hunch_net hunch_net-2008 hunch_net-2008-290 knowledge-graph by maker-knowledge-mining
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Introduction: Graduating students in Statistics appear to be at a substantial handicap compared to graduating students in Machine Learning, despite being in substantially overlapping subjects. The problem seems to be cultural. Statistics comes from a mathematics background which emphasizes large publications slowly published under review at journals. Machine Learning comes from a Computer Science background which emphasizes quick publishing at reviewed conferences. This has a number of implications: Graduating statistics PhDs often have 0-2 publications while graduating machine learning PhDs might have 5-15. Graduating ML students have had a chance for others to build on their work. Stats students have had no such chance. Graduating ML students have attended a number of conferences and presented their work, giving them a chance to meet people. Stats students have had fewer chances of this sort. In short, Stats students have had relatively few chances to distinguish themselves and
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1 Graduating students in Statistics appear to be at a substantial handicap compared to graduating students in Machine Learning, despite being in substantially overlapping subjects. [sent-1, score-1.469]
2 Statistics comes from a mathematics background which emphasizes large publications slowly published under review at journals. [sent-3, score-0.642]
3 Machine Learning comes from a Computer Science background which emphasizes quick publishing at reviewed conferences. [sent-4, score-0.494]
4 This has a number of implications: Graduating statistics PhDs often have 0-2 publications while graduating machine learning PhDs might have 5-15. [sent-5, score-0.821]
5 Graduating ML students have had a chance for others to build on their work. [sent-6, score-0.509]
6 Graduating ML students have attended a number of conferences and presented their work, giving them a chance to meet people. [sent-8, score-0.629]
7 Stats students have had fewer chances of this sort. [sent-9, score-0.606]
8 In short, Stats students have had relatively few chances to distinguish themselves and are heavily reliant on their advisors for jobs afterwards. [sent-10, score-0.883]
9 This is a poor situation, because advisors have a strong incentive to place students well, implying that recommendation letters must always be considered with a grain of salt. [sent-11, score-0.918]
10 This problem is more or less prevalent depending on which Stats department students go to. [sent-12, score-0.566]
11 In some places the difference is substantial, and in other places not. [sent-13, score-0.2]
12 One practical implication of this, is that when considering graduating stats PhDs for hire, some amount of affirmative action is in order. [sent-14, score-1.115]
13 At a minimum, this implies spending extra time getting to know the candidate and what the candidate can do is in order. [sent-15, score-0.382]
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