Mitschnitt des Livesets zum Opening von G-Lectric im Cafe Trauma am 17.12.2017

Live @ Cafe Trauma 17.12.2017

Liebe Franzi, lieber David, was ich euch schon immer sagen wollte: ... !

Kleines Techno-Liveset für die allerliebsten Franzi und David

Was für ein schöner Tag auf dem 'Puppenräuber' und was für eine Freude, dass ich ihn eröffnen durfte. Danke für all die Menschen, die mit mir gefiebert haben und mich so liebevoll unterstützt und getanzt haben! Viel Spaß mit dem Opening Liveset...

What a nice day on 'Puppenräuber' and what a pleasure opening it. I want to thank all the nice people for their support and for dancing! Here's the liveset, enjoy...

Liveset @ Puppenräuber Opening Wilde Möhre 2018

A Linear Tempering Paradigm for Hidden Markov Models
Nonstationary inference has found the most successful practice in many tasks such as data mining and classification. However, sparse inference is not a very flexible problem. In this work, we consider the problem from the sparsity perspective. We argue that sparse inference is an important problem in data science, because its solution is more flexible. Specifically, we formulate the problem as a linear domain in nonlinear terms, and propose a formulation of the problem that avoids the need of regularization. We prove the lower bound of the solution, and give an algorithm that does not need any regularization, thus proving the existence of a sparse problem. We further present an algorithm for sparse inference that works without any regularization, and we show that it can solve the nonlinearity problem. Finally, we give an algorithm for sparse inference that is efficient as well as suitable for many general models.

Eliah

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