question_id
int64 6
6.85k
| course_id
int64 0
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stringlengths 6
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3
|
|---|---|---|---|---|---|---|---|
1,214 | 15,127 |
Computer Science
|
master
|
Let's imagine that every pet owner in Europe sends us their dog and cat data to train our model, so we have lots of training data. Which of the following is true about the possible optimizers used to train our model? We assume that the optimal hyperparameters are used for each optimizer.
|
[
"Gradient descent steps are more computationally efficient, while Newton's method takes fewer steps to converge.",
"Gradient descent takes fewer steps to converge, while Newton steps are more computationally efficient.",
"Gradient descent and Newton's method take similar number of iterations to converge.",
"Overall, gradient descent and Newton's method are equal in terms of computational complexity."
] |
Gradient descent steps are more computationally efficient, while Newton's method takes fewer steps to converge.
| 0 |
1,216 | 15,127 |
Computer Science
|
master
|
You are doing your ML project. It is a regression task under a square loss. Your neighbor uses linear regression and least squares. You are smarter. You are using a neural net with 10 layers and activations functions $f(x)=3 x$. You have a powerful laptop but not a supercomputer. You are betting your neighbor a beer at Satellite who will have a substantially better scores. However, at the end it will essentially be a tie, so we decide to have two beers and both pay. What is the reason for the outcome of this bet?
|
[
"Because we use exactly the same scheme.",
"Because it is almost impossible to train a network with 10 layers without a supercomputer.",
"Because I should have used more layers.",
"Because I should have used only one layer."
] |
Because we use exactly the same scheme.
| 0 |
1,217 | 15,127 |
Computer Science
|
master
|
Let $f:\R^D
ightarrow\R$ be an $L$-hidden layer multi-layer perceptron (MLP) such that
\[
f(xv)=\sigma_{L+1}ig(\wv^ op\sigma_L(\Wm_L\sigma_{L-1}(\Wm_{L-1}\dots\sigma_1(\Wm_1xv)))ig),
\]
with $\wv\in\R^{M}$, $\Wm_1\in\R^{M imes D}$ and $\Wm_\ell\in\R^{M imes M}$ for $\ell=2,\dots, L$, and $\sigma_i$ for $i=1,\dots,L+1$ is an entry-wise activation function. For any MLP $f$ and a classification threshold $ au$ let $C_{f, au}$ be a binary classifier that outputs YES for a given input $xv$ if $f(xv) \leq au$ and NO otherwise. space{3mm}
Assume $\sigma_{L+1}$ is the element-wise extbf{sigmoid} function and $C_{f, rac{1}{2}}$ is able to obtain a high accuracy on a given binary classification task $T$. Let $g$ be the MLP obtained by multiplying the parameters extbf{in the last layer} of $f$, i.e. $\wv$, by 2. Moreover, let $h$ be the MLP obtained by replacing $\sigma_{L+1}$ with element-wise extbf{ReLU}. Finally, let $q$ be the MLP obtained by doing both of these actions. Which of the following is true?
ReLU(x) = max\{x, 0\} \
Sigmoid(x) = rac{1}{1 + e^{-x}}
|
[
"$C_{g, \frac{1}{2}}$ may have an accuracy significantly lower than $C_{f, \frac{1}{2}}$ on $T$",
"$C_{h, 0}$ may have an accuracy significantly lower than $C_{f, \frac{1}{2}}$ on $T$",
"$C_{q, 0}$ may have an accuracy significantly lower than $C_{f, \frac{1}{2}}$ on $T$",
"$C_{g, \frac{1}{2}}$, $C_{h, 0}$, and $C_{q, 0}$ have the same accuracy as $C_{f, \frac{1}{2}}$ on $T$"
] |
$C_{g, rac{1}{2}}$, $C_{h, 0}$, and $C_{q, 0}$ have the same accuracy as $C_{f, rac{1}{2}}$ on $T$
| 3 |
1,218 | 15,127 |
Computer Science
|
master
|
Binary logistic regression assumes a:
|
[
"Linear relationship between the input variables.",
"Linear relationship between the observations.",
"Linear relationship between the input variables and the logit (inverse of sigmoid) of the probability of the event that the outcome $Y=1$.",
"Linear relationship between the input variables and the probability of the event that the outcome $Y=1$"
] |
Linear relationship between the input variables and the logit (inverse of sigmoid) of the probability of the event that the outcome $Y=1$.
| 2 |
1,221 | 15,127 |
Computer Science
|
master
|
Let $f_{\mathrm{MLP}}: \mathbb{R}^{d} \rightarrow \mathbb{R}$ be an $L$-hidden layer multi-layer perceptron (MLP) such that $$ f_{\mathrm{MLP}}(\mathbf{x})=\mathbf{w}^{\top} \sigma\left(\mathbf{W}_{L} \sigma\left(\mathbf{W}_{L-1} \ldots \sigma\left(\mathbf{W}_{1} \mathbf{x}\right)\right)\right) $$ with $\mathbf{w} \in \mathbb{R}^{M}, \mathbf{W}_{1} \in \mathbb{R}^{M \times d}$ and $\mathbf{W}_{\ell} \in \mathbb{R}^{M \times M}$ for $\ell=2, \ldots, L$, and $\sigma$ is an entry-wise activation function. Also, let $f_{\mathrm{CNN}}: \mathbb{R}^{d} \rightarrow \mathbb{R}$ be an $L^{\prime}$-hidden layer convolutional neural network (CNN) such that $$ f_{\mathrm{CNN}}(\mathbf{x})=\mathbf{w}^{\top} \sigma\left(\mathbf{w}_{L^{\prime}} \star \sigma\left(\mathbf{w}_{L^{\prime}-1} \star \ldots \sigma\left(\mathbf{w}_{1} \star \mathbf{x}\right)\right)\right) $$ with $\mathbf{w} \in \mathbb{R}^{d}, \mathbf{w}_{\ell} \in \mathbb{R}^{K}$ for $\ell=1, \ldots, L^{\prime}$ and $\star$ denoting the one-dimensional convolution operator with zero-padding, i.e., output of the convolution has the same dimensionality as the input. Regarding the weight updates in back-propagation,
|
[
"The output layer weights are not used for computing the error of the hidden layer.",
"The weight changes are not proportional to the difference between the desired and actual outputs.",
"A standard technique to initialize the weights is to set them exactly to 0.",
"The weight change is also proportional to the input to the weight layer."
] |
The weight change is also proportional to the input to the weight layer.
| 3 |
1,222 | 15,127 |
Computer Science
|
master
|
Let the samples $\left\{\left(y_{n}, x_{n}\right)\right\}$ come from some fixed joint distribution $p(x, y)$, where $x_{n}$ and $y_{n}$ are scalars and both have zero mean. Consider linear regression, i.e., we want to predict $Y$ from $X$ by means of $f(x)=\alpha x$ and we consider a square loss. Meaningful regression is possible
|
[
"(a) only if $X$ \"causes\" $Y$",
"(b) as long as $Y$ and $X$ have non-zero correlation",
"(c) only if $Y$ and $X$ are positively correlated, i.e., $\\mathbb{E}[X Y]>0$",
"(d) only if $Y$ and $X$ are negatively correlated, i.e., $\\mathbb{E}[X Y]<0$"
] |
(c) only if $Y$ and $X$ are positively correlated, i.e., $\mathbb{E}[X Y]>0$
| 2 |
1,226 | 15,100 |
Life Sciences Engineering
|
online
|
Does this learning rule allow for both potentiation and depression?
|
[
"No, because there aren't any negative terms.",
"Yes, because there are also negative terms.",
"No, because the negative terms are always smaller than the positive ones.",
"Yes, only because there is the last term with the power of four."
] |
Yes, because there are also negative terms.
| 1 |
1,241 | 15,100 |
Life Sciences Engineering
|
online
|
The above mentioned property of the energy function [mathjaxinline] H [/mathjaxinline] was proven explicitly in the exercises of this course. In an intermediate step of this proof we could write the energy change as
|
[
"The minus sign of the energy change [mathjaxinline] \\Delta H [/mathjaxinline] itself ensures the decay of the energy function. Thus it is always decreasing, i.e. it never increases.",
"The update dynamics includes the sign-function. Thus the product in the energy change [mathjaxinline] \\Delta H [/mathjaxinline] is always positiv. The minus sign in [mathjaxinline] \\Delta H [/mathjaxinline] finally leads to a negative change in every case. Thus [mathjaxinline] H [/mathjaxinline] is always decreasing, i.e. the energy never increases.",
"The update dynamics includes the sign-function. Thus the product in the energy change [mathjaxinline] \\Delta H [/mathjaxinline] is always negativ. The minus sign in [mathjaxinline] \\Delta H [/mathjaxinline] finally leads to a positive change in every case. Thus [mathjaxinline] H [/mathjaxinline] is strictly increasing.",
"The quantities [mathjaxinline] S_k(t+1) [/mathjaxinline] and [mathjaxinline] \\sum_j w_{kj} S_j(t) [/mathjaxinline] are always orthogonal. Thus their product in [mathjaxinline] \\Delta H [/mathjaxinline] is 0 and accordingly we obtain [mathjaxinline] \\Delta H = 0 [/mathjaxinline]. This means that the energy is conserved: [mathjaxinline] H = const [/mathjaxinline]."
] |
The update dynamics includes the sign-function. Thus the product in the energy change [mathjaxinline] \Delta H [/mathjaxinline] is always positiv. The minus sign in [mathjaxinline] \Delta H [/mathjaxinline] finally leads to a negative change in every case. Thus [mathjaxinline] H [/mathjaxinline] is always decreasing, i.e. the energy never increases.
| 1 |
1,243 | 15,100 |
Life Sciences Engineering
|
online
|
We assume a pair-based STDP model formulated with traces:
|
[
"For pre-before-post the decay of the STDP window is exponential with time constant [mathjaxinline]\\tau_+[/mathjaxinline].",
"For pre-before-post the decay is a double exponential with time constants [mathjaxinline]\\tau_+[/mathjaxinline] and [mathjaxinline]\\tau_-[/mathjaxinline].",
"For pre-before-post the decay of the STDP window is exponential with time constant [mathjaxinline]\\tau_-[/mathjaxinline].",
"The integral over the STDP window is always positive."
] |
For pre-before-post the decay of the STDP window is exponential with time constant [mathjaxinline]\tau_+[/mathjaxinline].
| 0 |
1,245 | 15,052 |
Life Sciences Engineering
|
online
|
The space constant of a passive cable is:
|
[
"[mathjaxinline]\\lambda=\\frac{r_m}{r_L}[/mathjaxinline]",
"[mathjaxinline]\\lambda=\\frac{r_L}{r_m}[/mathjaxinline]",
"[mathjaxinline]\\lambda=\\sqrt{\\frac{r_L}{r_m}}[/mathjaxinline]",
"[mathjaxinline]\\lambda=\\sqrt{\\frac{r_m}{r_L}}[/mathjaxinline]"
] |
[mathjaxinline]\lambda=\sqrt{\frac{r_m}{r_L}}[/mathjaxinline]
| 3 |
1,249 | 15,052 |
Life Sciences Engineering
|
online
|
A spike train is generated by a homogenous Poisson process with rate 25Hz with time steps of 0.1 ms.
|
[
"The most likely interspike interval is 25 ms.",
"The most likely interspike interval is 40 ms.",
"The most likely interspike interval is 0.1 ms.",
"We cannot say."
] |
The most likely interspike interval is 0.1 ms.
| 2 |
1,252 | 15,052 |
Life Sciences Engineering
|
online
|
Consider AdEx dynamical system:
|
[
"[mathjaxinline]u[/mathjaxinline]-nullcline moves horizontally",
"[mathjaxinline]u[/mathjaxinline]-nullcline moves vertically",
"[mathjaxinline]w[/mathjaxinline]-nullcline moves horizontally",
"[mathjaxinline]w[/mathjaxinline]-nullcline moves vertically"
] |
[mathjaxinline]u[/mathjaxinline]-nullcline moves vertically
| 1 |
1,401 | 15,052 |
Life Sciences Engineering
|
online
|
If a short current pulse is injected into the dendrite:
|
[
"the voltage at the injection site is maximal immediately after the end of the injection.",
"the voltage at the dendritic injection site is maximal a few milliseconds after the end of the injection.",
"the voltage at the soma is maximal immediately after the end of the injection.",
"the voltage at the soma is maximal a few milliseconds after the end of the injection."
] |
the voltage at the injection site is maximal immediately after the end of the injection.
| 0 |
1,402 | 15,052 |
Life Sciences Engineering
|
online
|
A spike train is generated by an inhomogenous Poisson process with a rate that oscillates periodically (sine wave with 1Hz frequency) between 0 and 50Hz (mean 25Hz). A first spike has been fired at a time when the rate was at its maximum. Time steps are 0.1ms.
|
[
"The most likely interspike interval is 25 ms.",
"The most likely interspike interval is 40 ms.",
"The most likely interspike interval is 0.1 ms.",
"We cannot say."
] |
The most likely interspike interval is 0.1 ms.
| 2 |
1,403 | 15,125 |
Computer Science
|
master
|
Which statement is false in the context of recommender systems?
|
[
"Cold-start problem is a typical problem of user-based collaborative filtering",
"Matrix factorization can be interpreted as a combination of user-based and content-based collaborative filtering",
"In item-based collaborative filtering, the item similarities can be computed in advance",
"Content-based recommendation tends to recommend more of the same items to users"
] |
Matrix factorization can be interpreted as a combination of user-based and content-based collaborative filtering
| 1 |
1,404 | 15,125 |
Computer Science
|
master
|
Which of the following is correct regarding Louvain algorithm?
|
[
"It creates a hierarchy of communities with a common root",
"Clique is the only topology of nodes where the algorithm detects the same communities, independently of the starting point",
"If n cliques of the same order are connected cyclically with n-1 edges, then the algorithm will always detect the same communities, independently of the starting point",
"Modularity is always maximal for the communities found at the top level of the community hierarchy"
] |
If n cliques of the same order are connected cyclically with n-1 edges, then the algorithm will always detect the same communities, independently of the starting point
| 2 |
1,405 | 15,125 |
Computer Science
|
master
|
Considering the transaction below, which one is false?
Transaction IDItems Bought1Tea2Tea, Yoghurt3Tea, Yoghurt, Kebap4Kebap5Tea, Kebap
|
[
"{Yoghurt, Kebap} has 20% support",
"{Tea} has the highest support",
"{Yoghurt} -> {Kebab} has 50% confidence",
"{Yoghurt} has the lowest support among all itemsets"
] |
{Yoghurt} has the lowest support among all itemsets
| 3 |
1,406 | 15,125 |
Computer Science
|
master
|
What is WRONG regarding the Transformer model?
|
[
"Its computation cannot be parallelized compared to LSTMs and other sequential models.",
"It uses a self-attention mechanism to compute representations of the input and output.",
"Its complexity is quadratic to the input size.",
"It captures the semantic context of the input."
] |
Its computation cannot be parallelized compared to LSTMs and other sequential models.
| 0 |
1,407 | 15,125 |
Computer Science
|
master
|
If we run the Apriori algorithm on the following transaction database with minimal support count of 2, which of the itemsets will have a support count of 3?Transaction IDItemsT1{1,3,4}T2{2,3,5}T3{1,2,3,5}T4{2,5}T5{1,2,3,5}
|
[
"{1,5}",
"{2,3}",
"{2,5}",
"{1,2}"
] |
{2,3}
| 1 |
1,408 | 15,125 |
Computer Science
|
master
|
When computing PageRank iteratively, the computation ends when:
|
[
"The norm of the difference of rank vectors of two subsequent iterations falls below a predefined threshold",
"The difference among the eigenvalues of two subsequent iterations falls below a predefined threshold",
"All nodes of the graph have been visited at least once",
"The probability of visiting an unseen node falls below a predefined threshold"
] |
The norm of the difference of rank vectors of two subsequent iterations falls below a predefined threshold
| 0 |
1,409 | 15,125 |
Computer Science
|
master
|
Consider the document: “Information retrieval is the task of finding the documents satisfying the information needs of the user”
Using MLE to estimate the unigram probability model, what is P(the|Md) and P(information|Md)?
|
[
"1/16 and 1/16",
"1/12 and 1/12",
"1/4 and 1/8",
"1/3 and 1/6"
] |
1/4 and 1/8
| 2 |
1,410 | 15,125 |
Computer Science
|
master
|
Let the first four retrieved documents be N N R R, where N denotes a non-relevant and R a relevant document. Then the MAP (Mean Average Precision) is:
|
[
"1/2",
"5/12",
"3/4",
"7/24"
] |
5/12
| 1 |
1,411 | 15,125 |
Computer Science
|
master
|
Which one of the following is wrong. Schema mapping is used to:
|
[
"Overcome semantic heterogeneity",
"Reconcile different logical representations of the same domain",
"Optimize the processing of queries",
"Support schema evolution of databases"
] |
Optimize the processing of queries
| 2 |
1,414 | 15,125 |
Computer Science
|
master
|
Modularity clustering will end up always with a single community at the top level?
|
[
"true",
"Only for dense graphs",
"Only for connected graphs",
"never"
] |
Only for connected graphs
| 2 |
1,416 | 15,125 |
Computer Science
|
master
|
The inverse document frequency of a term can increase
|
[
"by adding the term to a document that contains the term",
"by removing a document from the document collection that does not contain the term",
"by adding a document to the document collection that contains the term",
"by adding a document to the document collection that does not contain the term"
] |
by adding a document to the document collection that does not contain the term
| 3 |
1,417 | 15,125 |
Computer Science
|
master
|
Which of the following is wrong regarding Ontologies?
|
[
"We can create more than one ontology that conceptualize the same real-world entities",
"Ontologies help in the integration of data expressed in different models",
"Ontologies support domain-specific vocabularies",
"Ontologies dictate how semi-structured data are serialized"
] |
Ontologies dictate how semi-structured data are serialized
| 3 |
1,418 | 15,125 |
Computer Science
|
master
|
In a Ranked Retrieval result, the result at position k is non-relevant and at k+1 is relevant. Which of the following is always true (P@k and R@k are the precision and recall of the result set consisting of the k top ranked documents)?
|
[
"P@k-1 > P@k+1",
"P@k-1 = P@k+1",
"R@k-1 < R@k+1",
"R@k-1 = R@k+1"
] |
R@k-1 < R@k+1
| 2 |
1,419 | 15,125 |
Computer Science
|
master
|
We want to return, from the two posting lists below, the top-2 documents matching a
query using Fagin’s algorithm with the aggregation function taken as the sum of the tf-idf weights. How many entries (total of both lists) are accessed in the first phase of the
algorithm performing round-robin starting at List 1 (i.e., before performing the random
access)?
|
[
"4",
"6",
"8",
"10"
] |
8
| 2 |
1,420 | 15,125 |
Computer Science
|
master
|
What is true regarding Fagin's algorithm?
|
[
"It performs a complete scan over the posting files",
"It provably returns the k documents with the largest aggregate scores",
"Posting files need to be indexed by TF-IDF weights",
"It never reads more than (kn)½ entries from a posting list"
] |
It provably returns the k documents with the largest aggregate scores
| 1 |
1,421 | 15,125 |
Computer Science
|
master
|
Which of the following is true for Recommender Systems (RS)?
|
[
"Matrix Factorization can predict a score for any user-item combination in the dataset.",
"The complexity of the Content-based RS depends on the number of users",
" Item-based RS need not only the ratings but also the item features",
"Matrix Factorization is typically robust to the cold-start problem."
] |
Matrix Factorization can predict a score for any user-item combination in the dataset.
| 0 |
1,422 | 15,125 |
Computer Science
|
master
|
Which of the following is WRONG for Ontologies?
|
[
"Different information systems need to agree on the same ontology in order to interoperate.",
"They help in the integration of data expressed in different models.",
"They give the possibility to specify schemas for different domains.",
"They dictate how semi-structured data are serialized."
] |
They dictate how semi-structured data are serialized.
| 3 |
1,423 | 15,125 |
Computer Science
|
master
|
Why is non-discounted cumulative gain used as evaluation metrics for recommender systems
|
[
"because often only the top recommendations are considered by the user",
"because it is more accurate than retrieval metrics, like precision and recall",
"because it considers the predicted ratings of all items that have not been rated by the user",
"because it allows to consider the financial value of recommended items "
] |
because often only the top recommendations are considered by the user
| 0 |
1,424 | 15,125 |
Computer Science
|
master
|
What is the benefit of LDA over LSI?
|
[
"LSI is sensitive to the ordering of the words in a document, whereas LDA is not",
"LDA has better theoretical explanation, and its empirical results are in general better than LSI’s",
"LSI is based on a model of how documents are generated, whereas LDA is not",
"LDA represents semantic dimensions (topics, concepts) as weighted combinations of terms, whereas LSI does not"
] |
LDA has better theoretical explanation, and its empirical results are in general better than LSI’s
| 1 |
1,425 | 15,125 |
Computer Science
|
master
|
Which of the following is true?
|
[
"High precision implies low recall",
"High precision hurts recall",
"High recall hurts precision",
"High recall implies low precisions"
] |
High precision hurts recall
| 1 |
1,426 | 15,125 |
Computer Science
|
master
|
Maintaining the order of document identifiers for vocabulary construction when partitioning the document collection is important
|
[
"in the index merging approach for single node machines",
"in the map-reduce approach for parallel clusters",
"in both",
"in neither of the two"
] |
in the index merging approach for single node machines
| 0 |
1,427 | 15,125 |
Computer Science
|
master
|
Which of the following is correct regarding Crowdsourcing?
|
[
"Random Spammers give always the same answer for every question",
"It is applicable only for binary classification problems",
"Honey Pot discovers all the types of spammers but not the sloppy workers",
"The output of Majority Decision can be equal to the one of Expectation-Maximization"
] |
The output of Majority Decision can be equal to the one of Expectation-Maximization
| 3 |
1,428 | 15,125 |
Computer Science
|
master
|
When computing PageRank iteratively, the computation ends when...
|
[
"The difference among the eigenvalues of two subsequent iterations falls below a predefined threshold",
"The norm of the difference of rank vectors of two subsequent iterations falls below a predefined threshold",
"All nodes of the graph have been visited at least once",
"The probability of visiting an unseen node falls below a predefined threshold"
] |
The norm of the difference of rank vectors of two subsequent iterations falls below a predefined threshold
| 1 |
1,429 | 15,125 |
Computer Science
|
master
|
TransE is known to have difficulties in representing symmetric relationships r. Which of the following statements is correct for a symmetric relationship and provides insight for this problem?
|
[
"For all e1 , e2: \\( f(e_1, r, e_2) = f(e_2, r, e_1) \\)",
"For all e1 , e2: \\( f(e_1, r, e_2) = -f(e_2, r, e_1) \\)",
"\\( \\Sigma_{ e_1, e_2} f(e_1, r, e_2) + f(e_2, r, e_1) \\) is minimized if the embedding vector of r is large",
"\\( \\Sigma_{ e_1, e_2} f(e_1, r, e_2) + f(e_2, r, e_1) \\) is minimized if the embedding vectors of e1and e2 are close to each other"
] |
\( \Sigma_{ e_1, e_2} f(e_1, r, e_2) + f(e_2, r, e_1) \) is minimized if the embedding vectors of e1and e2 are close to each other
| 3 |
1,430 | 15,125 |
Computer Science
|
master
|
How does LSI querying work?
|
[
"The query vector is treated as an additional term; then cosine similarity is computed",
"The query vector is transformed by Matrix S; then cosine similarity is computed",
"The query vector is treated as an additional document; then cosine similarity is computed",
"The query vector is multiplied with an orthonormal matrix; then cosine similarity is computed"
] |
The query vector is treated as an additional document; then cosine similarity is computed
| 2 |
1,433 | 15,125 |
Computer Science
|
master
|
Suppose that an item in a leaf node N exists in every path. Which one is correct?
|
[
"N co-occurs with its prefix in every transaction.",
"For every node P that is a parent of N in the fp tree, confidence(P->N) = 1",
"N’s minimum possible support is equal to the number of paths.",
"The item N exists in every candidate set."
] |
N’s minimum possible support is equal to the number of paths.
| 2 |
1,434 | 15,125 |
Computer Science
|
master
|
In a Ranked Retrieval result, the result at position k is non-relevant and at k+1 is relevant. Which of the following is always true (P@k and R@k are the precision and recall of the result set consisting of the k top ranked documents)?
|
[
"P@k-1 > P@k+1",
"P@k-1 = P@k+1",
"R@k-1 < R@k+",
"R@k-1 = R@k+1"
] |
R@k-1 < R@k+
| 2 |
1,435 | 15,125 |
Computer Science
|
master
|
Semi-structured data
|
[
"is always schema-less",
"always embeds schema information into the data",
"must always be hierarchically structured",
"can never be indexed"
] |
always embeds schema information into the data
| 1 |
1,436 | 15,125 |
Computer Science
|
master
|
How many among the listed classifiers can be used to derive probability estimate of the class label?
1NN, kNN, Rocchio, NB, fasttext
|
[
"1",
"2",
"3",
"4"
] |
3
| 2 |
1,438 | 15,125 |
Computer Science
|
master
|
Given the following list of transactions: {apple,milk}, {milk, bread}, {apple, bread, milk}, {bread}, which of the following is correct?
|
[
"milk → apple has support ½ and confidence 1",
"milk → bread has support ½ and confidence 1",
"bread → milk has support ½ and confidence 1",
"apple → milk has support ½ and confidence 1"
] |
apple → milk has support ½ and confidence 1
| 3 |
1,439 | 15,125 |
Computer Science
|
master
|
For the number of times the apriori algorithm and the FPgrowth algorithm for association rule mining are scanning the transaction database the following is true
|
[
"fpgrowth has always strictly fewer scans than apriori",
"fpgrowth and apriori can have the same number of scans",
"apriori cannot have fewer scans than fpgrowth",
"all three above statements are false"
] |
fpgrowth and apriori can have the same number of scans
| 1 |
1,441 | 15,125 |
Computer Science
|
master
|
Given the following teleporting matrix (Ε) for nodes A, B and C:[0 ½ 0][0 0 0][0 ½ 1]and making no assumptions about the link matrix (R), which of the following is correct:(Reminder: columns are the probabilities to leave the respective node.)
|
[
"A random walker can never reach node A",
"A random walker can never leave node A",
"A random walker can always leave node C",
"A random walker can always leave node B"
] |
A random walker can always leave node B
| 3 |
1,442 | 15,125 |
Computer Science
|
master
|
Suppose that an item in a leaf node N exists in every path. Which one is correct?
|
[
"N co-occurs with its prefix in every transaction.",
"For every node p that is a parent of N in the fp tree, confidence(p->n) = 1 c.",
"N’s minimum possible support is equal to the number of paths.",
"The item N exists in every candidate set."
] |
N’s minimum possible support is equal to the number of paths.
| 2 |
1,443 | 15,125 |
Computer Science
|
master
|
What is the support of the itemset {beer, chocolate} and the confidence of the rule {chocolate} → {beer} in the dataset below?TID: Items BoughtT1: milk, butter, beerT2: milk, diaper, beer, eggsT3: butter, diaper, beer, chocolate
T4: milk, butter, diaper, beerT5: milk, butter, diaper, chocolate
|
[
"0.2/0.25",
"0.4/0.5",
"0.2/0.5",
"0.4/0.25\n\n\n\n"
] |
0.2/0.5
| 2 |
1,444 | 15,125 |
Computer Science
|
master
|
Which of the following methods does not exploit statistics on the co-occurrence of words in a text?
|
[
"Word embeddings\n\n\n",
"Transformers\n\n\n",
"Vector space retrieval\n\n\n",
"Fasttext"
] |
Vector space retrieval
| 2 |
1,445 | 15,125 |
Computer Science
|
master
|
Which of the following is true regarding inverted files?
|
[
"The space requirement for the postings file is O(nβ), where β is generally between 0.4 and 0.6",
"Varying length compression is used to reduce the size of the index file",
"Inverted files prioritize efficiency on insertion over efficiency on search",
"Storing differences among word addresses reduces the size of the postings file"
] |
Storing differences among word addresses reduces the size of the postings file
| 3 |
1,446 | 15,125 |
Computer Science
|
master
|
The loss function is minimized
|
[
"By modifying the word embedding vectors",
"By changing the sampling strategy for negative samples",
"By carefully choosing the positive samples",
"By sampling non-frequent word-context pairs more frequently"
] |
By modifying the word embedding vectors
| 0 |
1,447 | 15,125 |
Computer Science
|
master
|
Fundamentally, why clustering is considered an unsupervised machine learning technique?
|
[
"Number of clusters are not known.",
"The class labels are not known.",
"The features are not known.",
"The clusters can be different with different initial parameters."
] |
The class labels are not known.
| 1 |
1,449 | 15,125 |
Computer Science
|
master
|
Which attribute gives the best split?A1PNa44b44A2PNx51y33A3PNt61j23
|
[
"A1",
"A3",
"A2",
"All the same"
] |
A3
| 1 |
1,450 | 15,125 |
Computer Science
|
master
|
Suppose that q is density reachable from p. The chain of points that ensure this relationship are {t,u,g,r} Which one is FALSE?
|
[
"{t,u,g,r} have to be all core points.",
"p and q will also be density-connected",
"p has to be a core point",
"q has to be a border point"
] |
q has to be a border point
| 3 |
1,451 | 15,125 |
Computer Science
|
master
|
In User-Based Collaborative Filtering, which of the following is correct, assuming that all the ratings are positive?
|
[
"Pearson Correlation Coefficient and Cosine Similarity have different value range, but return the same similarity ranking for the users",
"If the ratings of two users have both variance equal to 0, then their Cosine Similarity is maximized",
"Pearson Correlation Coefficient and Cosine Similarity have the same value range, but can return different similarity ranking for the users",
"If the variance of the ratings of one of the users is 0, then their Cosine Similarity is not computable"
] |
If the ratings of two users have both variance equal to 0, then their Cosine Similarity is maximized
| 1 |
1,452 | 15,125 |
Computer Science
|
master
|
The term frequency of a term is normalized
|
[
"by the maximal frequency of all terms in the document",
"by the maximal frequency of the term in the document collection",
"by the maximal frequency of any term in the vocabulary",
"by the maximal term frequency of any document in the collection"
] |
by the maximal frequency of all terms in the document
| 0 |
1,453 | 15,125 |
Computer Science
|
master
|
Which of the following statements on Latent Semantic Indexing (LSI) and Word Embeddings (WE) is false?
|
[
"LSI is deterministic (given the dimension), whereas WE is not",
"LSI does not depend on the order of words in the document, whereas WE does",
"The dimensions of LSI can be interpreted as concepts, whereas those of WE cannot",
"LSI does take into account the frequency of words in the documents, whereas WE with negative sampling does not"
] |
LSI does take into account the frequency of words in the documents, whereas WE with negative sampling does not
| 3 |
1,457 | 15,125 |
Computer Science
|
master
|
Tugrulcan wanted to plan his next summer vacation so he wrote “best beaches” to his favourite search engine. Little did he know, his favourite search engine was using pseudo-relevance feedback and the top-k documents that are considered relevant were about the beaches only in Turkey. What is this phenomenon called?
|
[
"Query Bias",
"Query Confounding",
"Query Drift",
"Query Malfunction"
] |
Query Drift
| 2 |
1,458 | 15,125 |
Computer Science
|
master
|
When compressing the adjacency list of a given URL, a reference list
|
[
"Is chosen from neighboring URLs that can be reached in a small number of hops",
"May contain URLs not occurring in the adjacency list of the given URL",
"Lists all URLs not contained in the adjacency list of given URL",
"All of the above"
] |
May contain URLs not occurring in the adjacency list of the given URL
| 1 |
1,461 | 15,125 |
Computer Science
|
master
|
Data being classified as unstructured or structured depends on the:
|
[
"Degree of abstraction",
"Level of human involvement",
"Type of physical storage",
"Amount of data "
] |
Degree of abstraction
| 0 |
1,463 | 15,125 |
Computer Science
|
master
|
Suppose you have a search engine that retrieves the top 100 documents and
achieves 90% precision and 20% recall. You modify the search engine to
retrieve the top 200 and mysteriously, the precision stays the same. Which one
is CORRECT?
|
[
"The recall becomes 10%",
"The number of relevant documents is 450",
"The F-score stays the same",
"This is not possible"
] |
The number of relevant documents is 450
| 1 |
1,464 | 15,125 |
Computer Science
|
master
|
Which of the following is true for community detection in social graphs?
|
[
"The Louvain algorithm always creates a hierarchy of communities with a common root.",
"The Louvain algorithm is efficient for small networks, while the Girvan-Newman algorithm is efficient for large networks.",
"If n cliques of the same order are connected cyclically with n edges, then the Louvain algorithm will always detect the same communities, independently of the order of processing of the nodes.",
"The result of the Girvan-Newman algorithm can depend on the order of processing of nodes whereas for the Louvain algorithm this is not the case."
] |
If n cliques of the same order are connected cyclically with n edges, then the Louvain algorithm will always detect the same communities, independently of the order of processing of the nodes.
| 2 |
1,465 | 15,125 |
Computer Science
|
master
|
In the χ2 statistics for a binary feature, we obtain P(χ2 | DF = 1) > 0.05. This means in this case, it is assumed:
|
[
"That the class labels depends on the feature",
"That the class label is independent of the feature",
"That the class label correlates with the feature",
"None of the above"
] |
That the class label is independent of the feature
| 1 |
1,467 | 15,125 |
Computer Science
|
master
|
Which of the following is correct regarding the use of Hidden Markov Models (HMMs) for entity recognition in text documents?
|
[
"The cost of learning the model is quadratic in the lengths of the text.",
"The cost of predicting a word is linear in the lengths of the text preceding the word.",
"An HMM model can be built using words enhanced with morphological features as input.",
"The label of one word is predicted based on all the previous labels"
] |
An HMM model can be built using words enhanced with morphological features as input.
| 2 |
1,468 | 15,125 |
Computer Science
|
master
|
10 itemsets out of 100 contain item A, of which 5 also contain B. The rule A -> B has:
|
[
"5% support and 10% confidence",
"10% support and 50% confidence",
"5% support and 50% confidence",
"10% support and 10% confidence"
] |
5% support and 50% confidence
| 2 |
1,469 | 15,125 |
Computer Science
|
master
|
Which of the following is correct regarding the use of Hidden Markov Models (HMMs) for entity recognition in text documents?
|
[
"HMMs cannot predict the label of a word that appears only in the test set",
"If the smoothing parameter λ is equal to 1, the emission probabilities for all the words in the test set will be equal",
"When computing the emission probabilities, a word can be replaced by a morphological feature (e.g., the number of uppercase first characters)",
"The label of one word is predicted based on all the previous labels"
] |
When computing the emission probabilities, a word can be replaced by a morphological feature (e.g., the number of uppercase first characters)
| 2 |
1,470 | 15,125 |
Computer Science
|
master
|
A basic statement in RDF would be expressed in the relational data model by a table
|
[
"with one attribute",
"with two attributes",
"with three attributes",
"cannot be expressed in the relational data model"
] |
with two attributes
| 1 |
1,471 | 15,125 |
Computer Science
|
master
|
Which of the following statements is wrong regarding RDF?
|
[
"An RDF statement would be expressed in SQL as a tuple in a table",
"Blank nodes in RDF graphs correspond to the special value NULL in SQL",
"The object value of a type statement corresponds to a table name in SQL",
"RDF graphs can be encoded as SQL databases"
] |
Blank nodes in RDF graphs correspond to the special value NULL in SQL
| 1 |
1,472 | 15,125 |
Computer Science
|
master
|
The number of non-zero entries in a column of a term-document matrix indicates:
|
[
"how many terms of the vocabulary a document contains",
"how often a term of the vocabulary occurs in a document",
"how relevant a term is for a document ",
"none of the other responses is correct"
] |
how many terms of the vocabulary a document contains
| 0 |
1,473 | 15,125 |
Computer Science
|
master
|
If t has no Hypernym
|
[
"It is a root concept",
"It cannot match c such as t and X",
"It is identical to the initial root concept",
"It is a basic concept"
] |
It is a root concept
| 0 |
1,474 | 15,125 |
Computer Science
|
master
|
Which of the following is true?
|
[
"Exploiting locality with gap encoding may increase the size of an adjacency list",
"Exploiting similarity with reference lists may increase the size of an adjacency list",
"Both of the above is true",
"None of the above is true"
] |
Exploiting locality with gap encoding may increase the size of an adjacency list
| 0 |
1,475 | 15,125 |
Computer Science
|
master
|
What is TRUE regarding Fagin's algorithm?
|
[
"Posting files need to be indexed by TF-IDF weights",
"It performs a complete scan over the posting files",
"It never reads more than (kn)1⁄2 entries from a posting list",
"It provably returns the k documents with the largest aggregate scores"
] |
It provably returns the k documents with the largest aggregate scores
| 3 |
1,476 | 15,125 |
Computer Science
|
master
|
A false negative in sampling can only occur for itemsets with support smaller than
|
[
"the threshold s",
"p*s",
"p*m",
"None of the above"
] |
None of the above
| 3 |
1,477 | 15,125 |
Computer Science
|
master
|
Why is XML a document model?
|
[
"It supports application-specific markup",
"It supports domain-specific schemas",
"It has a serialized representation",
"It uses HTML tags"
] |
It has a serialized representation
| 2 |
1,478 | 15,125 |
Computer Science
|
master
|
What is TRUE regarding the Multi-head Self-attention mechanism?
|
[
"Its computation cannot be parallelized compared to LSTMs and other sequential models.",
"It gives the Transformer the ability to learn different aspects of the meanings of each word.",
"LSTMs have larger memory than models with self-attention.",
"Its complexity is linear to the input size."
] |
It gives the Transformer the ability to learn different aspects of the meanings of each word.
| 1 |
1,481 | 15,125 |
Computer Science
|
master
|
Suppose you have a search engine that retrieves the top 100 documents and achieves 90% precision and 20% recall. You modify the search engine to retrieve the top 200, and mysteriously, the precision stays the same. Which one is correct?
|
[
"The recall becomes 10%",
"The number of relevant documents is 450",
"The F-score stays the same",
"This is not possible"
] |
The number of relevant documents is 450
| 1 |
1,482 | 15,125 |
Computer Science
|
master
|
A retrieval model attempts to capture
|
[
"the interface by which a user is accessing information",
"the importance a user gives to a piece of information for a query",
"the formal correctness of a query formulation by user",
"the structure by which a document is organised"
] |
the importance a user gives to a piece of information for a query
| 1 |
1,485 | 15,125 |
Computer Science
|
master
|
When computing HITS, the initial values
|
[
"Are set all to 1",
"Are set all to 1/n",
"Are set all to 1/sqrt(n)",
"Are chosen randomly"
] |
Are set all to 1/sqrt(n)
| 2 |
1,486 | 15,125 |
Computer Science
|
master
|
Which of the following is correct regarding schemas and ontologies?
|
[
" An ontology is created from constructing mappings between schemas",
"Ontologies can be used for reasoning about different schemas",
"Ontologies always require a schema",
"Semi-structured data cannot have a schema"
] |
Ontologies can be used for reasoning about different schemas
| 1 |
1,488 | 15,125 |
Computer Science
|
master
|
Given the 2-itemsets {1,2}, {1,5}, {2,5}, {1,4}, {1,3}, when generating the 3-itemsets we will:
|
[
"Generate 5 3-itemsets after the join and 2 3-itemsets after the prune",
"Generate 6 3-itemsets after the join and 1 3-itemsets after the prune",
"Generate 4 3-itemsets after the join and 1 3-itemsets after the prune",
"Generate 4 3-itemsets after the join and 2 3-itemsets after the prune"
] |
Generate 6 3-itemsets after the join and 1 3-itemsets after the prune
| 1 |
1,490 | 15,125 |
Computer Science
|
master
|
When indexing a document collection using an inverted file, the main space requirement is implied by
|
[
"The access structure",
"The vocabulary",
"The index file",
"The postings file"
] |
The postings file
| 3 |
1,492 | 15,125 |
Computer Science
|
master
|
Which of the following is correct regarding prediction models?
|
[
"A high bias is a sign of overfitting.",
"A high variance is a sign of underfitting.",
"In low data regime, complex models tend to perform better.",
"Simple models have higher bias than complex models."
] |
Simple models have higher bias than complex models.
| 3 |
1,493 | 15,125 |
Computer Science
|
master
|
For a user that has not done any ratings, which method can make a prediction?
|
[
"User-based collaborative RS",
"Item-based collaborative RS",
"Content-based RS",
"None of the above"
] |
None of the above
| 3 |
1,495 | 15,125 |
Computer Science
|
master
|
Which statement is correct?
|
[
"The Viterbi algorithm works because words are independent in a sentence",
"The Viterbi algorithm works because it is applied to an HMM model that makes an independence assumption on the word dependencies in sentences",
"The Viterbi algorithm works because it makes an independence assumption on the word dependencies in sentences",
"The Viterbi algorithm works because it is applied to an HMM model that captures independence of words in a sentence"
] |
The Viterbi algorithm works because it is applied to an HMM model that makes an independence assumption on the word dependencies in sentences
| 1 |
1,497 | 15,125 |
Computer Science
|
master
|
Recall can be defined as:
|
[
"P(relevant documents | retrieved documents)",
"P(retrieved documents relevant documents)",
"P(retrieved documents number of documents)",
"P(relevant documents number of documents)"
] |
P(retrieved documents relevant documents)
| 1 |
1,498 | 15,125 |
Computer Science
|
master
|
Which of the following is WRONG about inverted files? (Slide 24,28 Week 3)
|
[
"The space requirement for the postings file is O(n)",
"Variable length compression is used to reduce the size of the index file",
"The index file has space requirement of O(n^beta), where beta is about 1⁄2",
"Storing differences among word addresses reduces the size of the postings file"
] |
Variable length compression is used to reduce the size of the index file
| 1 |
1,499 | 15,125 |
Computer Science
|
master
|
Information extraction:
|
[
"Necessarily requires training data.",
"Is used to identify characteristic entities in a document.",
"Is always bootstrapped by using ontologies.",
"Can be used to populate ontologies."
] |
Can be used to populate ontologies.
| 3 |
1,500 | 15,125 |
Computer Science
|
master
|
Which statement is true?
|
[
"Random forests tend to easily overfit",
"Decision trees are robust against small perturbations in the data",
"Random forests are hard to parallelize",
"Decision trees are linear models"
] |
Random forests tend to easily overfit
| 0 |
1,501 | 15,125 |
Computer Science
|
master
|
In User-Based Collaborative Filtering, which of the following is TRUE?
|
[
"Pearson Correlation Coefficient and Cosine Similarity have the same value range and return the same similarity ranking for the users.",
"Pearson Correlation Coefficient and Cosine Similarity have different value ranges and can return different similarity rankings for the users",
"Pearson Correlation Coefficient and Cosine Similarity have different value ranges, but return the same similarity ranking for the users",
"Pearson Correlation Coefficient and Cosine Similarity have the same value range but can return different similarity rankings for the users"
] |
Pearson Correlation Coefficient and Cosine Similarity have different value ranges and can return different similarity rankings for the users
| 1 |
1,502 | 15,100 |
Life Sciences Engineering
|
online
|
Even for constant firing rates, the input will fluctuate around the mean input calculated above. Assume that the weights scale as [mathjaxinline] w_0 \propto 1/N[/mathjaxinline].
|
[
"The expected input scales as [mathjaxinline] \\overline{I} - I^{\\textrm{ext}} \\propto N [/mathjaxinline]. Its fluctations as [mathjaxinline]~ \\textrm{std}\\left(I_i(t) - I^{\\textrm{ext}}\\right)\\propto N^2[/mathjaxinline]",
"The expected input scales as [mathjaxinline] \\overline{I} - I^{\\textrm{ext}} \\propto const [/mathjaxinline]. Its fluctations as [mathjaxinline]~ \\textrm{std}\\left(I_i(t) - I^{\\textrm{ext}}\\right)\\propto 1/N[/mathjaxinline]",
"The expected input scales as [mathjaxinline] \\overline{I} - I^{\\textrm{ext}}\\propto const [/mathjaxinline]. Its fluctations as [mathjaxinline]~ \\textrm{std}\\left(I_i(t) - I^{\\textrm{ext}}\\right)\\propto 1/\\sqrt{N}[/mathjaxinline]",
"The expected input scales as [mathjaxinline] \\overline{I} - I^{\\textrm{ext}} \\propto const [/mathjaxinline]. Its fluctations as [mathjaxinline]~ \\textrm{std}\\left(I_i(t) - I^{\\textrm{ext}}\\right)\\propto const[/mathjaxinline]"
] |
The expected input scales as [mathjaxinline] \overline{I} - I^{\textrm{ext}}\propto const [/mathjaxinline]. Its fluctations as [mathjaxinline]~ \textrm{std}\left(I_i(t) - I^{\textrm{ext}}\right)\propto 1/\sqrt{N}[/mathjaxinline]
| 2 |
1,503 | 15,043 |
Life Sciences Engineering
|
online
|
Moving through V2, V4, the posterior inferior temporal (IT) cortex and the anterior IT cortex takes one further along the ventral stream away from V1. Which of these area is likely to have neurons tuned for the most complex shapes?
|
[
"V4",
"Posterior IT",
"V2",
"Anterior IT"
] |
Anterior IT
| 3 |
1,504 | 15,043 |
Life Sciences Engineering
|
online
|
How is an input implemented in the model?
|
[
"An axon from the primary visual cortex was added to the microcircuit based on biological data on synapse density",
"A predetermined number of neurons in the microcircuit were activated to simulate an external input",
"A thalamic innervation was added to the microcircuit based on biological data on synapse density",
"All synapses present in one microcolumn were matched to different single neurons situated in the hypothetical input region"
] |
A thalamic innervation was added to the microcircuit based on biological data on synapse density
| 2 |
1,505 | 15,043 |
Life Sciences Engineering
|
online
|
In which case do you need optimization algorithm to construct a data-driven model?
|
[
"When dealing with long-tail data",
"When the data is sparse",
"When the data used is at a higher level than the model",
"When the data used is at the same level than the model"
] |
When the data used is at a higher level than the model
| 2 |
1,506 | 15,043 |
Life Sciences Engineering
|
online
|
What type of stimuli allows the best predictions of the response of a cell in the primary visual cortex to a broad range of stimuli?
|
[
"Short bars",
"Natural Images",
"White noise",
"All stimuli allow equally accurate predictions"
] |
Natural Images
| 1 |
1,507 | 15,043 |
Life Sciences Engineering
|
online
|
What is the order of magnitude of a large-scale dataset in neuroscience?
|
[
"8 GB",
"100 GB",
"8 TB",
"1 PB"
] |
8 TB
| 2 |
1,508 | 15,043 |
Life Sciences Engineering
|
online
|
Which assertions concerning the suppression signal are true?
|
[
"It is slower than the original waves",
"It has the same speed than the original waves",
"It can only be observed with spontaneous activity",
"It is always present when waves collide"
] |
It has the same speed than the original waves
| 1 |
1,509 | 15,043 |
Life Sciences Engineering
|
online
|
What is the relation between running speed and cell activity in the presence of any random visual stimulus?
|
[
"Cell activity increases with running speed",
"Cell activity decreases with running speed",
"Depending of the running speed, the activity can be enhanced or suppressed",
"It differs between cells and can be any of the above"
] |
It differs between cells and can be any of the above
| 3 |
1,510 | 15,043 |
Life Sciences Engineering
|
online
|
What happens when two waves collide?
|
[
"They merge and go on as the sum of the two original waves",
"They merge and go on weaker than the sum of the two original waves",
"They merge and go on with the amplitude of the strongest of the two original waves",
"They cancel each other out"
] |
They merge and go on weaker than the sum of the two original waves
| 1 |
1,511 | 15,043 |
Life Sciences Engineering
|
online
|
Why are whole cell preps not ideal for cell type characterization in adult human brain tissue?
|
[
"Enzymatic methods generate cellular debris that hinder cell dissociation and compromise prep quality",
"The variety of enzymes used for cell dissociation impacts the health and type of cells recovered in the final prep",
"The recovery of cells is biased towards glial cells",
"All of the above"
] |
All of the above
| 3 |
1,512 | 15,043 |
Life Sciences Engineering
|
online
|
According to the model, what causes the suppression effect when waves collide?
|
[
"The spatially restrained connectivity of inhibitory cells",
"The conductance shunting the cells in response to a high input regime",
"The model does not reproduce the suppression effect",
"The greater response of inhibitory cells than of excitatory cells to the same input"
] |
The conductance shunting the cells in response to a high input regime
| 1 |
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