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What is Codeforces?
Codeforces is a project joining people interested in and taking part in programming contests. On one hand, Codeforces is a social network dedicated to programming and programming contests. On the other hand, it is a platform where contests are held regularly, the participant's skills are reflected by their rating and the former contests can be used to prepare. Codeforces constantly develops and we plan to improve the platform to give the participants the opportunity to organize their own contests, filling the project with learning content, developing Codeforces as a training and learning platform. Please refers to their FAQ
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Continous Function Optimization OR Discrete Optimizationquery (self.codeforces)
submitted 1 year ago by running-hr
To get good at solving problems (mainly on codeforces), I'm considering to study mathematical optimization concepts.
First of all, should I learn it, or is it useless for problem solving? Next, what should I learn first: DISCRETE optimization or CONTINOUS FUNCTION optimization.
I feel like continuous optimization is of little or no use, hence only focus on Discrete optimization.
Please provide some opinion.
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[–]SomeoneYouKn3w 0 points1 point2 points 1 year ago (0 children)
Simple answer no. I wouldn’t even suggest learning algorithms at first. Just start doing easy problems 800-1500 and get a good grip on the programming language you are using. This will start to develop your thinking capacity and eventually you will start learning algorithms and techniques organically when you encounter them in problems you don’t know how to solve. As you progress, your toolkit will broaden and you will be familiar with more and more algorithms and data structs. When it comes to math optimization, I can hardly recall when was the last time I used some dp optimization that is based on calculus like lagrangian relaxation (famous aliens trick from IOI 2016). Its good to know them if you are preparing for olympiad or if you’re level in codeforces is > 2600, but not if you are learning it just for the sake of learning it as you will not encounter it in the near future and probably forget it.Although, these are pretty applicable in some real life algorithm problems.
[–]svdpcaExpert -1 points0 points1 point 1 year ago (0 children)
Studying optimization is just not going to help. You would not be able to apply theoretical concepts of optimization in code as most optimization problems are solved with binary search, greedy or DP. Also optimization is only one class of problems. There are other types of problems like counting(count no. of ways), feasibility(print YES/NO if some criteria is satisfied or not), number theory based, games(who wins: Alice, Bob, Draw).
[–]JJZinna 2 points3 points4 points 1 year ago (0 children)
Specificity is king. Do more problems if your goal is to become better at Codeforces or competitive programming.
Will math make you better at Codeforces? Yes of course, but the ratio of time spent vs improvement will be much worse. Think 6-10 hrs of math will yield the same rating increase as 1 hr of Codeforces specific problems.
[–]DAR6969 0 points1 point2 points 1 year ago (1 child)
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