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Comment Re:Scientific result based on closed data (Score 1) 149

Keep in mind that their result is on a controlled dataset ("labeled faces in the wild," for which a lot of training data is available and on which previously proposed systems already perform well.

So this 97% number is a bit of an adventurous extrapolation. Think of it as only polling in NYC and stating that you can predict the result of the next presidential election. The paper was clear on that point, only the summary made it look catchy as usual.

Comment Scientific result based on closed data (Score 1) 149

I read the paper and while the approach of learning a representation for faces, and then classifying in that new space whether the face is the same as model is sound, the representation is trained on a closed dataset (the 4m faces from facebook).

So it means that there is no way for the scientific community to check whether the results are correct or not. The results in the paper lack a comparison to a reproducible result, like using the youtube or faces in the wild datasets to train the representation, and then report results given that representation. This way researchers could validate the approach.

I would never have accepted such paper if I were to review it.

Comment Not new (Score 1) 100

Nothing is performed on the fly. It's just another feature extraction and selection pipeline.
1) Deep Neural Networks also save the feature engineering step (for instance
2) If as suggested by the title you are interested by on-the-fly object recognition, look at Tracking-Learning-Detection (TLD) (

Comment Sampling (Score 1) 226

If your results depend on hardware, software and so on, what you are doing is sampling from the solution space. You can then model that distribution and perform significance testing vs that distribution. What is the probability of your result being correct? your result belonging to the true distribution?

Statistics over mathematical proofs. That's what you want to do.

Comment buggy struct (Score 5, Informative) 88

Here is the current structure proposed by the organizers for storing the social network.

struct user_struct {
        int user_ID;
        char * name;
        char * account_handle;
        int number_of_BFFs;
        user * BFF_list;
        int scratch;

The BFF_list field is supposed to contain the list of friends of a user. The proposed type, user*, suggests that it should be implemented as an array of user. This means that if a user is in your list of friends (stored by value in the array BFF_list), you cannot be in his list of friends unless you both have the same friends. It can only represent non-symetric friendship where each user is involved once in a BFF_list.

I would suggest using type user** for this field.

Comment You should stick to it (Score 1) 347

What you learn at university is not about technology, it's rather
- to be curious and to explore avenues that you don't know: this will help you draw those lines between opposing domains that no body had seen before
- to multitask, meet deadlines, and work under pressure (why would you need that?)
- to communicate with people who don't know what you are talking about (customers, boss?)
- to teach yourself new stuff.

Comment What a PhD really is (Score 1) 260

A PhD is about science, not money. With a little bit of luck, you'll be in for a startup project, but otherwise, there is no big money making in science.

On the other hand, it's going to be very interesting. When you write your thesis, you will learn something about yourself: how you can cope with frustration, and how you can do stuff that you though you would never be able to do.

But it's all like professional sports, only a few make it to the top.

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