date stringlengths 10 10 | nb_tokens int64 60 629k | text_size int64 234 1.02M | content stringlengths 234 1.02M |
|---|---|---|---|
2019/06/03 | 227 | 869 | <issue_start>username_0: As stated in the universal approximation theorem, a neural network can approximate almost any function.
Is there a way to calculate the closed-form (or analytical) expression of the function that a neural network computes/approximates?
Or, alternatively, figure out if the function is linear o... |
2019/06/04 | 2,063 | 5,813 | <issue_start>username_0: I was reading the following book: <http://neuralnetworksanddeeplearning.com/chap2.html>
and towards the end of equation 29, there is a paragraph that explains this:
[](https://i.stack.imgur.com/KkBdn.png)
However I am unsur... |
2019/06/04 | 2,168 | 6,318 | <issue_start>username_0: I need to manually classify thousands of pictures into discrete categories, say, where each picture is to be tagged either A, B, or C.
**Edit:** I want to do this work myself, not outsource / crowdsource / whatever online collaborative distributed shenanigans. Also, I'm currently not intereste... |
2019/06/05 | 2,011 | 5,769 | <issue_start>username_0: There was a recent informal question on chat about RTS games suitable for AI benchmarks, and I thought it would be useful to ask a question about them in relation to AI research.
Compact is defined as the fewest mechanics, elements, and smallest gameboard that produces a balanced, intractable,... |
2019/06/06 | 576 | 2,080 | <issue_start>username_0: As far I know, the RNN accepts a sequence as input and can produce as a sequence as output.
Are there neural networks that accept graphs or trees as inputs, so that to represent the relationships between the nodes of the graph or tree?<issue_comment>username_1: There are types of neural networ... |
2019/06/07 | 424 | 1,803 | <issue_start>username_0: The question is little bit broad, but I could not find any concrete explanation anywhere, hence decided to ask the experts here.
I have trained a classifier model for binary classification task. Now I am trying to fine tune the model. With different sets of hyperparameters I am getting differe... |
2019/06/07 | 1,837 | 8,132 | <issue_start>username_0: In regression, in order to minimize an error function, a functional form of hypothesis $h$ must be decided upon, and it must be assumed (as far as I'm concerned) that $f$, the true mapping of instance space to target space, must have the same form as $h$ (if $h$ is linear, $f$ should be linear.... |
2019/06/09 | 371 | 1,640 | <issue_start>username_0: I have way more unlabeled data than labeled data. Therefore I would like to train an autoencoder using MobileNetV2 as the encoder. Then I will use the pre-trained model for the classification of the labeled data.
I think it is rather difficult to "invert" the MobileNet architecture to create a... |
2019/06/10 | 455 | 1,962 | <issue_start>username_0: I was working on CNN. I modified the training procedure on runtime.
[](https://i.stack.imgur.com/0hrgz.png)
As we can see from the validation loss and validation accuracy, the yellow curve does not fluctuate much. ... |
2019/06/10 | 452 | 2,120 | <issue_start>username_0: In general, how does one make a neural network learn the training data while also forcing it to represent some known structure (e.g., representing a family of functions)?
The neural network might find the optimal weights, but those weights might no longer make the layer represent the function ... |
2019/06/12 | 595 | 2,602 | <issue_start>username_0: Basically, economic decision making is not restricted to mundane finance, the managing of money, but any decision that involves expected utility (some result with some degree of optimality.)
* Can Machine Learning algorithms make economic decisions as well as or better than humans?
"Like hum... |
2019/06/15 | 6,318 | 19,039 | <issue_start>username_0: [Explainable artificial intelligence (XAI)](https://en.wikipedia.org/wiki/Explainable_artificial_intelligence) is concerned with the development of techniques that can enhance the interpretability, accountability, and transparency of artificial intelligence and, in particular, machine learning ... |
2019/06/16 | 459 | 1,871 | <issue_start>username_0: For the purposes of this question, let's suppose that an artificial general intelligence (AGI) is defined as a machine that can successfully perform any intellectual task that a human being can [[1]](https://en.wikipedia.org/wiki/Artificial_general_intelligence).
Would an AGI have to be Turing... |
2019/06/16 | 625 | 2,615 | <issue_start>username_0: Problem Statement
-----------------
I've built a classifier to classify a dataset consisting of n samples and four classes of data. To this end, I've used pre-trained VGG-19, pre-trained Alexnet and even LeNet (with cross-entropy loss). However, I just changed the softmax layer's architecture ... |
2019/06/18 | 430 | 1,886 | <issue_start>username_0: What are some interesting myths of Artificial Intelligence and what are the facts behind them?<issue_comment>username_1: In artificial intelligence, even though not everyone agrees, a common (and maybe the biggest) myth is that of the [intelligence explosion](https://en.wikipedia.org/wiki/Techn... |
2019/06/18 | 754 | 3,015 | <issue_start>username_0: I’m looking for some help with my neural network. I’m working on a binary classification on a recurrent neural network that predicts stock movements (up and down) Let’s say I’m studying Eur/Usd, I’m using all the data from 2000 to 2017 to train et I’m trying to predict every day of 2018.
The ... |
2019/06/19 | 841 | 3,447 | <issue_start>username_0: Everyone is afraid of losing their job to robots. Will or does artificial intelligence cause mass unemployment?<issue_comment>username_1: Up to a point. Some jobs will IMHO not easily be replaced by robots, others more easily. Some could be, but I hope common sense will prevail and stop that.
... |
2019/06/20 | 1,048 | 4,313 | <issue_start>username_0: I have the following problem. We have $4$ separate *discrete* inputs, which can take any integer value between $-63$ and $63$. The output is also supposed to be a discrete value between $-63$ and $63$. Another constraint is that the solution should allow for online learning with singular values... |
2019/06/21 | 1,608 | 6,053 | <issue_start>username_0: I recently got a 18-month postdoc position in a math department. It's a position with relative light teaching duty and a lot of freedom about what type of research that I want to do.
Previously I was mostly doing some research in probability and combinatorics. But I am thinking of doing a bit ... |
2019/06/21 | 1,379 | 6,382 | <issue_start>username_0: When describing tensors of higher order I feel like there is an overloading of the term *dimension* as it may be used to describe the order of the tensor but also the dimensionality of the... "orders"?
Assume one describes the third-order tensor produced by a convolutional layer and wants to r... |
2019/06/23 | 1,285 | 5,928 | <issue_start>username_0: I need to develop a convolutional neural network whose inputs are 1-channel images, but I dont know how to do it, given that most libraries use 3 channel images. Should I convert my images to RGB? Is there any way to implement a CNN that receive as input 1-channel images?<issue_comment>username... |
2019/06/23 | 547 | 2,314 | <issue_start>username_0: I have a bunch of images from different trucks passing the road. Here is an example.
[](https://i.stack.imgur.com/3mHXL.png)
The truck needs to be at a certain distance from the border of the lane. Some of the trucks are way ... |
2019/06/24 | 640 | 2,519 | <issue_start>username_0: Actually, I am "fresh-water", and I've never known what is neural network. Now I am trying understand how to design simple neuronetwork for this problem:
I'd like to make up such neural network that after learning it could predicate a mark of passed exam (for example, math). There is such fact... |
2019/06/27 | 384 | 1,684 | <issue_start>username_0: Both of them deal with data of graph structure like a network community. Is there a big difference there?<issue_comment>username_1: One possible approach will be to use an algorithm which detects lines (Ex. Hough lines or any deep neural net trained to detect lanes) and use some threshold range... |
2019/06/28 | 1,070 | 4,296 | <issue_start>username_0: The [Planning Domain Definition Language (PDDL)](https://en.wikipedia.org/wiki/Planning_Domain_Definition_Language) is known for its capabilities of symbolic planning in the state space. A solver will find a sequence of steps to bring the system from a start state to the goal state. A common ex... |
2019/06/29 | 846 | 3,373 | <issue_start>username_0: I have implemented an epsilon-greedy Monte Carlo reinforcement learning agent like suggested in [Sutton and Barto's RL book](http://incompleteideas.net/book/the-book-2nd.html) (page 101). As far as I understood epsilon-greedy agents so far, the evaluation has to stop at some point to exploit th... |
2019/06/30 | 839 | 3,314 | <issue_start>username_0: At a time step $t$, for a state $S\_{t}$, the return is defined as the discounted cumulative reward from that time step $t$.
If an agent is following a policy (which in itself is a probability distribution of choosing a next state $S\_{t+1}$ from $S\_{t}$), the agent wants to find the value at... |
2019/07/01 | 474 | 1,986 | <issue_start>username_0: I need to cluster my points into unknown number of clusters, given the minimal Euclidean distance R between the two clusters. Any two clusters that are closer than this minimal distance should be merged and treated as one.
I could implement a loop starting from the two clusters and going up un... |
2019/07/02 | 862 | 3,460 | <issue_start>username_0: The basic seq-2-seq model consists of 2 parts: a recurrent encoder that compresses a sequence to a vector and decoder that unrolls the vector into the output sequence:
[](https://i.stack.imgur.com/IkEwP.png)
Why is the output... |
2019/07/03 | 1,461 | 6,220 | <issue_start>username_0: Let's say I have an adjustable loaded die, and I want to train a neural network to give me the probability of each face, depending on the settings of the loaded die.
I can't mesure its performance on individual die roll, since it does not give me a probability.
I could batch a lot of roll to ... |
2019/07/06 | 432 | 1,687 | <issue_start>username_0: Most image classifiers like Inception-v3 accept images of about size 299 x 299 x 3 as input. In this particular case, I cannot resize the image and lose resolution. Is there an easy solution of dealing with this rather than retraining the model? (Particularly in tensorflow)<issue_comment>userna... |
2019/07/07 | 2,075 | 8,435 | <issue_start>username_0: I listened to a talk by a panel consisting of two influential Chinese scientists: [<NAME>](https://sites.google.com/site/gangwang6/) and [<NAME>](https://www.crunchbase.com/person/kai-yu#section-overview) and others.
When being asked about the biggest bottleneck of the development of artificia... |
2019/07/07 | 978 | 4,008 | <issue_start>username_0: Dietterich, who introduced the [taxi environment](https://arxiv.org/pdf/cs/9905014.pdf) (see p. 9), states the following: In total there “are 500 [distinct] possible states: 25 squares, 5 locations for the passenger (counting the four starting locations and the taxi), and 4 destinations” (Diett... |
2019/07/08 | 714 | 2,783 | <issue_start>username_0: Is there any precedent for using a neuroevolution algorithm, like NEAT, as a way of getting to an initialization of weights for a network that can then be fine-tuned with gradient descent and back-propagation?
I wonder if this may be a faster way of getting to a global minimum before starting... |
2019/07/08 | 2,487 | 10,281 | <issue_start>username_0: Let's consider this example:
>
> It's John's birthday, let's buy him a kite.
>
>
>
We humans most likely would say the kite is a birthday gift, if asked why it's being bought; and we refer to this reasoning as *common sense*.
Why do we need this in artificially intelligent agents? I thin... |
2019/07/10 | 1,610 | 6,541 | <issue_start>username_0: Imagine you show a neural network a picture of a lion 100 times and label it with "dangerous", so it learns that lions are dangerous.
Now imagine that previously you have shown it millions of images of lions and alternatively labeled it as "dangerous" and "not dangerous", such that the probabi... |
2019/07/11 | 2,401 | 8,253 | <issue_start>username_0: The [Wikipedia article for the universal approximation](https://en.wikipedia.org/wiki/Universal_approximation_theorem) theorem cites a version of the universal approximation theorem for Lebesgue-measurable functions from [this conference paper](https://arxiv.org/pdf/1709.02540.pdf). However, th... |
2019/07/14 | 568 | 2,417 | <issue_start>username_0: I have a continuous state space, and a continuous action space. The way I understand it, I can build a policy network which takes as input a continuous state vector and outputs both mean vector and covariance matrix of the action-distribution. To get a valid action I then sample from that distr... |
2019/07/15 | 710 | 2,450 | <issue_start>username_0: From the subjective perspective, the number of documentaries about the subject Artificial Intelligence and robotics is small. It seems, that the topic is hard to visualize for the audience and in most cases, the assumption is, that the recipient isn't familiar with computers at all. I've found ... |
2019/07/15 | 772 | 3,205 | <issue_start>username_0: The definition of *deterministic environment* I am familiar with goes as follows:
>
> The next state of the agent depends only on the current state and the action chosen by the agent.
>
>
>
By exclusion, everything else would be a *stochastic environment*.
However, what about environment... |
2019/07/16 | 814 | 3,217 | <issue_start>username_0: Tay was a chatbot, who learned from Twitter users.
>
> Microsoft's AI fam from the internet that's got zero chill. The more you talk the smarter Tay gets. — Twitter tagline.
>
>
>
Microsoft trained the AI to have a basic ability to communicate, and taught it a few jokes from hired comedia... |
2019/07/19 | 790 | 3,169 | <issue_start>username_0: I've heard that [prediction is equivalent to data compression](https://www.reddit.com/r/artificial/comments/5r4vwa/data_compression_as_the_key_to_agi/).
Is there a way to take a compression function and use it to create an AI that predicts?<issue_comment>username_1: The way some (not all) comp... |
2019/07/19 | 913 | 3,246 | <issue_start>username_0: To me, most ANN/RNN related articles don't tell me actually how the network is implemented. I know that in the ANN you'll have multiple neurons, activation function, weights, etc. But, how do you, actually, in each neuron, convert the input to the output?
Putting activation function aside, is ... |
2019/07/19 | 1,026 | 3,789 | <issue_start>username_0: Say I have a ML model which is not very costly to train. It has around say 5 hyperparameters.
One way to select best hyperparameters would be to keep all the other hyperparamaters fixed and train the model by changing only one hyperparameter within a certain range. For the sake of mathematica... |
2019/07/19 | 1,657 | 6,378 | <issue_start>username_0: I am unsure about the following parts of the architecture and mechanics of convolution layers in CNNs. Possibly, this is implementation-dependent though.
**First question:**
Say I have 2 convolution layers with 10 filters each and the dimension of my input tensors is $n \times m \times 1$ (so... |
2019/07/23 | 1,162 | 4,318 | <issue_start>username_0: Why do people use the $PReLU$ activation?
$PReLU[x] = ReLU[x] + ReLU[p\*x]$
with the parameter $p$ typically being a small negative number.
If a fully connected layer is followed by a at least two element $ReLU$ layer then the combined layers together are capable of emulating exactly the $PR... |
2019/07/23 | 898 | 3,484 | <issue_start>username_0: In [this answer](https://ai.stackexchange.com/a/13543/2444) to the question [Is an optimization algorithm equivalent to a neural network?](https://ai.stackexchange.com/q/13524/2444), the author stated that, in theory, there is some recurrent neural network that implements a given optimization a... |
2019/07/26 | 1,359 | 5,783 | <issue_start>username_0: I have very outdated idea about how NLP tasks are carried out by normal RNN's, LSTM's/GRU's, word2vec, etc to basically generate some hidden form of the sentence understood by the machine.
One of the things I have noticed is that in general researchers are interested in generating the context ... |
2019/07/26 | 1,298 | 5,655 | <issue_start>username_0: I'm very new to AI. I read somewhere that AI can be used to create GUI UI/UX design. That has fascinated me for a long time. But, since I'm very new here, I don't have any idea how it can happen.
The usual steps to create the UI Design are:
* Create Grids.
* Draw Buttons/Text/Boxes/Borders/s... |
2019/07/29 | 1,411 | 5,369 | <issue_start>username_0: I would like to incrementally train my model with my current dataset and [I asked this question on Github](https://github.com/tensorflow/models/issues/7200#issuecomment-510850230), which is what I'm using SSD MobileNet v1.
Someone there told me about [**learning without forgetting**](https://a... |
2019/07/29 | 1,222 | 4,761 | <issue_start>username_0: I am working with [the Inception ResNet V2 model](https://ai.googleblog.com/2016/08/improving-inception-and-image.html), pre-trained with ImageNet, for face recognition.
However, I'm so confused about what the exact output of the feature extraction layer (i.e. the layer just before the fully c... |
2019/07/29 | 783 | 3,389 | <issue_start>username_0: Suppose we have a data set with $4,000$ labeled examples. The outcome variable is trinary (three possible categorical values). Suppose the accuracy of a given model is "bad" (e.g. less than $50 \%$).
>
> **Question.** Should you try different traditional machine learning models (e.g. multinom... |
2019/07/30 | 1,105 | 4,833 | <issue_start>username_0: When executing MCTS' expansion phase, where you create a number of child nodes, select one of the numbers, and simulate from that child, how can you efficiently and unbiasedly decide which child(ren) to generate?
One strategy is to always generate all possible children. I believe that [this an... |
2019/07/30 | 584 | 2,461 | <issue_start>username_0: Many games have multiple paths to the same states. What is the appropriate way to deal with this in MCTS?
If the state appears once in the tree, but with multiple parents, then it seems to be difficult to define back propagation: do we only propagate back along the path that got us there "thi... |
2019/07/31 | 874 | 3,315 | <issue_start>username_0: I am new to convolutional neural networks, and I am learning 3D convolution. What I could understand is that 2D convolution gives us relationships between low-level features in the X-Y dimension, while the 3D convolution helps detect low-level features and relationships between them in all the ... |
2019/07/31 | 811 | 3,021 | <issue_start>username_0: I am building a model which predicts angles as output. What are the different kinds of outputs that can be used to predict angles?
For example,
1. output the angle in radians
* cyclic nature of the angles is not captured
* output might be outside $\left[-\pi, \pi \right)$
2. output the sine... |
2019/07/31 | 695 | 3,047 | <issue_start>username_0: I have a decent background in Mathematics and Computer Science .I started learning AI from Andrew Ng's course from one month back. I understand logic and intuition behind everything taught but if someone asks me to write or derive mathematical formulas related to back propagation I will fail to... |
2019/08/02 | 3,953 | 14,407 | <issue_start>username_0: I came across a comment recently "reads like sentences strung together with no logic." But is this even possible?
Sentences can be strung together randomly if the selection process is random. (Random sentences in a random sequence.) Stochasticity does not seem logical—it's a probability distri... |
2019/08/02 | 3,492 | 13,205 | <issue_start>username_0: I'm reading the book Pattern Recognition and Machine Learning by Bishop, specifically the intro where he covers polynomial regression model. In short, let's say we generate $10$ data points using the function $\sin(2\pi x)$ and add some gaussian random noise to each observation. Now we pretend ... |
2019/08/04 | 2,429 | 10,308 | <issue_start>username_0: I just finished a 1-year Data Science master's program where we were taught R. I found that Python is more popular and has a larger community in AI.
What are the advantages that Python may have over R in terms of features applicable to the field of Data Science and AI (other than popularity an... |
2019/08/05 | 294 | 1,264 | <issue_start>username_0: Is there any way to make [deepfake](https://en.wikipedia.org/wiki/Deepfake) videos without a fancy computer? For example, run the [DeepFaceLab](https://github.com/iperov/DeepFaceLab) on a website so your own computer won't get involved?<issue_comment>username_1: Yes. There are services that pro... |
2019/08/06 | 433 | 1,601 | <issue_start>username_0: I've heard somewhere that due to their nature of capturing spatial relations, even untrained CNNs can be used as feature extractors? Is this true? Does anyone have any sources regarding this I can look at?<issue_comment>username_1: I'm not sure it's possible. Untrained CNN means it has random k... |
2019/08/06 | 535 | 2,130 | <issue_start>username_0: As per subject title, are there ways to try Deep Learning without downloading and installing anything?
I'm just trying to have a feel of how this work, not really want to go through the download and install step if possible.<issue_comment>username_1: You can definitely get a good handle on th... |
2019/08/06 | 528 | 2,119 | <issue_start>username_0: I have implemented a CNN for image classification. I have not used fully connected layers, but only a softmax. Still, I am getting results.
Must I use fully-connected layers in a CNN?<issue_comment>username_1: In theory, you do not need fully-connected (FC) layers. FC layers are used to intro... |
2019/08/06 | 572 | 2,351 | <issue_start>username_0: **In a neural network, by how much does the number of neurons typically vary from layer to layer?**
Note that I am **NOT** asking how to find the optimal number of neurons per layer.
As a hardware design engineer with no practical experience programming neural networks, I would like to glean ... |
2019/08/06 | 563 | 2,140 | <issue_start>username_0: I recently came across this [article](https://www.analyticsindiamag.com/iisc-bangalores-ai-team-comes-up-with-a-solution-to-an-old-nlp-problem/) which cites a [paper](https://malllabiisc.github.io/publications/papers/EWISE_ACL19.pdf), which apparently won the outstanding paper award in ACL 2019... |
2019/08/06 | 756 | 3,329 | <issue_start>username_0: As everyone experienced in deep learning might know, in an image classification problem we normally add borders to images then resize it to the input size of a CNN network. The reason of doing this is to keep aspect ratio of the original image and retain it's information.
I have seen people f... |
2019/08/07 | 1,674 | 6,046 | <issue_start>username_0: As the question suggests, I'm trying to see if I can solve [OpenAI's hardcore version of their gym's bipedal walker](https://gym.openai.com/envs/BipedalWalkerHardcore-v2/) using OpenAI's [DDPG algorithm](https://spinningup.openai.com/en/latest/algorithms/ddpg.html).
Below is a performance grap... |
2019/08/08 | 4,176 | 17,218 | <issue_start>username_0: So far I understand - I know very little on the topic - the core of AI boils down to design algorithms that shall provide a TRUE/FALSE answer to a given statement. Nevertheless, I am aware of the limitations provided by the Gödel's incomplete theorems but I am also aware that there have been lo... |
2019/08/08 | 544 | 2,544 | <issue_start>username_0: I am wondering if I can use neural networks to find features importances in similar manner as it can be done for random forests or decision trees and if so, how to do it?
I would like to use it on tabular time series data (not images). The reason why I want to find importances on neural networ... |
2019/08/09 | 2,233 | 9,019 | <issue_start>username_0: This seems like such a simple idea, but I've never heard anyone that has addressed it, and a quick Google revealed nothing, so here it goes.
The way I learned about machine learning is that it recognizes patterns in data, and not necessarily ones that exist -- which can lead to bias. One such ... |
2019/08/09 | 1,490 | 6,335 | <issue_start>username_0: I'm trying to use a Monte Carlo Tree Search for a non-deterministic game. Apparently, one of the standard approaches is to model non-determinism using *chance nodes*. The problem for this game is that it has a very high min-entropy for the random events (imagine the shuffle of a deck of cards),... |
2019/08/11 | 643 | 2,563 | <issue_start>username_0: Every week I will get a lot of videos from a game that I play, outside the game where you throw wooden skittle bats at skittles, and then I will cut videos, so that, at the end. there [is video only about throws](https://www.youtube.com/watch?v=ITCglVMyKLs).
The job is simple and systematic. ... |
2019/08/12 | 549 | 2,542 | <issue_start>username_0: A while back I posted on the Reverse Engineering site about an audio DSP system whose designer had passed away and whose manufacturer no longer had source code (but [the question was deleted](https://reverseengineering.stackexchange.com/questions/17238/decode-filter-coefficients-for-audio-dsp))... |
2019/08/12 | 1,782 | 7,796 | <issue_start>username_0: I came across 'Amber'(<https://ambervideo.co/>) where they are claiming that they have trained their AI to find patterns emerging due to artificially created videos which are invisible to naked eye.
I am wondering that the people who are creating deepfakes can as well their AI's to remove the... |
2019/08/12 | 706 | 2,634 | <issue_start>username_0: Assume I have a list of sentences, which is just a list of strings. I need a way of comparing some input string against those sentences to find the most similar. Can [ELMO embeddings](https://allennlp.org/elmo) be used to train a model that can give you the $n$ most similar sentences to an inpu... |
2019/08/13 | 886 | 3,351 | <issue_start>username_0: For an experiment that I'm working on, I want to train a deep network in a special way. I want to initialize and train a small network first, then, in a specific way, I want to increase network depth leading to a bigger network which is subsequently to be trained. This process will be repeated ... |
2019/08/13 | 1,236 | 5,492 | <issue_start>username_0: Consider an MLP that outputs an integer 'rating' of 0 to 4. Would it be correct to say this could be modeled in either of the following ways:
1. map each rating in the dataset to a 'normalized set' between 0 and 1 (i.e. 0, 0.25, 0.5, 0.75, 1), have a single neuron with sigmoid activation at ou... |
2019/08/14 | 1,610 | 6,692 | <issue_start>username_0: I'm a beginner of RL and currently trying to make DQN agent that can act optimally in a simple situation.
In the situation agent should decide at what rate to charge or discharge the electrical battery, which is equivalent to buying the electrical energy or selling it, for making money by mea... |
2019/08/14 | 2,083 | 7,621 | <issue_start>username_0: I'm new to NN. I am trying to understand some of its foundations. One question that I have is: *why the **derivative** of an activation function is important (not the function itself), and why it's the derivative which is tied to how the network performs learning*?
For instance, when we say a... |
2019/08/15 | 2,078 | 7,717 | <issue_start>username_0: I read these comments from Judea Pearl saying we don't have causality, physical equations are symmetric, etc. But the conditional probability is clearly not symmetric and captures directed relationships.
How would Pearl respond to someone saying that conditional probability already captures a... |
2019/08/16 | 2,100 | 8,087 | <issue_start>username_0: I am a newbie in the fantastic AI world, I have started my learning recently.
After a while, my understanding is, we need to feed in tremendous data to train a or many models.
Once the training is complete, we could take out the trained models and "plug in" to any other programming languages... |
2019/08/16 | 517 | 2,294 | <issue_start>username_0: I've been reading different papers regarding graph convolution and it seems that they come into two flavors: spatial and spectral. From what I can see the main difference between the two approaches is that for spatial you're directly multiplying the adjacency matrix with the signal whereas for ... |
2019/08/16 | 598 | 2,760 | <issue_start>username_0: I am currently building a chatbot. What I have done so far is, collected possible questions/training data/files and create a model out of it using Apache OpenNLP; the model is able to predict all the questions that are in the training data and fails to predict for new questions.
Instead of doi... |
2019/08/18 | 565 | 2,431 | <issue_start>username_0: I have developed face recognition algorithms by using pre-built libraries in Python and open CV. However, suppose if I want to make my own neural network algorithm for face recognition, what are the steps that I need to follow?
I have just seen [<NAME>'s course videos](https://www.youtube.com/... |
2019/08/19 | 1,260 | 4,843 | <issue_start>username_0: There seems to be a lot of literature and research on the problems of stochastic gradient descent and catastrophic forgetting, but I can't find much on solutions to perform continual learning with neural network architectures.
By continual learning, I mean improving a model (while using it) wi... |
2019/08/21 | 2,898 | 11,204 | <issue_start>username_0: [](https://i.stack.imgur.com/7FnY6.png)
I tried to create a simple model that receives an $80 \times 130$ pixel image. I only had 35 images and 10 test images. I trained this model for a binary classification task. The archite... |
2019/08/21 | 2,572 | 9,871 | <issue_start>username_0: Is it possible to specify what the asymptotic behaviour of a Neural Networks (NN) model should be?
I am thinking of a NN which tries to learn a mapping $\vec y=f(\vec x)$ with $\vec x$ a vector of features of dimension $d$ and $\vec y$ a vector of outputs of dimension $p$.
Is it possible to s... |
2019/08/23 | 582 | 1,664 | <issue_start>username_0: Suppose we have a labeled data set with columns $A$, $B$, and $C$ and a binary outcome variable $X$. Suppose we have rows as follows:
```
col A B C X
1 1 2 3 1
2 4 2 3 0
3 6 5 1 1
4 1 2 3 0
```
Should we throw away either row 1 or row 4 because they have different values of... |
2019/08/24 | 624 | 2,555 | <issue_start>username_0: Currently, I am working on a few projects that use feedforward neural networks for regression and classification of simple tabular data. I have noticed that training a neural network using TensorFlow-GPU is often slower than training the same network using TensorFlow-CPU.
Could something be wr... |
2019/08/25 | 575 | 2,406 | <issue_start>username_0: I started working on the application of deep learning in medical imaging recently. While dealing with MRI images in the BraTS dataset, I observe that first and last few frames are always completely empty (black). I want to ask those who are already working in the field, is there a way to remove... |
2019/08/27 | 2,518 | 8,696 | <issue_start>username_0: I came across some papers that use $\mathbb E$ in equations, in particular, this paper: <https://arxiv.org/pdf/1511.06581.pdf>. Here is some equations from the paper that uses it:
$Q^\pi \left(s,a \right) = \mathbb E \left[R\_t|s\_t = s, a\_t = a, \pi \right]$ ,
$V^\pi \left(s \right) = \mat... |
2019/08/28 | 487 | 1,943 | <issue_start>username_0: K-means tries to find centroid and then clusters around the centroids. But what if we want to cluster based on the complement?
For example, suppose we have a group of animals and we want to cluster Dogs, Cats, (Not Dogs and Not Cats). The 3rd category will not arise from mean clustering.<issue... |
2019/08/30 | 680 | 2,855 | <issue_start>username_0: How do I program a neural network such that, when an image is inputted, the output is a numerical value that is not the probability of the image being a certain class? In other words, a CNN that doesn't classify. For example, when an input of an image of a chair is given, the model should not g... |
2019/08/30 | 2,011 | 6,983 | <issue_start>username_0: I would like to take in some input values for $n$ variables, say $R$, $B$, and $G$. Let $Y$ denote the response variable of these $n$ inputs (in this example, we have $3$ inputs). Other than these, I would like to use a reference/target value to compare the results.
Now, suppose the relation ... |
2019/08/31 | 3,809 | 14,341 | <issue_start>username_0: If the original purpose for developing AI was to help humans in some tasks and that purpose still holds, why should we care about its explainability? For example, in deep learning, as long as the intelligence helps us to the best of their abilities and carefully arrives at its decisions, why wo... |
2019/09/01 | 1,474 | 5,154 | <issue_start>username_0: After an AI goes through the process described in [How would an AI learn language?](https://ai.stackexchange.com/questions/1970/how-would-an-ai-learn-language), an AI knows the grammar of a language through the process of grammar induction. They can speak the language, but they have learned *fo... |
2019/09/02 | 552 | 2,056 | <issue_start>username_0: I have a simple text classifier, with the following structure:
```
input = keras.layers.Input(shape=(len(train_x[0]),))
x=keras.layers.Dense(500, activation='relu')(input)
x=keras.layers.Dropout(0.5)(x)
x=keras.layers.Dense(250, activation='relu')(x)
x=keras.layers.Dropout... |
2019/09/04 | 834 | 3,399 | <issue_start>username_0: When watching the machine learning course on Coursera by <NAME>, in the logistic regression week, the cost function was a bit more complex than the one for linear regression, but definitely not that hard.
But it got me thinking, why not use the same cost function for logistic regression?
So... |
2019/09/11 | 926 | 3,180 | <issue_start>username_0: I've recently encountered different articles that are recommending to use the KL divergence instead of the MSE/RMSE (as the loss function), when trying to learn a probability distribution, but none of the articles are giving a clear reasoning why the first is better than the others.
Could anyo... |