Industrial Researcher

Report info

Report date	Tuesday, May 17, 2011 2:58:25 PM BST

Start date	Monday, April 4, 2011 12:47:00 AM BST

Stop date	Sunday, April 24, 2011 11:59:00 PM BST

Stored responses	56

Number of completed responses	46

Question 1

Do you conduct research in, teach, or study machine learning?

Frequency table
Choices	Absolute frequency	Relative frequency	Adjusted relative frequency
Yes	55	98.21%	98.21%
No	1	1.79%	1.79%
Sum:	56	100%	100%
Total answered: 56

Question 2

What do you do?

Frequency table
Choices	Absolute frequency	Relative frequency	Adjusted relative frequency
Researcher in an industrial laboratory	56	100%	100%
Sum:	56	100%	100%
Total answered: 56

Question 3

Which department(s) are you based in? (You may select more than one)

Frequency table
Choices	Absolute frequency	Relative frequency	Adjusted relative frequency
Biology	2	1.85%	3.57%
Cognitive science	1	0.93%	1.79%
Computer science	42	38.89%	75%
Economics	1	0.93%	1.79%
Electrical engineering	6	5.56%	10.71%
Engineering sciences	6	5.56%	10.71%
Machine Learning	28	25.93%	50%
Mathematics	3	2.78%	5.36%
Neuroscience	4	3.7%	7.14%
Operations research	3	2.78%	5.36%
Physics	1	0.93%	1.79%
Statistics	6	5.56%	10.71%
Other:	5	4.63%	8.93%
Sum:	108	100%	100%
Total answered: 56

Text input

Natural language processing

Research Team

NLP

User Interaction (Anthropology)

Finance

Question 4

Which conferences do you regularly attend? (You may pick more than one)

Frequency table
Choices	Absolute frequency	Relative frequency	Adjusted relative frequency
AAAI	5	3.85%	11.36%
ACL	7	5.38%	15.91%
AISTATS	6	4.62%	13.64%
CogSci	1	0.77%	2.27%
COLT	1	0.77%	2.27%
CoNLL	2	1.54%	4.55%
CVPR	6	4.62%	13.64%
ECCV	4	3.08%	9.09%
ECML	12	9.23%	27.27%
EMNLP	5	3.85%	11.36%
ICCV	4	3.08%	9.09%
ICML	27	20.77%	61.36%
IJCAI	6	4.62%	13.64%
ISMB	1	0.77%	2.27%
NAACL	5	3.85%	11.36%
NIPS	25	19.23%	56.82%
SIGIR	4	3.08%	9.09%
Snowbird	2	1.54%	4.55%
UAI	7	5.38%	15.91%
Sum:	130	100%	100%
Total answered: 44

Text input

UMAP

KDD

AGI

Interspeech, ICASP

Compstat
IFCS

VISWEEK

MICCAI

Some USENIX (NSDI, etc).

SIG KDD

KDD

SfN

Question 5

Do you have (or have you had) students in machine learning?

Frequency table
Choices	Absolute frequency	Relative frequency	Adjusted relative frequency
Yes	26	46.43%	46.43%
No	30	53.57%	53.57%
Sum:	56	100%	100%
Total answered: 56

Question 6

What is your educational background/training/disciplinary background? (You may select more than one)

Frequency table
Choices	Absolute frequency	Relative frequency	Adjusted relative frequency
Cognitive science	2	1.75%	3.64%
Computer science	40	35.09%	72.73%
Economics	4	3.51%	7.27%
Electrical engineering	10	8.77%	18.18%
Engineering sciences	5	4.39%	9.09%
Machine Learning	24	21.05%	43.64%
Mathematics	11	9.65%	20%
Neuroscience	4	3.51%	7.27%
Operations research	3	2.63%	5.45%
Physics	3	2.63%	5.45%
Psychology	1	0.88%	1.82%
Statistics	5	4.39%	9.09%
Other:	2	1.75%	3.64%
Sum:	114	100%	100%
Total answered: 55

Text input

Linguistics

Linguistics

Question 7

Did your educational background prepare you well for research in machine learning?

Frequency table
Levels	Absolute frequency	Relative frequency	Adjusted relative frequency
2	10	17.86%	18.18%
3	25	44.64%	45.45%
4 (Well prepared)	20	35.71%	36.36%
Not answered:	1	1.79%	-
Sum:	56	100%	100%
Total answered: 55

Question 8

What educational backgrounds do your students have? (You may select more than one)

Frequency table
Choices	Absolute frequency	Relative frequency	Adjusted relative frequency
Computer science	21	39.62%	87.5%
Economics	1	1.89%	4.17%
Electrical engineering	4	7.55%	16.67%
Engineering sciences	4	7.55%	16.67%
Machine Learning	6	11.32%	25%
Mathematics	5	9.43%	20.83%
Neuroscience	2	3.77%	8.33%
Operations research	1	1.89%	4.17%
Physics	3	5.66%	12.5%
Statistics	6	11.32%	25%
Sum:	53	100%	100%
Total answered: 24

Question 9

Did the educational backgrounds of your students prepare them well for studying machine learning?

Frequency table
Levels	Absolute frequency	Relative frequency	Adjusted relative frequency
2	9	16.07%	37.5%
3	10	17.86%	41.67%
4 (Well prepared)	5	8.93%	20.83%
Not answered:	32	57.14%	-
Sum:	56	100%	100%
Total answered: 24

Question 10

In your opinion, what will constitute good educational backgrounds for a graduate student entering machine learning? (You may select as many as you like).

Frequency table
Choices	Absolute frequency	Relative frequency	Adjusted relative frequency
Biology	1	0.44%	1.92%
Cognitive science	6	2.65%	11.54%
Computer science	35	15.49%	67.31%
Economics	2	0.88%	3.85%
Electrical engineering	9	3.98%	17.31%
Engineering sciences	6	2.65%	11.54%
Machine Learning	39	17.26%	75%
Mathematics	41	18.14%	78.85%
Neuroscience	5	2.21%	9.62%
Operations research	19	8.41%	36.54%
Physics	14	6.19%	26.92%
Psychology	2	0.88%	3.85%
Social science	1	0.44%	1.92%
Statistics	45	19.91%	86.54%
Other:	1	0.44%	1.92%
Sum:	226	100%	100%
Total answered: 52

Text input

Artificial Intelligence

Text input

Above answers are for "core" ML - others are useful as application areas, etc.

have studied the area of the application

Possibly plus some knowledge of a domain. E.g. economics, biology, neuroscience... Exactly which domain probably doesn't matter.

Mathematics is the most important, the earlier, the most one do math the better for ML.
Then, stats and optimization are the most important.
The only thing that matter in CS is awareness to computational complexity.

Question 11

What area(s) in machine learning do you work in? (You may select more than one)

Frequency table
Choices	Absolute frequency	Relative frequency	Adjusted relative frequency
Bayesian statistics	23	10.55%	48.94%
Control and planning	4	1.83%	8.51%
Deep learning	7	3.21%	14.89%
Dimensionality reduction	13	5.96%	27.66%
Graphical models	21	9.63%	44.68%
Information theory	5	2.29%	10.64%
Kernel methods	7	3.21%	14.89%
Learning theory	4	1.83%	8.51%
Manifold learning	6	2.75%	12.77%
Model selection	10	4.59%	21.28%
Neural networks	7	3.21%	14.89%
Nonparametric methods	6	2.75%	12.77%
Online learning	8	3.67%	17.02%
Optimization	9	4.13%	19.15%
Reinforcement learning	6	2.75%	12.77%
Relational learning	6	2.75%	12.77%
Semisupervised learning	12	5.5%	25.53%
Sparse learning	7	3.21%	14.89%
Statistical physics of learning	1	0.46%	2.13%
Structured learning	10	4.59%	21.28%
Supervised learning	20	9.17%	42.55%
Time series modelling	6	2.75%	12.77%
Unsupervised learning	20	9.17%	42.55%
Sum:	218	100%	100%
Total answered: 47

Question 12

What other area(s) do you work in? (You may select more than one)

Frequency table
Choices	Absolute frequency	Relative frequency	Adjusted relative frequency
Artificial intelligence	14	7.22%	29.17%
Bioinformatics	8	4.12%	16.67%
Brain, medical imaging	3	1.55%	6.25%
Cognitive science	1	0.52%	2.08%
Collaborative filtering	7	3.61%	14.58%
Computer vision	7	3.61%	14.58%
Computer science	13	6.7%	27.08%
Databases	2	1.03%	4.17%
Data mining	22	11.34%	45.83%
Electrical engineering	1	0.52%	2.08%
Genetics	3	1.55%	6.25%
Hardware technologies	1	0.52%	2.08%
Multimedia processing	3	1.55%	6.25%
Linguistics	4	2.06%	8.33%
Image processing	5	2.58%	10.42%
Information retrieval	12	6.19%	25%
Mathematics	3	1.55%	6.25%
Natural language processing	16	8.25%	33.33%
Network analysis	3	1.55%	6.25%
Neuroscience	2	1.03%	4.17%
Operations research	4	2.06%	8.33%
Psychology	1	0.52%	2.08%
Signal processing	7	3.61%	14.58%
Social science	2	1.03%	4.17%
Speech processing	4	2.06%	8.33%
Statistics	12	6.19%	25%
Systems biology	1	0.52%	2.08%
Text and web analysis	29	14.95%	60.42%
Other:	4	2.06%	8.33%
Sum:	194	100%	100%
Total answered: 48

Text input

Finance

Behavior/User Modeling

finance

Applications in Medicine

Question 13

In your opinion, what are core (foundation) areas of machine learning? (You may select as many as you see fit)

Frequency table
Choices	Absolute frequency	Relative frequency	Adjusted relative frequency
Bayesian statistics	34	12.14%	72.34%
Control and planning	2	0.71%	4.26%
Deep learning	2	0.71%	4.26%
Dimensionality reduction	11	3.93%	23.4%
Graphical models	22	7.86%	46.81%
Information theory	15	5.36%	31.91%
Kernel methods	16	5.71%	34.04%
Learning theory	25	8.93%	53.19%
Manifold learning	2	0.71%	4.26%
Model selection	16	5.71%	34.04%
Neural networks	6	2.14%	12.77%
Nonparametric methods	6	2.14%	12.77%
Online learning	13	4.64%	27.66%
Optimization	22	7.86%	46.81%
Reinforcement learning	7	2.5%	14.89%
Relational learning	4	1.43%	8.51%
Semisupervised learning	9	3.21%	19.15%
Sparse learning	4	1.43%	8.51%
Statistical physics of learning	3	1.07%	6.38%
Structured learning	6	2.14%	12.77%
Supervised learning	24	8.57%	51.06%
Time series modelling	5	1.79%	10.64%
Unsupervised learning	22	7.86%	46.81%
Other:	4	1.43%	8.51%
Sum:	280	100%	100%
Total answered: 47

Text input

active learning

Complexity

these are all subareas of machine learning. No one is more core than another.

Question 14

In your opinion, machine learning is a subfield of statistics.

Frequency table
Levels	Absolute frequency	Relative frequency	Adjusted relative frequency
1 (Disagree)	6	10.71%	13.04%
2	12	21.43%	26.09%
3	20	35.71%	43.48%
4 (Agree)	8	14.29%	17.39%
Not answered:	10	17.86%	-
Sum:	56	100%	100%
Total answered: 46

Question 15

In your opinion, machine learning is a subfield of computer science.

Frequency table
Levels	Absolute frequency	Relative frequency	Adjusted relative frequency
1 (Disagree)	3	5.36%	6.52%
2	11	19.64%	23.91%
3	19	33.93%	41.3%
4 (Agree)	13	23.21%	28.26%
Not answered:	10	17.86%	-
Sum:	56	100%	100%
Total answered: 46

Question 16

In your opinion, machine learning is a subfield of cognitive science.

Frequency table
Levels	Absolute frequency	Relative frequency	Adjusted relative frequency
1 (Disagree)	24	42.86%	52.17%
2	14	25%	30.43%
3	7	12.5%	15.22%
4 (Agree)	1	1.79%	2.17%
Not answered:	10	17.86%	-
Sum:	56	100%	100%
Total answered: 46

Question 17

In your opinion, machine learning is a subfield of neuroscience.

Frequency table
Levels	Absolute frequency	Relative frequency	Adjusted relative frequency
1 (Disagree)	24	42.86%	52.17%
2	19	33.93%	41.3%
3	2	3.57%	4.35%
4 (Agree)	1	1.79%	2.17%
Not answered:	10	17.86%	-
Sum:	56	100%	100%
Total answered: 46

Question 18

In your opinion, machine learning is a subfield of engineering.

Frequency table
Levels	Absolute frequency	Relative frequency	Adjusted relative frequency
1 (Disagree)	12	21.43%	26.09%
2	17	30.36%	36.96%
3	12	21.43%	26.09%
4 (Agree)	5	8.93%	10.87%
Not answered:	10	17.86%	-
Sum:	56	100%	100%
Total answered: 46

Question 19

In your opinion, machine learning is a subfield of artificial intelligence.

Frequency table
Levels	Absolute frequency	Relative frequency	Adjusted relative frequency
1 (Disagree)	4	7.14%	8.7%
2	8	14.29%	17.39%
3	18	32.14%	39.13%
4 (Agree)	16	28.57%	34.78%
Not answered:	10	17.86%	-
Sum:	56	100%	100%
Total answered: 46

Question 20

In your opinion, machine learning is an interdisciplinary area.

Frequency table
Levels	Absolute frequency	Relative frequency	Adjusted relative frequency
2	4	7.14%	8.7%
3	7	12.5%	15.22%
4 (Agree)	35	62.5%	76.09%
Not answered:	10	17.86%	-
Sum:	56	100%	100%
Total answered: 46

Question 21

In your opinion, machine learning is a a discipline distinct from other disciplines.

Frequency table
Levels	Absolute frequency	Relative frequency	Adjusted relative frequency
1 (Disagree)	10	17.86%	21.74%
2	20	35.71%	43.48%
3	12	21.43%	26.09%
4 (Agree)	4	7.14%	8.7%
Not answered:	10	17.86%	-
Sum:	56	100%	100%
Total answered: 46

Question 22

Any further comments regarding the relationship of machine learning to other disciplines?

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it is a discipline where researchers claim to be doing new stuff, but due to their lack of education and awareness, often end up rediscovering old ideas, again and again. so, indeed, ml is not really as new a *new* discipline as it is made to be.

I also feel that machine learning should also be related with human computer interaction because thats where the machine is going to take inputs from to improve its learning

Data mining should be mentioned.

geometry and topology are fundamental tools to provide good machine learning models

The emerging nature of the field, as new as it is, means that its relationship to other fields changes as the field matures. This is a good thing.

Question 23

In your opinion, in the university, machine learning should ideally be a group within computer science.

Frequency table
Levels	Absolute frequency	Relative frequency	Adjusted relative frequency
1 (Disagree)	3	5.36%	6.52%
2	9	16.07%	19.57%
3	20	35.71%	43.48%
4 (Agree)	14	25%	30.43%
Not answered:	10	17.86%	-
Sum:	56	100%	100%
Total answered: 46

Question 24

In your opinion, in the university, machine learning should ideally be a group within neuroscience.

Frequency table
Levels	Absolute frequency	Relative frequency	Adjusted relative frequency
1 (Disagree)	30	53.57%	65.22%
2	13	23.21%	28.26%
3	3	5.36%	6.52%
Not answered:	10	17.86%	-
Sum:	56	100%	100%
Total answered: 46

Question 25

In your opinion, in the university, machine learning should ideally be a group within engineering.

Frequency table
Levels	Absolute frequency	Relative frequency	Adjusted relative frequency
1 (Disagree)	15	26.79%	32.61%
2	15	26.79%	32.61%
3	14	25%	30.43%
4 (Agree)	2	3.57%	4.35%
Not answered:	10	17.86%	-
Sum:	56	100%	100%
Total answered: 46

Question 26

In your opinion, in the university, machine learning should ideally be a group within statistics.

Frequency table
Levels	Absolute frequency	Relative frequency	Adjusted relative frequency
1 (Disagree)	7	12.5%	15.22%
2	19	33.93%	41.3%
3	16	28.57%	34.78%
4 (Agree)	4	7.14%	8.7%
Not answered:	10	17.86%	-
Sum:	56	100%	100%
Total answered: 46

Question 27

In your opinion, in the university, machine learning should ideally be a group within psychology.

Frequency table
Levels	Absolute frequency	Relative frequency	Adjusted relative frequency
1 (Disagree)	38	67.86%	82.61%
2	8	14.29%	17.39%
Not answered:	10	17.86%	-
Sum:	56	100%	100%
Total answered: 46

Question 28

In your opinion, in the university, machine learning should ideally be a spread across multiple departments.

Frequency table
Levels	Absolute frequency	Relative frequency	Adjusted relative frequency
1 (Disagree)	8	14.29%	17.39%
2	11	19.64%	23.91%
3	13	23.21%	28.26%
4 (Agree)	14	25%	30.43%
Not answered:	10	17.86%	-
Sum:	56	100%	100%
Total answered: 46

Question 29

In your opinion, in the university, machine learning should ideally be an interdisciplinary centre.

Frequency table
Levels	Absolute frequency	Relative frequency	Adjusted relative frequency
1 (Disagree)	2	3.57%	4.35%
2	9	16.07%	19.57%
3	9	16.07%	19.57%
4 (Agree)	26	46.43%	56.52%
Not answered:	10	17.86%	-
Sum:	56	100%	100%
Total answered: 46

Question 30

In your opinion, in the university, machine learning should ideally be its own department.

Frequency table
Levels	Absolute frequency	Relative frequency	Adjusted relative frequency
1 (Disagree)	15	26.79%	32.61%
2	7	12.5%	15.22%
3	14	25%	30.43%
4 (Agree)	10	17.86%	21.74%
Not answered:	10	17.86%	-
Sum:	56	100%	100%
Total answered: 46

Question 31

In your opinion, in the university, machine learning should be taught at the graduate level.

Frequency table
Levels	Absolute frequency	Relative frequency	Adjusted relative frequency
1 (Disagree)	1	1.79%	2.17%
2	5	8.93%	10.87%
3	12	21.43%	26.09%
4 (Agree)	28	50%	60.87%
Not answered:	10	17.86%	-
Sum:	56	100%	100%
Total answered: 46

Question 32

In your opinion, in the university, machine learning should be taught as a specialist track in a related undergraduate programme.

Frequency table
Levels	Absolute frequency	Relative frequency	Adjusted relative frequency
1 (Disagree)	2	3.57%	4.35%
2	8	14.29%	17.39%
3	16	28.57%	34.78%
4 (Agree)	20	35.71%	43.48%
Not answered:	10	17.86%	-
Sum:	56	100%	100%
Total answered: 46

Question 33

In your opinion, in the university, machine learning should be taught in a dedicated undergraduate programme.

Frequency table
Levels	Absolute frequency	Relative frequency	Adjusted relative frequency
1 (Disagree)	12	21.43%	26.09%
2	19	33.93%	41.3%
3	11	19.64%	23.91%
4 (Agree)	4	7.14%	8.7%
Not answered:	10	17.86%	-
Sum:	56	100%	100%
Total answered: 46

Question 34

In your opinion, in which departments should machine learning be taught?

Frequency table
Choices	Absolute frequency	Relative frequency	Adjusted relative frequency
Biology	8	3.57%	17.39%
Cognitive science	12	5.36%	26.09%
Computer science	46	20.54%	100%
Economics	8	3.57%	17.39%
Electrical engineering	15	6.7%	32.61%
Engineering sciences	16	7.14%	34.78%
Machine Learning	26	11.61%	56.52%
Mathematics	16	7.14%	34.78%
Neuroscience	11	4.91%	23.91%
Operations research	12	5.36%	26.09%
Physics	6	2.68%	13.04%
Psychology	5	2.23%	10.87%
Social science	7	3.12%	15.22%
Statistics	36	16.07%	78.26%
Sum:	224	100%	100%
Total answered: 46

Question 35

Any further comments regarding the place of machine learning within the university?

Text input

introducing machine learning too early (undergrad) may lead to more confusion rather than make the student appreciate the multidisciplinary nature of this field

There is no universally "ideal" place of ML in universities. It really depends on the university.

(I am not a university person, I don't hold strong opinions, except that the strong disciplinary boundaries as they have emerged in academia are a problem for many fields, not only machine learning.

Question 36

What brought you into machine learning? (You may select more than one)

Frequency table
Choices	Absolute frequency	Relative frequency	Adjusted relative frequency
I want to use machine learning techniques to analyse data.	31	29.25%	68.89%
I want to understand how the brain works.	10	9.43%	22.22%
I want to understand the fundamental principles of learning and intelligence.	25	23.58%	55.56%
I want to understand existing machine learning techniques and develop new ones.	23	21.7%	51.11%
I want to build intelligent computers or robots.	17	16.04%	37.78%
Sum:	106	100%	100%
Total answered: 45

Text input

ill fortune

1,2,4,5 ==> 3

Question 37

In your opinion, what are the goals of machine learning? (You may select more than one)

Frequency table
Choices	Absolute frequency	Relative frequency	Adjusted relative frequency
To understand the fundamental principles of learning and intelligence.	25	17.73%	55.56%
To analyze and extract useful information from data.	38	26.95%	84.44%
To understand how the brain works.	9	6.38%	20%
To build smarter computers or robots.	27	19.15%	60%
To develop algorithms for making accurate predictions based on data.	42	29.79%	93.33%
Sum:	141	100%	100%
Total answered: 45

Text input

currently however, the goals seem to be less dramatic; also a fundamental goal of ML is to actually help humans make better decisions---an aspect that is often underplayed.

in my opinion, it's realy philosophic

Machine learning will, in part supercede statistics as it matures.

Question 38

Do you have further comments regarding any part of this survey?

Text input

good survey.

Great work.
Do make the raw results available!