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Podcast #474: The Surprises of Romantic Attraction

According to the popular, evolutionary theory of human attraction, people select romantic partners based on objective assessments of what’s called their “mate value” — the extent to which an individual possesses traits like good looks and status. But is that really all that’s behind the way people pair up?

My guest today has done a series of studies which add greater nuance to the mysteries of romantic attraction. His name is Paul Eastwick and he’s a professor of psychology at USC Davis. We begin our conversation unpacking the fact that there’s sometimes a gap between the sexual and romantic partners people say they prefer in the abstract, and the partners they actually choose in real life. We then turn to whether or not the popular idea that men value physical attractiveness more than women, and that women value status and resources more than men, is really true. We also talk about how people’s consensus over who is and isn’t attractive changes over time, and whether it’s true that people of equal attractiveness generally end up together. We end our conversation discussing how these research-based insights can be applied to the real world of dating, and why less attractive people may have better luck meeting people offline than on.

Some interesting insights in this show that lend credence to the old adage that there’s someone for everyone.

Show Highlights

• What’s the accepted theory of how men and women are attracted to each other?
• How “mate value” is calculated 
• Is it true that men value physical appearance more than women?
• The self-insight gap that plagues daters 
• Why trait-based compatibility doesn’t give the full picture of a relationship’s potential
• The importance of “fit” when it comes to compatibility
• How physical attractiveness changes over time as we get to know people
• Do equally attractive people always end up with each other?
• What does modern science say about pick-up artist techniques?
• Tips for how to think about modern dating apps 

Resources/People/Articles Mentioned in Podcast

• The Best Relationship Episodes of the AoM Podcast
• Mate value
• Is Love Overrated?
• The Problem With Ambiguity in Relationships
• What’s Causing the Sex Recession?
• How Do You Know When She’s the One?
• Assortative mating
• How to Know If a Woman Likes You
• How to REALLY Be Alpha Like the Wolf
• Paul’s website

Source: https://www.quora.com/What-are-the-most-important-algorithms-needed-to-solve-graph-problems

Graphs is an interesting topic as such. Even more, the concepts and algorithms used to tackle graph problems are elegant. Compiling a list of graph theory concepts would  be a lot tedious but if your focus is on sport programming then I might make sense.

My pick would be:

0. The basics – graph notations, graph representations

1. graph traversal (BFS / DFS ) – perhaps the most versatile topic in graph theory. Just look at the applications of these methods, both have their own unique properties.

2. Shortest Path (Dijkstra / Bellman Ford / Floyd-Warshall)

3. Minimum spanning trees (Prim’s / Kruskal’s)

4. Euler tour trees

5. Lowest Common Ancestor (LCA algo : I, II, III, IV)

6. Min cut / Max Flow / Matching : topcoder

7. Strongly connected components : SCC

8. Articulation points and edges : Explanation of Algorithm for finding articulation points or cut vertices of a graph

Also there are some optimization techniques like Heavy light decomposition

These are the basics of graph to get on with graph questions.

Source: https://stackoverflow.com/questions/6164629/dynamic-programming-and-memoization-bottom-up-vs-top-down-approaches

rev4: A very eloquent comment by user Sammaron has noted that, perhaps, this answer previously confused top-down and bottom-up. While originally this answer (rev3) and other answers said that “bottom-up is memoization” (“assume the subproblems”), it may be the inverse (that is, “top-down” may be “assume the subproblems” and “bottom-up” may be “compose the subproblems”). Previously, I have read on memoization being a different kind of dynamic programming as opposed to a subtype of dynamic programming. I was quoting that viewpoint despite not subscribing to it. I have rewritten this answer to be agnostic of the terminology until proper references can be found in the literature. I have also converted this answer to a community wiki. Please prefer academic sources. List of references: {Web: 1,2} {Literature: 5}

Continue reading “Dynamic programming and memorization: bottom-up vs top-down approaches”

Obama on Trump (without mentioning his name):

“People just make stuff up. They just make stuff up. We see it in the growth of state-sponsored propaganda. We see it in internet fabrications. We see it in the blurring of lines between news and entertainment,” Obama said. “We see the utter loss of shame among political leaders where they’re caught in a lie and they just double down and they lie some more. It used to be that if you caught them lying, they’d be like, ‘Oh, man’— now they just keep on lying.”

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