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teaching:ws2019:dltheory_ws19 [2019/10/08 13:15] frerix |
teaching:ws2019:dltheory_ws19 [2019/10/08 13:47] (current) frerix |
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| Modern deep learning methods have shown remarkable success in various domains of machine learning. However, our theoretical understanding of such methods remains rather shallow. Recently, novel ideas to better understand aspects of optimization and generalization in these models have emerged that require rethinking classical concepts in these domains. A prominent example is the implicit bias of optimization methods in an overparameterized regime. We will discuss such ideas from the computational and statistical viewpoint. | Modern deep learning methods have shown remarkable success in various domains of machine learning. However, our theoretical understanding of such methods remains rather shallow. Recently, novel ideas to better understand aspects of optimization and generalization in these models have emerged that require rethinking classical concepts in these domains. A prominent example is the implicit bias of optimization methods in an overparameterized regime. We will discuss such ideas from the computational and statistical viewpoint. | ||
| - | ==== Organization | + | ==== Material and Schedule |
| + | Seminar material and the schedule can be accessed [[teaching: | ||
| + | ==== Organization ==== | ||
| == General == | == General == | ||
| * ** Organizer: | * ** Organizer: | ||
