PhD position: Artificial intelligence in Hepato-Pancreato-Biliary imaging
https://www.umcg.nl/EN/corporate/careers/Careers/Medicalscientific_staff/Paginas/PhD_position_Artificial_intelligence_in_Hepato-Pancreato-Biliary_imaging.aspx

Allow remote paper & poster presentations at scientific conferences


We are deeply concerned about how much flight traffic is caused by us - machine learners and, more generally, (data) scientists who should understand the dangers of climate change. Although we acknowledge that scientific exchange is difficult without traveling, we believe that video conferences - if set up properly - could become an increasingly important replacement. By streaming talks, some conferences already offer the opportunity to follow remotely. However, usually it is strictly required that authors present their work via physical attendance. Especially in machine learning, where conferences play an important role in scientific communication and careers, young scientists cannot realistically choose not to publish at the main venues, "just" because they are too far away.

We therefore ask all conferences, in particular all machine learning conferences (NeurIPS, ICML, AISTATS, ICLR, UAI, ...), to introduce the option of presenting papers or posters remotely, so that anyone be free to decide in his or her own conscience, whether the benefits of attending on site outweigh the negative consequences of the trip - both for climate and for family life. The implementation of these measures should ensure that presenting remotely actually does reduce conference emissions.

https://www.change.org/p/organizers-of-data-science-and-machine-learning-conferences-neurips-icml-aistats-iclr-uai-allow-remote-paper-poster-presentations-at-conferences

A 2020 Guide To Text Moderation with NLP and Deep Learning
The pervasive problem of hate speech, biases and stereotypes has persisted in society for a long time. This article shows how you can detect toxic language automatically by exploring several state of the art deep learning and NLP approaches and implementing a BERT embeddings based multi-label classifier.

Article link: https://nanonets.com/blog/text-moderation/

Neural Module Networks for Reasoning over Text
Gupta et al.: https://arxiv.org/abs/1912.04971
Code: https://nitishgupta.github.io/nmn-drop
#NeuralNetworks #Reasoning #SymbolicAI

Neural Network Training with Approximate Logarithmic Computations
Arnab Sanyal, Peter A. Beerel, Keith M. Chugg
An end-to-end training and inference scheme that eliminates multiplications by approximate operations in the log-domain which has the potential to significantly reduce implementation complexity.
Arxiv pre-print - https://arxiv.org/abs/1910.09876
Research blog - https://towardsdatascience.com/neural-networks-training-with-approximate-logarithmic-computations-44516f32b15b

This paper recently got accepted in the 45th IEEE International Conference on Acoustics, Speech, and Signal Processing ICASSP 2020, set to convene in Barcelona Spain, between May 4, 2020, and May 8, 2020.

Deep Learning and Reinforcement Learning Summer School 2020 will take place in Montreal on July 29 – August 6, 2020
https://dlrlsummerschool.ca/

Map of Ethical and Right-Based Approaches
Fjeld et al.: https://ai-hr.cyber.harvard.edu/primp-viz.html
This data visualization presents thirty-two sets of principles side by side, enabling comparison between efforts from governments, companies, advocacy groups, and multi-stakeholder initiatives.
#AIGovernance #ArtificialIntelligence #DeepLearning

Fugro wins ISFOG 2020 machine-learning competition


https://www.satellite-evolution.com/single-post/2020/02/06/Fugro-wins-ISFOG-2020-machine-learning-competition

Take a closer look at this remarkable piece by Hasson, Nastase, and Goldstein. It is amazing.
@ArtificialIntelligenceArticles

You will find answers to questions like: Are artificial neural networks black box models? How do they compare to biological neural networks? Which is the role of evolution in the learning process? Have cognitive and computational neuroscience followed the right path in understanding mind processes? And what about psychology?

Only one excerpt now; there were too many good ones but the space here is not enough!
@ArtificialIntelligenceArticles
"[A]rtificial networks, as opposed to humans, fail miserably in situations that require generalization and extrapolation across contexts ... Instead of imposing efficiency, simplicity, and interpretability wholesale across neural system, psychologists should ask how our uniquely human cognitive capacities can extract explicit and compact knowledge about the outside world from the billions of direct-fit model weights. ... How high-level cognitive functions emerge from brute-force over-parameterized biological neural networks is likely to be a central question for future cognitive studies." https://www.biorxiv.org/content/10.1101/764258v3

join
@ArtificialIntelligenceArticles

Project DeepSpeech
A TensorFlow implementation of Baidu's DeepSpeech architecture

Code: https://github.com/mozilla/DeepSpeech

Tensorflow & Pytorch: https://github.com/DemisEom/SpecAugment

SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition:

https://arxiv.org/pdf/1904.08779.pdf

IS TESLA DUMPING PYTHON FOR THIS PROGRAMMING LANGUAGE
https://analyticsindiamag.com/elon-musk-tesla-python-c-programming-language-tensorflow-pytorch/

t-SNE algorithm on MNIST dataset in Kaggle kernels. NVIDIA's Rapids library with GPU acceleration. The algorithm achieves a 2000x speedup as compared to the sklearn version on CPU!
https://www.kaggle.com/tunguz/mnist-2d-t-sne-with-rapids

ML and NLP Publications in 2019
https://www.marekrei.com/blog/ml-and-nlp-publications-in-2019/

Researchers Reveal Secrets of 2,800-year-old Hebrew Texts Using Artificial Intelligence


https://www.haaretz.com/archaeology/.premium.MAGAZINE-researchers-reveal-secrets-of-2-800-year-old-hebrew-texts-using-ai-1.8434763

From how to why: An overview of causal inference in machine learning
https://www.ericsson.com/en/blog/2020/2/causal-inference-machine-learning