zacklipton.wordpress.com
“We Don’t Play for Free” | zacklipton
https://zacklipton.wordpress.com/2014/08/06/we-dont-play-for-free
Machine learning, music, miscellany. 8220;We Don’t Play for Free”. August 6, 2014. I hope to organize these thoughts at some point and deal with this topic more seriously. But I wanted to write something to document my ruminations regarding remuneration in the performing arts, specifically jazz. I felt like a prostitute. I felt artistically stifled. Music had ceased to be an intellectual or creative pursuit. Since beginning to play again, I have played most nights of the week. And I have made a polic...
approximatelycorrect.com
Elections – Approximately Correct
http://www.approximatelycorrect.com/tag/elections
Technical and Social Perspectives on Machine Learning Contact. The Failure of Simple Narratives. An aside: Not all political issues are scientific or technical. The relative value of free speech vs the danger of hate speech may be an intrinsically subjective judgment. But many issues, such as global warming, explicitly exhibit scientific dimensions.]. Technical developments can necessitate policy shifts. Absent the capacity to warm the planet or the ability to detect such warming, one couldn’t ...Leave a...
kdnuggets.com
The Myth of Model Interpretability
http://www.kdnuggets.com/2015/04/model-interpretability-neural-networks-deep-learning.html
Data Mining, Analytics, Big Data, and Data Science. Subscribe to KDnuggets News. Raquo; » The Myth of Model Interpretability ( 15:n13. Latest News, Stories. The 10 Algorithms Machine Learning Engineers Need to Know. Approaching (Almost) Any Machine Learning Problem. Join Us for the Top Analytics Conference. Acuity Solutions (BluVector): Applied Data Scientist. More News and Stories. The Myth of Model Interpretability. By Zachary Chase Lipton. In a previous post, (Deep Learning's Deep Flaws)'s Deep Flaws.
approximatelycorrect.com
Computational Creativity – Approximately Correct
http://www.approximatelycorrect.com/category/computational-creativity
Technical and Social Perspectives on Machine Learning Contact. Are Deep Neural Networks Creative? This article is a revised version reposted with permission from KDnuggets. Are deep neural networks creative? Given recent press coverage of art-generating deep learning, it might seem like a reasonable question. In February, Wired wrote of a gallery exhibition. Featuring works generated by neural networks. The works were created using Google’s. And apply it to the content of another image (say a photograph).
approximatelycorrect.com
Machine Learning – Approximately Correct
http://www.approximatelycorrect.com/tag/machine-learning
Technical and Social Perspectives on Machine Learning Contact. Fake News Challenge – Revised and Revisited. The organizers of the The Fake News Challenge. Have subjected it to a significant overhaul. In this light, many of my criticisms of the challenge no longer apply. Last month, I posted a critical piece addressing the fake news challenge. 8220;Hillary Clinton eats babies”. My response criticized the challenge as both ill-specified. How do we know the supporting documents are legit? And body text (from.
approximatelycorrect.com
Policy – Approximately Correct
http://www.approximatelycorrect.com/tag/policy
Technical and Social Perspectives on Machine Learning Contact. Policy Field Notes: NIPS Update. Conversations about the social impact of AI often are very abstract, focusing on broad generalizations about technology rather than talking about the specific state of the research field. That makes it challenging to have a full conversation about what good public policy regarding AI would be like. In the interest of helping to bridge that gap, Jack Clark. January 5, 2017. January 5, 2017. The #Data4Good at IC...
approximatelycorrect.com
Zachary C. Lipton – Approximately Correct
http://www.approximatelycorrect.com/author/zack
Technical and Social Perspectives on Machine Learning Contact. Author: Zachary C. Lipton. Is a PhD student in the Computer Science Engineering department at the University of California, San Diego. He is interested in both theoretical foundations and applications of machine learning. In addition to his work at UCSD, he has worked with Microsoft Research Redmond, Microsoft Research Bangalore, and Amazon Core Machine Learning. Fake News Challenge – Revised and Revisited. In version 2.0, the challenge p...
approximatelycorrect.com
The Failure of Simple Narratives – Approximately Correct
http://www.approximatelycorrect.com/2016/11/10/the-failure-of-simple-narratives
Technical and Social Perspectives on Machine Learning Contact. The Failure of Simple Narratives. An aside: Not all political issues are scientific or technical. The relative value of free speech vs the danger of hate speech may be an intrinsically subjective judgment. But many issues, such as global warming, explicitly exhibit scientific dimensions.]. Technical developments can necessitate policy shifts. Absent the capacity to warm the planet or the ability to detect such warming, one couldn’t ...The rol...
approximatelycorrect.com
Jack Clark – Approximately Correct
http://www.approximatelycorrect.com/author/jack
Technical and Social Perspectives on Machine Learning Contact. Strategy and Communications Director at OpenAI. Trawler of Arxiv, hiker of hills. Policy Field Notes: NIPS Update. And I have been playing around with doing recaps that’ll take a selection of papers from a recent conference and talk about the longer term policy implications of the work. This one covers papers that appeared at NIPS 2016. Continue reading “Policy Field Notes: NIPS Update”. January 5, 2017. January 5, 2017. Zachary C. Lipton.
