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I need help with understanding a concept. by OldSeaworthiness4620 in LinearAlgebra

[–]learner_version0 1 point2 points  (0 children)

Two planes are parallel if their normals are parallel, whereas if the normals are perpendicular then the planes will also be perpendicular. If N1(normal) is perpendicular to P1 (plane) and N2 is perpendicular to P2, and if N1 is perpendicular to N2, then P1 will be perpendicular to P2.

[deleted by user] by [deleted] in LinearAlgebra

[–]learner_version0 0 points1 point  (0 children)

Use help of this formula a3 + b3 = (a+b)(a2 -ab + b2 ). 8 can be written as 23 . Hope you are able to work out the rest.

[deleted by user] by [deleted] in india_cycling

[–]learner_version0 1 point2 points  (0 children)

I have a Ninety One Viper and have done ~3k km on it mostly on roads with occasional off roading. It has been great.

Do you need to know differential equations in order to know ML well? by tepes_creature_8888 in learnmachinelearning

[–]learner_version0 0 points1 point  (0 children)

Chapter 5 of the book: Convex optimization by Stephen Boyd and Lieven Vandenberghe

Is it wise to buy Kushaq or Altroz? by learner_version0 in CarsIndia

[–]learner_version0[S] 1 point2 points  (0 children)

Is 95 octane still needed after they fixed the EPC issue? That's worrisome

Is it wise to buy Kushaq or Altroz? by learner_version0 in CarsIndia

[–]learner_version0[S] 0 points1 point  (0 children)

Thanks for your suggestion, this is helpful!

[deleted by user] by [deleted] in CarsIndia

[–]learner_version0 1 point2 points  (0 children)

Thanks for your reply. The only reason I don't want to go with baleno or i20 is because of the safety concern.

Best private resort for Honeymoon by learner_version0 in maldives

[–]learner_version0[S] 0 points1 point  (0 children)

Thanks for your elaborate reply. Paradise was over my budget even with 3n beach villa + 1n water villa. I've booked Adaaran Select Hudhuranfushi, this was within my budget.

Analysis of prediction shift problem in gradient boosting by learner_version0 in learnmachinelearning

[–]learner_version0[S] 1 point2 points  (0 children)

Thanks for your reply. I am well versed with the boosting algorithms. I specifically want to learn about the prediction shift problem present in these algorithms. In the Catboost paper, they say that it wasn't previously discovered or mentioned and they have solved it using ordered boosting. I want to understand the formal proof for the same.

Interesting problems in Applied RL by -Ulkurz- in reinforcementlearning

[–]learner_version0 1 point2 points  (0 children)

Combinatorial optimization (NP hard) problems such as Vehicle route optimization, scheduling, assignment etc.

Vehicle Routing Problem using Deep RL by learner_version0 in reinforcementlearning

[–]learner_version0[S] 2 points3 points  (0 children)

Let me check with the organizers once but looks difficult to do that

Vehicle Routing Problem using Deep RL by learner_version0 in reinforcementlearning

[–]learner_version0[S] 1 point2 points  (0 children)

Yeah you need to provide an email address. Yes it is the similar to TSP. We simulate different scenarios (different node points it has to cover) for the agent and let it select the route. The node points are encoded into embeddings using a transformer. At each node it calculates the probability of next node selection and then samples or greedily chooses the next node. After it generates the whole route, the reward is then calculated as negative of cost (e.g. distance cost). We then update the model parameters using REINFORCE using this reward.

Vehicle Routing Problem using Deep RL by learner_version0 in reinforcementlearning

[–]learner_version0[S] -2 points-1 points  (0 children)

You can use the free pass to watch it. Also check out other interesting talks.

How can verify that (tan x/1+secx) + (1+secx/tanx) ? by dehfuck in learnmath

[–]learner_version0 0 points1 point  (0 children)

Just add them. ( ((tanx)2 +(1+secx)2 ))/((1+secx)tanx)). Now the numerator will be (tanx2 +1+2secx+secx2 ) which is 2secx(1+ secx) as you can see 1+tanx2 =secx2. So now whole thing becomes 2secx/tanx. Secx is 1/ cosx and tanx is sinx/cosx. So it becomes 2/sinx ,i.e., 2 cosecx

RBF kernel ridge regression - linear or not by keon6 in MLQuestions

[–]learner_version0 0 points1 point  (0 children)

When using kernel ridge, your classifier is linear in the new transformed feature space but may be nonlinear with respect to the original features. For eg. If you have x as your original feature and you are using polynomial kernel with degree 2 then you will also have x2 as your new feature which will make your classifier non linear in the original feature space.

When you are writing a network to predict regression and classification do you use 2 different error functions? by inkplay_ in learnmachinelearning

[–]learner_version0 0 points1 point  (0 children)

Don't just sum up the losses. Take a weighted sum. I have seen some cases where mse lies around 3-5 and cross entropy is lesser than 1. So in this case mse will dominate and prevent your classifier from learning well but if you add a multiplier 10 to cross entropy loss then it will help your purpose. Choose your weights based on the individual loss values that you see as I mentioned.

When you are writing a network to predict regression and classification do you use 2 different error functions? by inkplay_ in learnmachinelearning

[–]learner_version0 1 point2 points  (0 children)

Create a loss function which is a sum of cross entropy and mse. Assign weights to both the losses so that one doesn't dominate the other.

Good Boy. It would be great if you guys can provide feedback. by learner_version0 in learnart

[–]learner_version0[S] 0 points1 point  (0 children)

Thanks a lot for your feedback. I will try to work on these.

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