David Rossell; work in progress)
Presentations
Here is a list of talks and poster presentations I gave.
Contributed talks
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Projected Information Criteria for Variable Selection
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Projected Information Criteria for Variable Selection
Campus talks
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Projected L0 Criteria for Variable Selection in Regression Models
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Classical Analysis of Convergence and Complexity of Non-linear Smooth Optimization Algorithms
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Sequential Monte Carlo for Approximate Variable Selection in Generalized Linear Models
Contributed posters
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Projected and Updated L0 Criteria for Variable Selection in High-Dim. & Large-Sample Regression Models
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Projected-L0 Decoder for Variable Selection in Linear Regression
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Projected and One-Step L0 Criteria for Variable Selection
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Projected and One-Step L0 Criteria for Variable Selection
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Sequential Monte Carlo for Approximate Variable Selection in Generalized Linear Models