PhD positions in machine learning at Max Planck Institute Tübingen

I am looking for prospective Ph.D. students to work with me at the Max Planck Institute for Intelligent Systems in Tübingen, Germany. In particular, I am looking for students who have a strong mathematical background. The programming skill is a plus but is not mandatory. Our research projects will be at the intersection of kernel methods, counterfactual inference, causal inference, and learning theory (see https://krikamol.org/ for more details on my research interest). Successful candidates will also have a chance to engage in international collaborative projects. Last but not least, the successful candidates should be able to demonstrate that their motivation for the Ph.D. application is driven by a desire to solve difficult real-world problems and to push the boundary of science.

*** How to Apply ***

The applicants should already hold or are soon expected to obtain a master or equivalent degree in related areas. The application package must be a single PDF file and include

1) Curriculum vitae (CV),
2) academic transcripts (only bachelor and master degrees),
3) up to two pages in A4 of research statement describing your research experience and your research interest,
4) Names, affiliations, and email addresses of at most 3 references who can provide recommendation letters for you. Note that we will contact them directly so please make sure that the email addresses are correct.

The application package must be sent directly to [email protected]. The application will be open until we find the right candidates.

If you are at ICML19 or CVPR19, I am happy to talk in person.

*** Max Planck Institute & Tübingen ***

Max Planck Institute for Intelligent Systems (https://www.is.mpg.de/) is a world-class center for foundational research in machine learning and related areas. It is located in Tübingen, Germany (https://www.tuebingen.de/en/). Tübingen is a scenic medieval university town, cradled in what is simultaneously one of Germany’s most beautiful landscapes and one of Europe’s most economically successful areas. Most locals speak English and knowledge of German is not required to live here. The city is also not far from the Alps which is home to hundreds of high-quality ski resorts.

Best,
Krikamol

Berkeley using a new deep learning program to assess risk of suicide amongst veterans

Identifying patterns of risk within patients often involves a massive amount of data interpretation and algorithmic examination. New computer resources through Berkeley are today being dedicated to producing tailored algorithms for dynamic risk scores for VA patients and caregivers.

https://www.marktechpost.com/2019/04/19/berkeley-using-a-new-deep-learning-program-to-assess-risk-of-suicide-amongst-veterans/

Early Predictions of Movie Success: the Who, What, and When of Profitability


https://arxiv.org/pdf/1506.05382.pdf

A Review of “Compound Probabilistic Context-Free Grammars for Grammar Induction”

https://medium.com/@ryancotterell/a-review-of-compound-probabilistic-context-free-grammars-for-grammar-induction-2cd24ad060cf


paper https://arxiv.org/pdf/1906.10225.pdf

When Does Label Smoothing Help?

by Rafael Müller, Simon Kornblith, Geoffrey Hinton


https://arxiv.org/abs/1906.02629v1

Countdown Regression: Sharp and Calibrated Survival Predictions by Andrew Ng , Anand Avati, Tony Duan, Sharon Zhou, Kenneth Jung, Nigam H. Shah https://arxiv.org/abs/1806.08324v2

The future depends on some graduate student who is deeply suspicious of everything I have said. - Geoffrey Hinton https://t.iss.one/ArtificialIntelligenceArticles

Real-Time AR Self-Expression with Machine Learning

Augmented reality (AR) helps you do more with what you see by overlaying digital content and information on top of the physical world. For example, AR features coming to Google Maps will let you find your way with directions overlaid on top of your real world. With Playground - a creative mode in the Pixel camera -- you can use AR to see the world differently. And with the latest release of YouTube Stories and ARCore's new Augmented Faces API you can add objects like animated masks, glasses, 3D hats and more to your own selfies!

Direct Link: https://ai.googleblog.com/2019/03/real-time-ar-self-expression-with.html

[#basics][#deeplearningdevelopment]

0. Programming doubts, dont know where to ask, pls here first ?

https://stackoverflow.com/

0.1 Software versioning, software managing and production GIT

https://git-scm.com/book/en/v1/Getting-Started-Git-Basics

0.1.1 Searching for code that does something ?

https://github.com/
google for: https://github.com/repo: <term>

1. Python Programming, many references

https://www.fullstackpython.com/python-programming-language.html

A . Deep Learning Elementary Lectures by Geof Hinton

https://www.cs.toronto.edu/~hinton/coursera_lectures.html

A.1 Tensorflow Repository/**Documentation** and Issue Tracker (most popular and effective Deep Learning framework)

Issues: https://github.com/tensorflow/tensorflow/issues
Docs: https://www.tensorflow.org/api_docs/python/tf

A.2 Keras Mailing List (High Level Python Tensorflow API)

https://groups.google.com/forum/#!forum/keras-users

A.3 Tensorflow Computational Graphs Explained From Scratch

https://www.deepideas.net/deep-learning-from-scratch-i-computational-graphs/

B. Conda, One of the most impressives python virtual environment managers, essential for python development,

https://conda.io/en/latest/

B.0 Create virtual env only with the Conda manager and its dependencies: Miniconda
https://docs.conda.io/en/latest/miniconda.html

B.1 Anaconda, big Python Libs Distros
https://www.anaconda.com/

C. Conda Virtual Envs with Docker
https://medium.com/@chadlagore/conda-environments-with-docker-82cdc9d25754

Clothing Identification Tech from CVPR 2019!

paper: [https://www.profillic.com/paper/arxiv:1901.07973](https://www.profillic.com/paper/arxiv:1901.07973?fbclid=IwAR3bIPaWZk4Plhug0SvKdQt96dR8eAPqPgK7YX4TKlMkHC8OH5vVHwUjsao)

Deepfashion 2 provides a new benchmark for Detection, Pose Estimation, Segmentation and Re-Identification of Clothing Images

(The dataset contains 491K diverse images of 13 popular clothing categories from both commercial shopping stores and consumers)

The first AI universe sim is fast and accurate—and its creators don't know how it works
https://phys.org/news/2019-06-ai-universe-sim-fast-accurateand.html

Applied Data Scientists / Quantitative Researchers (Stats, Machine Learning, Python/R) @ YELP London

We are looking for Applied Data Scientists / Quantitative Researchers to join our London team. Please visit the

following link for more info: https://www.yelp.com/careers/job-openings/8c288764-b1db-4b72-ac75-07b34c9f9b74

For those who are interested in healthcare : Machine Learning for Healthcare 2019
https://www.mlforhc.org/

Training an AI agent to play Snake with TensorFlow 2.0.

Code by Paweł Kieliszczyk: https://github.com/pawel-kieliszczyk/snake-reinforcement-learning

#MachineLearning #ReinforcementLearning #TensorFlow

Fast Training of Sparse Graph Neural Networks on Dense Hardware

Balog et al.: https://arxiv.org/abs/1906.11786

#artificialintelligence #neuralnetworks #machinelearning #datascience

Growing Action Spaces
Farquhar et al.: https://arxiv.org/abs/1906.12266
#deeplearning #machinelearning #reinforcementlearning

PhD fellow in Theoretical Machine Learning
University of Copenhagen, Denmark

More Details: https://www.marktechpost.com/job/phd-fellow-in-theoretical-machine-learning/
Department of Computer Science, Faculty of Science at University of Copenhagen is offering a PhD scholarship in Theoretical Machine Learning commencing 01.10.2019 or as soon as possible thereafter.

How do neural networks see depth in single images?
https://arxiv.org/pdf/1905.07005.pdf

Robots that Learn to Adapt
https://bair.berkeley.edu/blog/2019/05/06/robot-adapt/