Remove 2015 Remove Experimentation Remove Risk Remove Strategy
article thumbnail

Drug Discovery Needs AI To Discover More Treatments

Smart Data Collective

In a report on the failure rates of drug discovery efforts between 2013 and 2015, Richard K. Without better methodology, difficult-to-treat and ill-understood conditions and diseases are at risk of staying that way. The 15% failure rate of new drugs due to incompatible company strategies doesn’t have to continue.

article thumbnail

Towards optimal experimentation in online systems

The Unofficial Google Data Science Blog

It is also a sound strategy when experimenting with several parameters at the same time. To find optimal values of two parameters experimentally, the obvious strategy would be to experiment with and update them in separate, sequential stages. (And sometimes even if it is not[1].) We use these designs frequently, and so can you.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Changing assignment weights with time-based confounders

The Unofficial Google Data Science Blog

by ALEXANDER WAKIM Ramp-up and multi-armed bandits (MAB) are common strategies in online controlled experiments (OCE). These strategies involve changing assignment weights during an experiment. The first is a strategy called ramp-up and is advised by many experts in the field [1].

article thumbnail

The 2015 Digital Marketing Rule Book. Change or Perish.

Occam's Razor

A huge part of the last few years for me have been about bringing more data, better strategies, more powerful tools, ever more impactful keynotes to people around the world. Get the senior-most people in the largest companies in the world to unlock their imaginations when it comes to their digital existence via impactful digital strategies.

Marketing 140
article thumbnail

To Balance or Not to Balance?

The Unofficial Google Data Science Blog

In an ideal world, experimentation through randomization of the treatment assignment allows the identification and consistent estimation of causal effects. See Hainmueller (2012), and the work of Zhao & Percival (2015) for more details on how this optimization problem is solved, and for further discussion. 2014): 243-263.

article thumbnail

Themes and Conferences per Pacoid, Episode 11

Domino Data Lab

For more background about program synthesis, check out “ Program Synthesis Explained ” by James Bornholt from 2015, as well as the more recent “ Program Synthesis in 2017-18 ” by Alex Polozov from 2018. For details, see their SIGMOD 2015 paper where Michael Armbrust & co. This field is guaranteed to get interesting. SQL and Spark.

Metadata 105
article thumbnail

The trinity of errors in applying confidence intervals: An exploration using Statsmodels

O'Reilly on Data

As the number of experimental trials N approaches infinity, the probability of E equals M/N. Modern portfolio theory assumes that rational, risk-averse investors demand a risk premium, a return in excess of a risk-free asset such as a treasury bill, for investing in risky assets such as equities. on average.