Seven Myths in Machine Learning Research

02/18/2019
by   Oscar Chang, et al.
8

We present seven myths commonly believed to be true in machine learning research, circa Feb 2019. This is an archival copy of the blog post at https://crazyoscarchang.github.io/2019/02/16/seven-myths-in-machine-learning-research/

READ FULL TEXT

page 4

page 6

page 7

page 10

page 16

page 19

page 20

page 21

research
04/11/2021

Dissecting the square into seven or nine congruent parts

We give a computer-based proof of the following fact: If a square is div...
research
09/23/2022

Planar graph with twin-width seven

We construct a planar graph with twin-width equal to seven....
research
01/11/2018

Theoretical Impediments to Machine Learning With Seven Sparks from the Causal Revolution

Current machine learning systems operate, almost exclusively, in a stati...
research
11/04/2021

OpenFWI: Benchmark Seismic Datasets for Machine Learning-Based Full Waveform Inversion

We present OpenFWI, a collection of large-scale open-source benchmark da...
research
05/03/2021

Machine Learning Applications for Therapeutic Tasks with Genomics Data

Thanks to the increasing availability of genomics and other biomedical d...
research
03/20/2023

Seven open problems in applied combinatorics

We present and discuss seven different open problems in applied combinat...
research
07/22/2011

Analogy perception applied to seven tests of word comprehension

It has been argued that analogy is the core of cognition. In AI research...

Please sign up or login with your details

Forgot password? Click here to reset