ALEXANDER-SCHWING.DE

Alexander G. Schwing

There is nothing more practical. Than a good theory. My research interests are optimization algorithms (e.g., primal-dual methods), statistical models like structured predictors and parallelization of implementations for high performance computing environments. Interesting playground for all three fields are inference and structured prediction in machine learning as well as computer vision, and in particular 3D scene understanding. I am currently working with Prof. Ruslan Salakhutdinov. With an ETH medal.

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Alexander G. Schwing | alexander-schwing.de Reviews

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There is nothing more practical. Than a good theory. My research interests are optimization algorithms (e.g., primal-dual methods), statistical models like structured predictors and parallelization of implementations for high performance computing environments. Interesting playground for all three fields are inference and structured prediction in machine learning as well as computer vision, and in particular 3D scene understanding. I am currently working with Prof. Ruslan Salakhutdinov. With an ETH medal.

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1 projects

2 publications

3 teaching

4 links

5 kurt lewin

6 academics

7 computer science department

8 prof tamir hazan

9 acknowledgments

10 the fields institute

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Alexander G. Schwing | alexander-schwing.de Reviews

https://alexander-schwing.de

There is nothing more practical. Than a good theory. My research interests are optimization algorithms (e.g., primal-dual methods), statistical models like structured predictors and parallelization of implementations for high performance computing environments. Interesting playground for all three fields are inference and structured prediction in machine learning as well as computer vision, and in particular 3D scene understanding. I am currently working with Prof. Ruslan Salakhutdinov. With an ETH medal.

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alexander-schwing.de

1

Alexander G. Schwing

http://www.alexander-schwing.de/projectsOverview.php

Change is not made without inconvenience,. Even from worse to better. AG Schwing, T. Hazan. Distributed Structured Prediction with and without Latent Variables for General Graphical Models. AG Schwing, S. Fidler. 3D Indoor Scene Understanding. AG Schwing, T. Hazan. Inference in Graphical Models. AG Schwing, C. Zach. Adaptive Random Forest - How many ` experts' to ask before making a decision? 2009 - 2016 Alexander G. Schwing.

2

Alexander G. Schwing

http://www.alexander-schwing.de/teaching.php

By three methods we may learn wisdom:. First, by reflection, which is noblest;. Second, by imitation, which is easiest;. And third by experience, which is the bitterest. Winter 2016: Gaussian Processes (Guest Lecture in: Probabilistic Graphical Models). Fall 2015: Structured Prediction (Guest Lecture in: Intro to Machine Learning). Fall 2015: Neural Networks (Guest Lecture in: Intro to Image Understanding). Winter 2015: Deep Learning and Structured Prediction (Guest Lecture in: Intro to Machine Learning).

3

Alexander G. Schwing

http://www.alexander-schwing.de/links.php

The smallest act of kindness. Is worth more than the grandest intention. Some of the books I enjoyed reading or I like to use as a reference:. D P Bertsekas; Nonlinear Programming. C M Bishop; Pattern Recognition and Machine Learning. S Boyd and L. Vandenberghe; Convex Optimization. T Hastie, R. Tibshirani and J. Friedman; The Elements of Statistical Learning: Data Mining, Inference and Prediction. D Koller and N. Friedman; Probabilistic Graphical Models: Principles and Techniques. Library for solving li...

4

Alexander G. Schwing

http://www.alexander-schwing.de/projectsAdaptiveRandomForest.php

One problem in the field of statistics has been that everyone wants to be a theorist. Part of this is envy - the real sciences are based on mathematical theory. In the universities for this century, the glamor and prestige has been in mathematical models and theorems, no matter how irrelevant. Adaptive Random Forest - How many experts to ask before making a decision? By: AG. Schwing, C. Zach. How many people should you ask if you are not sure about your way? 2009 - 2016 Alexander G. Schwing.

5

Alexander G. Schwing

http://www.alexander-schwing.de/publications.php

If I have ever made any valuable discoveries,. It has been owing more to patient attention,. Than to any other talent. Y Song, A.G. Schwing, R. Zemel and R. Urtasun; Training Deep Neural Networks via Direct Loss Minimization. Int'l Conf. on Machine Learning (ICML); 2016. Author = {Y. Song and A. G. Schwing and R. Zemel and R. Urtasun},. Title = { Training Deep Neural Networks via Direct Loss Minimization} ,. Booktitle = {Proc. ICML},. Year = {2016},. Booktitle = {Proc. CVPR},. Year = {2016},. Z Zhang*, A...

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alexander-schwing.de

Alexander G. Schwing

There is nothing more practical. Than a good theory. My research interests are optimization algorithms (e.g., primal-dual methods), statistical models like structured predictors and parallelization of implementations for high performance computing environments. Interesting playground for all three fields are inference and structured prediction in machine learning as well as computer vision, and in particular 3D scene understanding. I am currently working with Prof. Ruslan Salakhutdinov. With an ETH medal.

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