Interesting, wonder why there is a dip at 45 years of experience? Computer Science |
- Interesting, wonder why there is a dip at 45 years of experience?
- How to create vertex-cover solved graphs
- Hot Chips | A California Startup Has Built an AI Chip as Big as a Notebook. Why?
- Logarithmic Space Verifiers on NP-complete
- Creator of Ultimate Go study guide is making one for coding interview challenges
- Reflinks vs symlinks vs hard links: How they can help machine learning projects
- WebAssembly allows to bring native desktop software to the web
- Seoul National University AI Uses Text Tags to Colourize Line Drawings
- Infinite Staircase Problem
- It's been my life long goal to build a self balancing robot, and I need you guys' help coming up with the next step(neural networking) thank you
- Are there good books on programming languages using Haskell, besides Scheme?
- Python framework for Git
- PID Loops and the Art of Keeping Systems Stable
- I created a decision problem that's meant to be NP-complete, but requires solving its unary variant. So, how do I reduce binary-knapsack <p my problem?
Interesting, wonder why there is a dip at 45 years of experience? Posted: 20 Aug 2019 03:23 PM PDT |
How to create vertex-cover solved graphs Posted: 21 Aug 2019 04:07 AM PDT I need to create a large dataset of random graphs which the vertex-cover problem is solved for them. I can't simply create random graph and solve the problem for them (best approximation solvers in python I could find use 2-approximation), but maybe there is some kind of "cheat" way to build the graphs so they will represent a good "solved" dataset. - for example creating a set of vertices which are decided from the beginning to become the vertex cover, and adding vertices and edges in a way that won't change that (pretty simple - cluster of star-graphs) Putting it more clearly, I want to efficiently create a set of "solved" graphs, such that for every graph G(V,E) in the set I know the min vertex cover. Sorry if was incoherent, English not my first language. [link] [comments] |
Hot Chips | A California Startup Has Built an AI Chip as Big as a Notebook. Why? Posted: 20 Aug 2019 10:14 AM PDT |
Logarithmic Space Verifiers on NP-complete Posted: 20 Aug 2019 06:06 PM PDT |
Creator of Ultimate Go study guide is making one for coding interview challenges Posted: 20 Aug 2019 11:09 AM PDT |
Reflinks vs symlinks vs hard links: How they can help machine learning projects Posted: 20 Aug 2019 11:02 AM PDT |
WebAssembly allows to bring native desktop software to the web Posted: 20 Aug 2019 07:00 AM PDT |
Seoul National University AI Uses Text Tags to Colourize Line Drawings Posted: 20 Aug 2019 12:11 PM PDT |
Posted: 20 Aug 2019 10:24 AM PDT I am recently on the topic "Design and analysis of Algorithms" offered by my college. So I was reading about solvability and came across the 'Infinite staircase problem'. Well, I was wondering is it physically possible to create infinite staircase which can left humans confused? And if it is possible and human brain can't solve this problem including similar set of problems which is unsolvable by computers, can we conclude this that human brain is nothing but an advanced biological computer with higher processing power than electronic computers? [link] [comments] |
Posted: 20 Aug 2019 08:46 AM PDT I'm a high school graduate, and I've been working on this on and off for the past 3 years, a self balanced robot is a robot that keeps itself vertical on two wheels by running the motors in the direction it's falling to catch itself. The difficult thing here is that you need to know the angle of the robot, and you get that from an accelerometer(noisy) and a gyroscope(drifts). So this the best way of combing these is to use the kelman filter, which does things like if it's at an angle it will start falling, so it anticipates the speed of rotation to increase using physics and matrices. I hate setting this up so I thought I could use a neural network to do this(there are people doing this I just dont understand their terminology), also the robot could figure other things out like how motor output affects it. Also the motor output is usually controlled by PID loop which works great but this is often instead with a neural network. So if I'm using two neural networks where ones the input of the other I could just multiply the matrices, and combine them. Do you think this could work, how do you suggest I do it? And what do you think I should do to get better at using neural networks? [link] [comments] |
Are there good books on programming languages using Haskell, besides Scheme? Posted: 20 Aug 2019 04:56 AM PDT I found the following programming language books use Scheme
and this uses OCaml
Are there good PL books using Haskell? Does Scheme have advantage over Haskell for being used in PL books? Same question about OCaml or SML. Does Haskell have similar features as Scheme and OCaml/SML to make it also suitable for the same purpose? Thanks. [link] [comments] |
Posted: 20 Aug 2019 06:39 AM PDT |
PID Loops and the Art of Keeping Systems Stable Posted: 20 Aug 2019 06:05 AM PDT |
Posted: 19 Aug 2019 08:08 PM PDT Decision- While unary subset-sum excludes value 0, do both sets share an equal subset-sum? (for the input value(s) X)? Examples
Facts: Unary Subset-Sum is in P Binary-Subset-Sum is in NP P⊆NP Since P⊆NP then Unary-SSum is a subset of NP Proof by contradiction Decision Problem: Given two different sets of numbers. The first is represented in integers, and the second is represented in unary. While unary subset-sum excludes value 0, do both sets share an equal subset-sum? (for the input value(s) X) Restriction: You are always solving the NP-complete problem Subset-Sum. Unary-Subset-sum instances always exclude values 0.
Subset-Sum is NP-complete. Which is NP-hard and in NP. So my problem is NP-hard because of the subset-sum restriction and is shown to be in NP. Therefore, my problem is NP-complete. This is likely to be wrong. Question How would I reduce another binary NP-complete problem < My problem? I need to reduce a NP-complete problem that only is represented in binary to my problem while all unary instances exclude the value 0. >;-) [link] [comments] |
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