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Looking back on 2018, looking to 2019

转载自:http://ianozsvald.com/2019/01/07/looking-back-on-2018-looking-to-2019/

Ian


发表于 2019-01-07

So last year was a damned hard year – ignoring Brexit and other international foolishness, on a personal level (without going in to details) by mid-year I was emotionally wiped out. A collection of health issues between family and friends kept rearing their ugly heads and over time I ran very low of emotionally supportive energy to share. Our not-so-old cat suddenly dying of kidney failure just about topped the year off. Thankfully by Christmas most of the health issues had sorted themselves out, massively reducing their induced stress.

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If you did not already know

转载自:https://analytixon.com/2019/01/07/if-you-did-not-already-know-603/

Michael Laux


发表于 2019-01-07

Evolutionary-Neural Hybrid Agent (Evo-NAS) Neural Architecture Search has recently shown potential to automate the design of Neural Networks. The use of Neural Network agents trained with Reinforcement Learning can offer the possibility to learn complex patterns, as well as the ability to explore a vast and compositional search space. On the other hand, evolutionary algorithms offer the greediness and sample efficiency needed for such an application, as each sample requires a considerable amount of resources. We propose a class of Evolutionary-Neural hybrid agents (Evo-NAS), that retain the best qualities of the two approaches. We show that the Evo-NAS agent can outperform both Neural and Evolutionary agents, both on a synthetic task, and on architecture search for a suite of text classification datasets. …

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Long-awaited updates to htmlTable

转载自:http://feedproxy.google.com/~r/RBloggers/~3/JK6O4EkY5r8/

Max Gordon


发表于 2019-01-07

Lets celebrate 2019 with some updates to my most popular package ever, the htmlTable. The image is CC by Thomas Hawk One of the most pleasant surprises has been the popularity of my htmlTable-package with more than 100k downloads per month. This is all thanks to more popular packages relying on it and the web expanding beyond its original boundaries. As a thank you I have taken the time to update and fix some features (the 1.13 release) – enjoy!

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Whats new on arXiv

转载自:https://analytixon.com/2019/01/06/whats-new-on-arxiv-861/

Michael Laux


发表于 2019-01-06

Low-Cost Device Prototype for Automatic Medical Diagnosis Using Deep Learning Methods

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Announcing the ultimate seminar speaker contest: 2019 edition!

转载自:https://andrewgelman.com/2019/01/06/announcing-the-ultimate-seminar-speaker-contest-2019-edition/

Andrew


发表于 2019-01-06

Paul Davidson made the bracket for us (thanks, Paul!):

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R Packages worth a look

转载自:https://analytixon.com/2019/01/07/r-packages-worth-a-look-1389/

Michael Laux


发表于 2019-01-06

Tools for Binning Data (rbin)Manually bin data using weight of evidence and information value. Includes other binning methods such as equal length, quantile and winsorized. Options …

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Distilled News

转载自:https://analytixon.com/2019/01/06/distilled-news-946/

Michael Laux


发表于 2019-01-06

Beginner’s guide to Speech Analysis

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Rotagrams

转载自:http://datagenetics.com/blog/january32019/index.html

未知


发表于 2019-01-06

Some of my earliest computer programming was done in 6502 assembly language. In most assembly languages there are a collection of instruction for rotating and shifting bits left and right in a byte (different instructions depending whether the carry bit is involved). Shifting to the left is the equivalent of multiplication by a power of two for each place, and to the right, dividing.

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Timing the Same Algorithm in R, Python, and C++

转载自:http://www.win-vector.com/blog/2019/01/timing-of-the-same-algorithm-in-r-python-and-c/

John Mount


发表于 2019-01-06

While developing the RcppDynProg R package I took a little extra time to port the core algorithm from C++ to both R and Python.

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R Packages worth a look

转载自:https://analytixon.com/2019/01/06/r-packages-worth-a-look-1388/

Michael Laux


发表于 2019-01-06

Statistical Learning Methods for Optimizing Dynamic Treatment Regimes (DTRlearn2)We provide a comprehensive software to estimate general K-stage DTRs from SMARTs with Q-learning and a variety of outcome-weighted learning methods. Pe …

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