Optimization in Life

I’ve been doing a lot of optimization related work and courses, for my PhD, most notably in convex optimization and non-linear programming. They say that the best way to learn theory is to implement it in real life, and so I thought that it wouldn’t hurt to find ways to optimize… life… eh? On that optimistic enough thought, here we go:

  1. The steepest descent is not necessarily the fastest. A common thing that people do when they are in an unwanted situation is to do starkly opposite of what they were initially doing, i.e. -\nabla f(x). This seems to be a go-to solution for minimizing conflict. However, it is well known that to reach the point of minimum (conflict), steepest descent can take far more number of iterations than other gradient based methods. So take it easier, guys. Extremeness is not a smart option.
  2. When bogged down by multiple issues, solve one-problem at-a-time. Coordinate descent is an approach in which the objective (life’s problems) is minimized w.r.t a fixed coordinate at a time. It’s known for its simplicity of implementation.
  3. The apple does not fall far from the tree. So when Newton came up with his method for optimizing functions, the initial estimates did not fall far from the optimum, most notably in the case of quadratic functions. Turns out, it helps to approximate functions at each point with quadratic estimates, and then to minimize that quadratic estimate. Basically, take a problem and convert it into an easier sub-problem that has a known minimum. Move on to the next sub-problem. This fetches you the global optimum much faster.
  4. While positive definiteness is ideal, positive semi-definiteness is good too. If the Hessian of the function to be minimized is positive semi-definite, then the function is convex and can be minimized easily (its local optimum is the global optimum). So keep calm (and kinda positive) and minimize issues.
  5. Often when there are too many parameters to handle, we tend to overfit a fairly complicated model to our life. In such cases, it is a good idea to penalize over-complication by adding a regularization term. Regularization also helps in solving an ill-posed problem. If we tend to focus on only a specific set of problems, we forget other facets of life, which leads us into making poorer choices. The key is to find the right balance or trade-off.
  6. Some problems actually have closed-form or unique solutions. There’s just one possible answer which is apparent enough. In that scenario the optimal strategy should be to stop optimizing. Stop contemplating, just go-get-it!
  7. On a closing note, heuristically speaking, one would need to try out a bunch of optimizing techniques to find the optimal optimization technique.


To make this post even more meta, how optimal would it be if the moral of this post converged to this statement?


Why Murphy was probably right

So, there’s this law by Murphy that most of you must be aware of.

If anything can go wrong, it will.

Now, the origin of Murphy’s law is quite well explained here.

And so goes the original Murphy’s law:

If there are two or more ways to do something, and one of those ways can result in a catastrophe, then someone will do it.

Now the situation that gave rise to this quote is something like this.

Edward A. Murphy, Jr. was one of the engineers on the rocket-sled experiments that were done by the U.S. Air Force in 1949 to test human acceleration tolerances (USAF project MX981). One experiment involved a set of 16 accelerometers mounted to different parts of the subject’s body. There were two ways each sensor could be glued to its mount, and somebody methodically installed all 16 the wrong way around. Murphy then made the original form of his pronouncement, which the test subject (Major John Paul Stapp) quoted at a news conference a few days later. (Source)

I’d think the odds of failure were quite high. How?

The person in charge of installing the accelerometers can be called Mike. Why? It’s a standard enough name. Now, Mike probably wasn’t a smart enough guy.

  1. He did not know which side of the sensor went where and randomly installed all accelerometers, using no common sense, failing to set the right combinations = 0.5 \times (1 - 0.5^{16}) [FAIL]
  2. He did not know which side went where and randomly installed all accelerometers, using no common sense  but luckily fixing the right combinations = 0.5 \times (0.5^{16}) [SUCCESS]
  3. He had the sides interchanged and installed all in the same way. Well, at least he had some common sense to install all in the same way = 0.5 \times 0.5 [FAIL]
  4. Mike was smart. He got the sides right and had the sense to install all in the right way = 0.5 \times 0.5 [SUCCESS]

Let’s give Mike the benefit of doubt. Maybe he was smart. Let’s assign that a probability of 0.5. Probability Mike was dumb is 0.5.

The probability of failure is then approximately 0.75. If you think of any ideal situation too, the probability of the chain of events leading to a success, when multiplied, is quite low.

Let’s look at it this way. The event: Me getting a sound night’s sleep. Shouldn’t be hard right?

Why it doesn’t work: I have a roommate who keeps talking loudly on the phone till wee hours. Why would I have a roommate? I am a research assistant, we don’t get paid well enough for me to be able to afford a better room. Why am I a research assistant? I want to do a PhD. Why do I want to do a PhD? You get the drift.

Turns out, I was almost destined to have a painful right ear, being subjected to continuous loud mindless rants in the middle of the night. The consequences of a lot of our actions aren’t really predictable until events transpire in due course of time. But when they do happen, it’s not that hard to chart out the trajectory of what might have caused them. And so, if anything wrong can happen, perhaps your brain is able to trace that trajectory in advance to forecast what will go wrong.

Here’s the catch though. When things are expected to go wrong and they don’t, we are so happy with the outcome, we barely recognize it as a failure of the law. So Murphy was a genius, in framing a law whose exceptions would go easily unnoticed. Whoever thought that something so iconic would come out of so much pessimism?

Then again, as Phil Dunphy from Modern Family would say…


The Physics of Interpersonal Relationships

1. Frictional force is directly proportional to normal reaction force between two people. If the two entities are close to each other, and at opposition, the more reaction supplied by either parties, the more friction. Also, work done by frictional force is non conservative in nature. One can only expend more and more time and energy into bickering with the other party, without expecting equivalent valuable output. Much is lost as heat.

2. Gravitational force is inversely proportional to the square of the physical distance between two people. If you find yourself gravitating towards someone, when you shouldn’t be, maintain a physical separation of at least 15 ft. That minimizes chance of physical contact and any form of non-awkward conversation.

3. If you find yourself fast accelerating into an unwanted situation with someone, the only way to change course of the events is to apply a jerk. Change in acceleration can be characterized by either one entity or favorably both being jerks.

4. The first law of thermodynamics states that energy of an isolated system is constant. One may decide to channel their energies into productive work and recreational hobbies, or indulge in interpersonal warfare, but not both. I’d pick the first.

5. Neural pathways get trained based on the associations between input stimulus to the output reaction. The weights on these pathways can be adjusted by experimentally varying the reactions to specific stimuli. If you dislike someone, for eg. a woman in your workplace that completely cold shoulders you even when you are sweet to her and offer sage advice on where to get the best kind of food in the locality, and giving her a heads up in the time of need, your most natural reaction is to detest that woman. You feel insulted. Now replace this feeling with that of pity for the poor woman who can’t see right from wrong.

Some associations might be tagged as positive compulsions. For example, when you feel disappointed by the lack of people to talk to, start writing a blog post instead. Wink wink.

6. Newton’s law of cooling suggests that rate of cooling is proportional to difference in temperature of the body and its surroundings. If you find yourself constantly agitated by your surroundings, walk out of the room. Staying in the room will only maintain or increase your agitation.

7. If two people have a charged discussion and are speeding through an argument, then in the presence of a magnetic field, they’re likely to experience a perpendicular force, called the Lorentz force, most likely in the form of a slap or punch, not by Lorentz himself.

8. If two interacting people have the same wavelength, a slight change in wavelength causes the formation of beats. A pattern of constructive and destructive interferences follows. In that case, just listen to the beat of your own music, some sound logic will follow.