id stringlengths 1 4 | question stringlengths 6 1.87k | context listlengths 5 5 | choices listlengths 2 18 | answer stringlengths 1 840 |
|---|---|---|---|---|
5 | Which of the following scheduler policies are preemptive? | [
"Fixed-priority preemptive scheduling is a scheduling system commonly used in real-time systems. With fixed priority preemptive scheduling, the scheduler ensures that at any given time, the processor executes the highest priority task of all those tasks that are currently ready to execute. The preemptive scheduler ... | [
"FIFO (First In, First Out)",
"SJF (Shortest Job First)",
"STCF (Shortest Time to Completion First)",
"RR (Round Robin)"
] | ['STCF (Shortest Time to Completion First)', 'RR (Round Robin)'] |
6 | Which of the following are correct implementation for acquire function ? Assume 0 means UNLOCKED and 1 means LOCKED. Initially l->locked = 0. | [
"is in the lexical scope of the anonymous function. Higher-order funcMons • Functions that operate on other functions, either by taking them as arguments or by returning them, are called higher-order functions. function myFunc() { const anotherFunc = function() { console.log(\"inner\"); } return anotherFunc; } cons... | [
"c \n void acquire(struct lock *l)\n {\n for(;;)\n if(xchg(&l->locked, 1) == 0)\n return;\n }",
"c \n void acquire(struct lock *l)\n {\n if(cas(&l->locked, 0, 1) == 0)\n return;\n }",
"c \n void acquire(struct lock *l)\n {\n for(;;)\n if(cas(&l->locked, 1... | ['c \n void acquire(struct lock *l)\n {\n for(;;)\n if(xchg(&l->locked, 1) == 0)\n return;\n }'] |
11 | In which of the following cases does JOS acquire the big kernel lock? | [
"@1ntext Persa Now, suppose Persa is a packet switch that forwards Alice’s traffic to Bob. Suppose Persa *modifies* the {plaintext, ciphertext} pair sent by Alice. But because Persa does not know *Alice’s private key*, she cannot produce a “consistent” pair: when Bob decrypts [click] Persa’s ciphertext he will not ... | [
"Processor traps in user mode",
"Processor traps in kernel mode",
"Switching from kernel mode to user mode",
"Initialization of application processor"
] | ['Processor traps in user mode', 'Initialization of application processor'] |
15 | In an x86 multiprocessor with JOS, how many Bootstrap Processors (BSP) is it possible to have at most? And how many Application Processors (AP) at most? | [
"use since 1981 when Hunter & Ready, the developers of the Versatile Real-Time Executive (VRTX), first coined the term to describe the hardware-dependent software needed to run VRTX on a specific hardware platform. Since the 1980s, it has been in wide use throughout the industry. Virtually all RTOS providers now us... | [
"BSP: 0, AP: 4",
"BSP: 1, AP: 4",
"BSP: 2, AP: 4",
"BSP: 0, AP: infinite",
"BSP: 1, AP: infinite",
"BSP: 2, AP: infinite"
] | ['BSP: 1, AP: infinite'] |
20 | Assume a user program executes following tasks. Select all options that will use a system call. | [
"The operating system takes control L03.3: System calls CS202 - Computer Systems Lectures slides adapted from the OS courses from Cornell, EPFL, IITB, UCB, UMASS, and UU Question How can a process request (from the OS) for operations that are only possible in the kernel mode (example: IO requests)? 25 26 Requesting... | [
"Read the user's input \"Hello world\" from the keyboard.",
"Write \"Hello world\" to a file.",
"Encrypt \"Hello world\" by AES.",
"Send \"Hello world\" to another machine via Network Interface Card."
] | ['Read the user\'s input "Hello world" from the keyboard.', 'Write "Hello world" to a file.', 'Send "Hello world" to another machine via Network Interface Card.'] |
22 | What is the content of the inode? | [
"ed to the file by the file system Note Inodes are unique for a file system but not globally Recycled after deletion An inode contains metadata of a file Permissions length access time Location of data block and indirection block Each file ha exactly one associated inode OS view Inode persistent ID Storage space is... | [
"Filename",
"File mode",
"Hard links counter",
"String with the name of the owner",
"File size",
"Capacity of the whole file system",
"Index structure for data blocks"
] | ['File mode', 'Hard links counter', 'File size', 'Index structure for data blocks'] |
23 | In x86, what are the possible ways to transfer arguments when invoking a system call? For example, in the following code, string and len are sys_cputs’s arguments. | [
"a letter through the postal system, you have to follow certain rules. - You need to put your letter in an envelope and write a correct address on a particular part of the envelope. - You need to drop your letter in a mailbox. These rules are the “interface” between you and the postal system -- your only way of usi... | [
"Stack",
"Registers",
"Instructions"
] | ['Stack', 'Registers'] |
26 | What is the worst case complexity of listing files in a directory? The file system implements directories as hash-tables. | [
"In computer science, a hash list is typically a list of hashes of the data blocks in a file or set of files. Lists of hashes are used for many different purposes, such as fast table lookup (hash tables) and distributed databases (distributed hash tables). A hash list is an extension of the concept of hashing an it... | [
"$O(1)$",
"$O(number of direntries in the directory)$",
"$O(size of the file system)$",
"$O(number of direntries in the file system)$",
"$O(log(number of direntries in the directory))$"
] | ['$O(number of direntries in the directory)$'] |
40 | In JOS, suppose one Env sends a page to another Env. Is the page copied? | [
"tag probability e pronunciation b oa r d z etc set of record identi ed by a reference e g a database with primary key Words Tokens Introduction Words Tokens Lexicon N gram Conclusion c EPFL J C Chappelier Field representation External v Internal structure i e serialization v memory representation Internal structur... | [
"Yes",
"No"
] | ['No'] |
41 | In JOS and x86, please select all valid options for a system call. | [
"extra wv2 x2x xalan-java xbill xbitmaps xcb-proto xclip xerces2-java xf86-input-acecad xf86-input-aiptek xf86-input-joystick xf86-input-keyboard xf86-input-mouse xf86-input-synaptics xf86-input-vmmouse xf86-input-void xf86-video-apm xf86-video-ark xf86-video-ast xf86-video-chips xf86-video-cirrus xf86-video-dummy ... | [
"A system call is for handling interrupts like dividing zero error and page fault.",
"In user mode, before and after a system call instruction(such as int 0x30), the stack pointer(esp in x86) stays the same.",
"During the execution of a system call, when transfering from user mode to kernel mode, the stack poin... | ['In user mode, before and after a system call instruction(such as int 0x30), the stack pointer(esp in x86) stays the same.'] |
44 | What are the drawbacks of non-preemptive scheduling compared to preemptive scheduling? | [
"Run-to-completion scheduling or nonpreemptive scheduling is a scheduling model in which each task runs until it either finishes, or explicitly yields control back to the scheduler. Run-to-completion systems typically have an event queue which is serviced either in strict order of admission by an event loop, or by ... | [
"It can lead to starvation especially for those real-time tasks",
"Less computational resources need for scheduling and takes shorted time to suspend the running task and switch the context.",
"Bugs in one process can cause a machine to freeze up",
"It can lead to poor response time for processes"
] | ['It can lead to starvation especially for those real-time tasks', 'Bugs in one process can cause a machine to freeze up', 'It can lead to poor response time for processes'] |
45 | Select valid answers about file descriptors (FD): | [
"\"Everything is a file\" is an approach to interface design in Unix derivatives. While this turn of phrase does not as such figure as a Unix design principle or philosophy, it is a common way to analyse designs, and informs the design of new interfaces in a way that prefers, in rough order of import: representing ... | [
"The value of FD is unique for every file in the operating system.",
"FD is usually used as an argument for read and write.",
"FD is constructed by hashing the filename.",
"FDs are preserved after fork() and can be used in the new process pointing to the original files."
] | ['FD is usually used as an argument for read and write.', 'FDs are preserved after fork() and can be used in the new process pointing to the original files.'] |
46 | What is the default block size for a traditional file system, e.g. ext3/4? | [
"the meaning of the standard metric terms. Rather than based on powers of 1000, these are based on powers of 1024 which is a power of 2. The JEDEC memory standard JESD88F notes that the definitions of kilo (K), giga (G), and mega (M) based on powers of two are included only to reflect common usage, but are otherwis... | [
"32 bits",
"32 bytes",
"512 bits",
"512 bytes",
"4096 bits",
"4096 bytes"
] | ['4096 bytes'] |
47 | Suppose a file system used only for reading immutable files in random fashion. What is the best block allocation strategy? | [
"at the beginning of the partition Data blocks Data blocks Data blocks Data blocks Data blocks Data blocks Inodes Free lists • One logical superblock per file system • Stores the metadata about the file system • Number of inodes • Number of data blocks • Where the inode table begins • May contain information to man... | [
"Linked-list allocation",
"Continuous allocation",
"Index allocation with B-tree",
"Index allocation with Hash-table"
] | ['Continuous allocation'] |
50 | Which of the following operations would switch the user program from user space to kernel space? | [
"'s basic functions, such as scheduling processes and controlling peripherals. In the 1950s, the programmer, who was also the operator, would write a program and run it. After the program finished executing, the output may have been printed, or it may have been punched onto paper tape or cards for later processing.... | [
"Dividing integer by 0.",
"Calling sin() in math library.",
"Invoking read() syscall.",
"Jumping to an invalid address."
] | ['Dividing integer by 0.', 'Invoking read() syscall.', 'Jumping to an invalid address.'] |
61 | Which flag prevents user programs from reading and writing kernel data? | [
"s was done without Institutional Review Board (IRB) approval. Despite undergoing review by the conference, this breach of ethical responsibilities was not detected during the paper's review process. This incident sparked criticism from the Linux community and the broader cybersecurity community. Greg Kroah-Hartman... | [
"PTE_P",
"PTE_U",
"PTE_D",
"PTE_W"
] | ['PTE_U'] |
62 | In JOS, after finishing the execution of a user-level page fault handler, how is the program control flow transferred back to the program? (You may get insights from the code snippet of _pagefault_upcall.) | [
"s call downwards, i.e., from application components to those closer to the hardware, while events call upwards. Certain primitive events are bound to hardware interrupts. Components are statically linked to each other via their interfaces. This increases runtime efficiency, encourages robust design, and allows for... | [
"The control flow will be transferred to kernel first, then to Env that caused the page fault.",
"The control flow will be transferred to Env that caused the page fault directly."
] | ['The control flow will be transferred to Env that caused the page fault directly.'] |
64 | What is the content of the superblock in the JOS file system? | [
"JEAN was a dialect of the JOSS programming language developed for and used on ICT 1900 series computers in the late 1960s and early 1970s; it was implemented under the MINIMOP operating system. It was used at universities including the University of Southampton. The name was an acronym derived from \"JOSS Extended... | [
"List of all directories",
"List of all files",
"List of all blocks",
"List of all inodes",
"Total number of blocks on disk",
"Magic number identifying the file system",
"Node with the root directory ('/')"
] | ['Total number of blocks on disk', 'Magic number identifying the file system', "Node with the root directory ('/')"] |
69 | In which of the following cases does the TLB need to be flushed? | [
"walks” page table 49 Translation lookaside buffer (TLB) A cache of recent virtual address to physical address mappings Translating virtual address to physical address: 1. MMU first looks up TLB 2. If TLB hit: physical address can be directly used 3. Only if TLB miss: MMU “walks” page table • TLB misses are expensi... | [
"Inserting a new page into the page table for a user-space application.",
"Deleting a page from the page table.",
"Changing the read/write permission bit in the page table.",
"Inserting a new page into the page table for kernel."
] | ['Deleting a page from the page table.', 'Changing the read/write permission bit in the page table.'] |
71 | Select all valid answers about UNIX-like shell. | [
"le. As all subjects assigned to a role are the same to the system, the system does not have the means to see if there are one or two users to enforce the separation of privilege. Another option, instead of looking at similarity between users, is to look at of permissions that are often needed together to run the s... | [
"The shell is a program, that runs in user-space.",
"The shell is a program, that runs in kernel-space.",
"The shell is a program, which reads from standard input.",
"The shell is a function inside kernel.",
"The shell is the layer, which has to be always used for communicating with kernel.",
"The shell m... | ['The shell is a program, that runs in user-space.', 'The shell is a program, which reads from standard input.', 'The shell is a user interface for UNIX-like systems.'] |
74 | In x86, select all synchronous exceptions? | [
"Automatic mutual exclusion is a parallel computing programming paradigm in which threads are divided into atomic chunks, and the atomic execution of the chunks automatically parallelized using transactional memory. References See also Bulk synchronous parallel",
"synchronous\", serial link. If you have an extern... | [
"Divide error",
"Timer",
"Page Fault",
"Keyboard"
] | ['Divide error', 'Page Fault'] |
76 | Once paging is enabled, load instruction / CR3 register / Page Table entry uses Virtual or Physical address? | [
"3 to physical page 2 • Virtual page 0 to physical page 3 • Virtual page 2 to physical page 5 • Virtual page 1 to physical page 7 16 Page table stores the address-translation information Physical memory OS mem Unused Pg 3 (P1) Pg 0 (P1) 64 B 48 B 32 B 16 B 0 B Unused Pg 2 (P1) Unused Pg 1 (P1) 128 B 112 B 96 B 80 B... | [
"Physical / Physical / Physical",
"Physical / Physical / Virtual",
"Virtual / Physical / Physical",
"Virtual / Virtual / Virtual",
"Virtual / Virtual / Physical"
] | ['Virtual / Physical / Physical'] |
78 | Which of the execution of an application are possible on a single-core machine? | [
"machine with limitation CPUs execute an endless stream of instruction All system memory is a contiguous blob that can be accessed using load store instruction by CPUs The disk is a finite set of block Processor Memory Storage Hardware Program Infinite processor Infinite memory Storage manager Network manager Graph... | [
"Concurrent execution",
"Parallel execution",
"Both concurrent and parallel execution",
"Neither concurrent or parallel execution"
] | ['Concurrent execution'] |
79 | Which of the following lock acquisition orders (locks are acquired from left to right), for thread 1 (T1) and thread 2 (T2), will result in a deadlock ? Assume that A, B, C, D are lock instances. | [
"about locks mainly from a software perspective o What to lock, and when u In this lecture, we focus on how locks work and their interactions with hardware/OS o Ties back to cache coherence protocol u Because locks require communication... o Use memory locations to implement them! Focus on Implementation CS 307 – F... | [
"T1: A,B,C,D T2: A,B,C,D",
"T1: A,D,C,B T2: A,D,C,B",
"T1: A,B,C,D T2: D,C,B,A",
"T1: A,B,C,D T2: A,B,E,F",
"T1: A,B,C,D T2: E,B,A,F"
] | ['T1: A,B,C,D T2: D,C,B,A', 'T1: A,B,C,D T2: E,B,A,F'] |
81 | In an x86 multiprocessor system with JOS, select all the correct options. Assume every Env has a single thread. | [
"extra wv2 x2x xalan-java xbill xbitmaps xcb-proto xclip xerces2-java xf86-input-acecad xf86-input-aiptek xf86-input-joystick xf86-input-keyboard xf86-input-mouse xf86-input-synaptics xf86-input-vmmouse xf86-input-void xf86-video-apm xf86-video-ark xf86-video-ast xf86-video-chips xf86-video-cirrus xf86-video-dummy ... | [
"Two Envs could run on the same processor simultaneously.",
"Two Envs could run on two different processors simultaneously.",
"One Env could run on two different processors simultaneously.",
"One Env could run on two different processors at different times."
] | ['Two Envs could run on two different processors simultaneously.', 'One Env could run on two different processors at different times.'] |
86 | In JOS, suppose a value is passed between two Envs. What is the minimum number of executed system calls? | [
"-of-sums (POS) form it is opposite. POS form requires parentheses to group the OR terms together under AND gates, because OR has lower precedence than AND. Both SOP and POS forms translate nicely into circuit logic. If we have two functions F1 and F2: F 1 = A B + A C + A D, {\\displaystyle F_{1}=AB+AC+AD,\\,} F 2 ... | [
"1",
"2",
"3",
"4"
] | ['2'] |
87 | What strace tool does? | [
"tool: ICSynth by InfoChem Spaya, Software freely available proposed by Iktos",
"Examples) scoring function to provide authentic example sentences for specific target words. Results are drawn from a special corpus of high-quality texts covering everyday, standard, formal, and professional language and displayed a... | [
"It prints out system calls for given program. These system calls are always called when executing the program.",
"It prints out system calls for given program. These systems calls are called only for that particular instance of the program.",
"To trace a symlink. I.e. to find where the symlink points to.",
"... | ['It prints out system calls for given program. These systems calls are called only for that particular instance of the program.'] |
961 | Consider the following context-free grammar \(G\) (where \(\text{S}\) is the top-level symbol):
\(R_{01}: \text{S} \rightarrow \text{NP VP}\)
\(R_{02}: \text{NP} \rightarrow \text{NP0}\)
\(R_{03}: \text{NP} \rightarrow \text{Det NP0}\)
\(R_{04}: \text{NP0} \rightarrow \text{N}\)
\(R_{05}: \text{NP0} \rightarrow \text{... | [
"(CNF) grammar A CFG is in CNF if all its syntactic rules are of the form: X →X1 X2 where X ∈C\\T and X1, X2 ∈C A context free grammar is in extended Chomsky Normal Form (eCNF) if all its syntactic rules are of the form: X →X1 or X →X1 X2 where X ∈C\\T and X1, X2 ∈C Syntactic parsing: Introduction & CYK Algorithm –... | [
"the grammar \\(G\\) cannot be converted to extended Chomsky Normal Form",
"the grammar \\(G\\) already is in extended Chomsky Normal Form",
"11 rules",
"31 rules",
"48 rules"
] | ['11 rules', '31 rules'] |
966 | Select the answer that correctly describes the differences between formal and natural languages. | [
"ClearTalk is a controlled natural language—a kind of a formal language for expressing information that is designed to be both human-readable (being based on English) and easily processed by a computer. Anyone who can read English can immediately read ClearTalk, and the people who write ClearTalk learn to write it ... | [
"Formal languages are by construction explicit and non-ambiguous while natural languages are implicit and ambiguous",
"Formal languages are by construction implicit and non-ambiguous while natural languages are explicit and ambiguous",
"Formal languages are by construction explicit and ambiguous while natural l... | ['Formal languages are by construction explicit and non-ambiguous while natural languages are implicit and ambiguous'] |
972 | Which of the following are parameters involved in the choice made by an order-1 HMM model for PoS tagging knowing that its output isthis/Pron is/V a/Det good/Adj question/Nand that neither "is" nor "question" can be adjectives, and that "question" can also not be a determiner.(Penalty for wrong ticks.) | [
"s to a k-order Hidden Markov Model (HMM) Part of Speech Tagging – 14 / 23 Introduction PoS tagging with HMMs Formalization order-1 HMM definition Learning Other models Conclusion c <unk>EPFL M. Rajman & J.-C. Chappelier (order 1) Hidden Markov Models (HMM) A order-1 HMM is: for PoS-tagging: K a set of states C = {... | [
"P(N|question)",
"P(question|N)",
"P(question|Adj N)",
"P(question|N Adj)",
"P(this)",
"P(this is)",
"P(this V)",
"P(Pron)",
"P(Pron V)",
"P(Pron is)",
"P(Det|Adj)",
"P(Adj|Det)",
"P(Adj|V Det)",
"P(Adj|Det V)",
"P(Det|V Adj)",
"P(Det|Pron V)",
"P(Adj|a)",
"P(question|Adj)"
] | ['P(question|N)', 'P(Pron)', 'P(Adj|Det)'] |
973 | For each of the sub-questions of this question (next page), tick/check the corresponding box if the presented sentence is correct
at the corresponding level (for a human). There will be a penalty for wrong boxes ticked/checked.Some sentences is hard understand to. | [
"convince the Gatekeeper, purely through argumentation, to let him out of the box. Due to the rules of the experiment, he did not reveal the transcript or his successful AI coercion tactics. Yudkowsky subsequently said that he had tried it against three others and lost twice. Overall limitations Boxing an AI could ... | [
"lexical",
"syntactic",
"semantic",
"pragmatic",
"none of the above is correct"
] | ['lexical'] |
975 | Select the morpho-syntactic categories that do not carry much semantic content and are thus usually filtered-out from indexing. | [
"entre sémantique et syntaxe reste relativement floue11. Ainsi, une description syntaxique est souvent porteuse de sens (voir l'exemple de \"les invités entendaient le bruit de leur fenêtre\"). D'une façon générale, toute analyse syntaxique basée sur un nombre important de classes d'éléments du discours possède iné... | [
"Determiners ",
"Conjunctions",
"Nouns",
"Adjectives",
"Verbs"
] | ['Determiners\xa0', 'Conjunctions'] |
981 | Consider the following lexicon \(L\):
boy : Adj, N
boys : N
blue : Adj, N
drink : N, V
drinks : N, V
Nice : Adj, N
When using an order-1 HMM model (using \(L\)) to tag the word sequence:"Nice boys drink blue drinks"does the tag of drink depend on the tag of nice?
| [
"C. Chappelier Tag sets (1/2) Complexity/Grain of tag set can vary a lot (even for the same language). Original Brown Corpus tagset contains 87 PoS tags (!) For instance, it contains 4 kind of adjectives: JJ adjective recent, over-all, possible, hard-fought [.] JJR comparative adjective greater, older, further, ear... | [
"yes, because the HMM approach relies on a global maximum.",
"no, the hypotheses make the two tags independent from each other."
] | ['no, the hypotheses make the two tags independent from each other.'] |
987 | Select the statements that are true.A penalty will be applied to any incorrect answers selected. | [
"waste facility. Australia The new section of the POEO Act (The Protection of the Environment Operations Act 1997) now imposes further penalties for offences including polluting waters with waste, polluting land, illegally dumping waste or using land as an illegal waste facility (Parrino, Maysaa, Kaoutarani & Salam... | [
"Information retrieval is the selection of documents relevant to a query from an unstructured collection of documents.",
"Different IR systems can differ in the way they represent documents, represent queries, and define the relevance measure between documents and queries.",
"The vector space model represents d... | ['Information retrieval is the selection of documents relevant to a query from an unstructured collection of documents.', 'Different IR systems can differ in the way they represent documents, represent queries, and define the relevance measure between documents and queries.', 'The vector space model represents document... |
989 |
Your aim is to evaluate a movie review analysis system, the purpose of which is to determine whether a review is globally positive or negative.
For each movie review, such a system outputs one of the following classes: positive and negative.
To perform your evaluation, you collect a large set of reviews and have it an... | [
"of product reviews and movie reviews respectively. This work is at the document level. One can also classify a document's polarity on a multi-way scale, which was attempted by Pang and Snyder among others: Pang and Lee expanded the basic task of classifying a movie review as either positive or negative to predict ... | [
"Cohen's kappa",
"accuracy",
"precision",
"recall",
"standard deviation",
"F1-score"
] | ['precision', 'recall', 'F1-score'] |
995 | Consider the following context-free grammar \(G\) (where \(\text{S}\) is the top-level symbol):
\(R_{01}: \text{S} \rightarrow \text{NP VP}\)
\(R_{02}: \text{NP} \rightarrow \text{NP0}\)
\(R_{03}: \text{NP} \rightarrow \text{Det NP0}\)
\(R_{04}: \text{NP0} \rightarrow \text{N}\)
\(R_{05}: \text{NP0} \rightarrow \text{... | [
"NP Det the N cat VP V PNP F(T) = {the, cat, V, PNP} and lmnt(T) = V ÉC OLE PO L Y TEC H NIQ U E FÉ DÉR A LE D E LA USAN NE LIA I&C Computational Linguistics Course (EPFL-MsCS) M. Rajman J.-C. Chappelier 12/29 ✬ ✫ ✩ ✪ Notations (2) Furthermore, the same notation R will be used for both the rule and the correspondin... | [
"\\(R_{01}, R_{08}, R_{02}, R_{04}, \\text{N}(\\text{letter}), \\text{V}(\\text{ran}), R_{03}, \\text{Det}(\\text{the}), R_{04}, \\text{N}(\\text{drinks})\\)",
"\\(R_{01}, R_{03}, \\text{Det}(\\text{a}), R_{05}, \\text{Adj}(\\text{blue}), \\text{N}(\\text{drink}), R_{07}, \\text{V}(\\text{ran})\\)",
"\\(R_{01},... | ['\\(R_{01}, R_{03}, \\text{Det}(\\text{a}), R_{05}, \\text{Adj}(\\text{blue}), \\text{N}(\\text{drink}), R_{07}, \\text{V}(\\text{ran})\\)'] |
996 | Select all statements that are true.A penalty will be applied for any wrong answers. | [
"waste facility. Australia The new section of the POEO Act (The Protection of the Environment Operations Act 1997) now imposes further penalties for offences including polluting waters with waste, polluting land, illegally dumping waste or using land as an illegal waste facility (Parrino, Maysaa, Kaoutarani & Salam... | [
"The analyzer functionality of a parser determines the set of all possible associated syntactic structures for any syntactically correct sentence.",
"The recognizer functionality of a parser decides if a given sequence of words is syntactically correct or not.",
"For a sentence to be acceptable in general, it i... | ['The analyzer functionality of a parser determines the set of all possible associated syntactic structures for any syntactically correct sentence.', 'The recognizer functionality of a parser decides if a given sequence of words is syntactically correct or not.', 'Determining whether a sentence has a pragmatic meaning ... |
1000 | The edit distance between “piece” and “peace” is(Penalty for wrong ticks) | [
"limiting pedestrian density during events.",
"waste facility. Australia The new section of the POEO Act (The Protection of the Environment Operations Act 1997) now imposes further penalties for offences including polluting waters with waste, polluting land, illegally dumping waste or using land as an illegal was... | [
"5",
"3",
"1, if considering insertion and deletion only",
"2, if considering insertion and deletion only",
"3, if considering insertion and deletion only",
"1, if considering insertion, deletion and substitution",
"2, if considering insertion, deletion and substitution",
"3, if considering insertion,... | ['2, if considering insertion and deletion only', '2, if considering insertion, deletion and substitution', '2, if considering insertion, deletion, transposition and substitution'] |
1010 | Select which statements are true about the CYK algorithm.A penalty will be applied for any incorrect answers. | [
"yle \\Theta } is the conditional expectation consensus (CEC) penalty on unlabeled data. The CEC penalty is defined as follows. Let the marginal kernel density for all the data be g m π ( x ) = ⟨ φ m π, ψ m ( x ) ⟩ {\\displaystyle g_{m}^{\\pi }(x)=\\langle \\phi _{m}^{\\pi },\\psi _{m}(x)\\rangle } where ψ m ( x ) ... | [
"It is a top-down chart parsing algorithm.",
"Its time complexity is \\( O(n^3) \\), where \\( n \\) is the length of sequence of words to be parsed.",
"Its time complexity decreases when the grammar is regular.",
"The Context-Free Grammar used with the CYK algorithm has to be converted into extended Chomsky ... | ['Its time complexity is \\( O(n^3) \\), where\xa0\\( n \\) is the length of sequence of words to be parsed.', 'The Context-Free Grammar used with the CYK algorithm has to be converted into extended Chomsky normal form.', 'It not only generates the syntactic interpretations of the sequence to be analyzed but also gener... |
1011 | Select all statements that are true.A penalty will be applied for any wrong answers. | [
"waste facility. Australia The new section of the POEO Act (The Protection of the Environment Operations Act 1997) now imposes further penalties for offences including polluting waters with waste, polluting land, illegally dumping waste or using land as an illegal waste facility (Parrino, Maysaa, Kaoutarani & Salam... | [
"Phrase-structure grammars are relatively better suited for fixed-order languages than free-order languages.",
"Dependency grammars describe functional dependencies between words in a sequence.",
"Phrase-structure grammars better describe selectional constraints.",
"The expressive power of context-free gramma... | ['Phrase-structure grammars are relatively better suited for fixed-order languages than free-order languages.', 'Dependency grammars describe functional dependencies between words in a sequence.', 'Any context-free grammar can be transformed into Chomsky-Normal form.'] |
1016 | What is a good distance metric to be used when you want to compute the similarity between documents independent of their length?A penalty will be applied for any incorrect answers. | [
"file comparison tools Computer-assisted reviewing – Text-comparison software Data differencing – Method for compressing changes over time Delta encoding – Type of data transmission method Document comparison Edit distance – Computer science metric of string similarity References",
"as a move. Text movements are ... | [
"Cosine similarity",
"Euclidean distance",
"Manhattan distance",
"Chi-squared distance"
] | ['Cosine similarity'] |
1025 | For this question, one or more assertions can be correct. Tick only the correct assertion(s). There will be a penalty for wrong assertions ticked.Which of the following associations can be considered as illustrative examples for inflectional
morphology (with here the simplifying assumption that canonical forms are rest... | [
"it into morphemes and produce additional syntactic and semantic information (on the current word) processable → process- -able ☞2 morphemes meaning: process possible role: root suffix semantic information: main less The importance and complexity of morphology vary from language to language Some information represe... | [
"(activate, action)",
"(hypothesis, hypotheses)",
"(to go, went)",
"(speaking, talking)"
] | ['(hypothesis, hypotheses)', '(to go, went)'] |
1026 | Consider the following lexicon \(L\):
bear : V, N
bears : V, N
blue : Adj, N
drink : N, V
drinks : N, V
Nice : Adj, N
When using an order-1 HMM model (using \(L\)) to tag the word sequence:"Nice bears drink blue drinks"does the tag of drink depend on the tag of nice?
| [
"C. Chappelier Tag sets (1/2) Complexity/Grain of tag set can vary a lot (even for the same language). Original Brown Corpus tagset contains 87 PoS tags (!) For instance, it contains 4 kind of adjectives: JJ adjective recent, over-all, possible, hard-fought [.] JJR comparative adjective greater, older, further, ear... | [
"yes, because the HMM approach relies on a global maximum.",
"no, the hypotheses make the two tags independent from each other."
] | ['yes, because the HMM approach relies on a global maximum.'] |
1031 | What could Out of Vocabulary (OoV) forms consist of? Select all that apply.A penalty will be applied for wrong answers. | [
"waste facility. Australia The new section of the POEO Act (The Protection of the Environment Operations Act 1997) now imposes further penalties for offences including polluting waters with waste, polluting land, illegally dumping waste or using land as an illegal waste facility (Parrino, Maysaa, Kaoutarani & Salam... | [
"Words from the lexicon",
"Words borrowed from other languages",
"Words with spelling errors",
"Neologisms",
"Abbreviations"
] | ['Words borrowed from other languages', 'Words with spelling errors', 'Neologisms', 'Abbreviations'] |
1034 | Select all the statements that are true.A penalty will be applied for any incorrect answers selected. | [
"waste facility. Australia The new section of the POEO Act (The Protection of the Environment Operations Act 1997) now imposes further penalties for offences including polluting waters with waste, polluting land, illegally dumping waste or using land as an illegal waste facility (Parrino, Maysaa, Kaoutarani & Salam... | [
"The Luhn law states that if a set of words are ranked by the decreasing order of their frequencies, the high-ranked words are the best features for identifying the topics that occur in the document collection.",
"The order of words are ignored in the bag-of-words model.",
"High values of document frequency mea... | ['The order of words are ignored in the bag-of-words model.', 'High values of document frequency means that the word is not very discriminative.', 'Cosine similarity is independent of the length of the documents.'] |
1035 | Consider:Non-terminals: S (top-level), NP (for "noun phrase"), VP (for "verbal phrase"), N (for "Noun"), V (for "Verb"), Det (for "Determiner").PoS tags: N, V, DetTerminals: I, yesterday, in, rain, went, home, the, cat, goOut of the following, select the ones which are possible valid "syntactic rules" as defined in a c... | [
"b\\right\\}} and non-terminal S symbols and a blank ε {\\displaystyle \\epsilon } may also be used as an end point. In the production rules of CFG and PCFG the left side has only one nonterminal whereas the right side can be any string of terminal or nonterminals. In PCFG nulls are excluded. An example of a gramma... | [
"S → NP VP",
"NP → Det N",
"V → VP N ",
"NP → N",
"VP → VP NP",
"VP NP → V N",
"VP → the cat",
"Det → went",
"Det N → NP",
"S → VP"
] | ['S\xa0→ NP VP', 'NP → Det N', 'NP → N', 'VP → VP NP', 'S → VP'] |
1157 | Which of the following statements are true? | [
"o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o oo o o o o o o o o o o o o o o o o o o o o oo o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o oo o o o o o o o o o o o o oo o o oo o o o o o o o o o o oo o o o oo o o o o o o o o o o o o o o o o o o o o o o o ... | [
"The more training examples, the more accurate the prediction of a $k$-nearest-neighbor classifier.",
"k-nearest-neighbors cannot be used for regression.",
"A $k$-nearest-neighbor classifier is sensitive to outliers.",
"Training a $k$-nearest-neighbor classifier takes more computational time than applying it ... | ['The more training examples, the more accurate the prediction of a $k$-nearest-neighbor classifier.', 'A $k$-nearest-neighbor classifier is sensitive to outliers.'] |
1158 | Let $n$ be an integer such that $n\geq 2$ and let $A \in \R^{n imes n}$, and $xv \in \R^n$, consider the function $f(xv) = xv^ op A xv$ defined over $\R^n$. Which of the following is the gradient of the function $f$? | [
"∇f : E →E defined by the following property: ∀x, v ∈E, ⟨∇f(x), v⟩= Df(x)[v]. Exercise 2.19. Show that Definition 2.18 is valid, that is, show that ∇f(x) exists under the stated conditions, and is unique. Exercise 2.20. Let E = Rn with the usual inner product. Show that (in this important particular case) ∇f(x) ∈Rn... | [
"$2 xv^\top A$",
"$2Axv$",
"$A^\top xv + Axv$",
"$2A^\top xv$"
] | $A^ op xv + Axv$$
abla f (xv)= A^ op xv+Axv$. Here the matrix $A$ is not symmetric. |
1160 | Consider a classification problem using either SVMs or logistic regression and separable data. For logistic regression we use a small regularization term (penality on weights) in order to make the optimum welldefined. Consider a point that is correctly classified and distant from the decision boundary. Assume that we m... | [
"s, including structured prediction problems. It is not clear that SVMs have better predictive performance than other linear models, such as logistic regression and linear regression. Motivation Classifying data is a common task in machine learning. Suppose some given data points each belong to one of two classes, ... | [
"Small change for SVMs and small change for logistic regression.",
"No change for SVMs and large change for logistic regression.",
"No change for SVMs and no change for logistic regression.",
"No change for SVMs and a small change for logistic regression.",
"Large change for SVMs and large change for logist... | No change for SVMs and a small change for logistic regression. |
1161 | You are given a distribution on $X, Y$, and $Z$ and you know that the joint distribution can be written in the form $p(x, y, z)=p(x) p(y \mid x) p(z \mid y)$. What conclusion can you draw? [Recall that $\perp$ means independent and $\mid \cdots$ means conditioned on $\cdots$. | [
"_{n},C_{k})=p(x_{i}\\mid C_{k})\\,.} Thus, the joint model can be expressed as p ( C k ∣ x 1,..., x n ) <unk> p ( C k, x 1,..., x n ) = p ( C k ) p ( x 1 ∣ C k ) p ( x 2 ∣ C k ) p ( x 3 ∣ C k ) ⋯ = p ( C k ) ∏ i = 1 n p ( x i ∣ C k ), {\\displaystyle {\\begin{aligned}p(C_{k}\\mid x_{1},\\ldots,x_{n})\\varpropto \\... | [
"$Y \\perp Z$",
"$X \\perp Y \\mid Z$",
"$Y \\perp Z \\quad X$",
"$X \\perp Z$",
"$X \\perp Y$",
"$X \\perp Z \\quad \\mid Y$"
] | $X \perp Z \quad \mid Y$ |
1164 | (Weight initialization) The choice of weight initialization will not impact the optimization behavior of the neural network. | [
"In deep learning, weight initialization or parameter initialization describes the initial step in creating a neural network. A neural network contains trainable parameters that are modified during training: weight initialization is the pre-training step of assigning initial values to these parameters. The choice o... | [
"True",
"False"
] | False |
1165 | Under certain conditions, maximizing the log-likelihood is equivalent to minimizing mean-squared error for linear regression. The mean-squared error can be defined as $\mathcal{L}_{m s e}(\mathbf{w}):=$ $\frac{1}{2 N} \sum_{n=1}^{N}\left(y_{n}-\widetilde{\mathbf{x}}_{n}^{\top} \mathbf{w}\right)^{2}$ and $y_{n}=\widetil... | [
"| w) = p(X | w)p(y | X, w) = p(X)p(y | X, w), where in the second step we have made the natural assumption that the X data does not depend on the parameter we choose in our model. Note that this is an assumption and part of our model. But now note that the factor p(X) is a constant wrt to the choice of w, and henc... | [
"The noise parameter $\\varepsilon_{n}$ should have a normal distribution.",
"The target variable $y_{n}$ should have a normal distribution.",
"The i.i.d. assumption on the variable $\\mathbf{w}$.",
"The conditional probability $p\\left(y_{n} \\mid \\widetilde{\\mathbf{x}}_{n}, \\mathbf{w}\\right)$ should fol... | The noise parameter $\varepsilon_{n}$ should have a normal distribution. |
1167 | Consider our standard least-squares problem $$ \operatorname{argmin}_{\mathbf{w}} \mathcal{L}(\mathbf{w})=\operatorname{argmin}_{\mathbf{w}} \frac{1}{2} \sum_{n=1}^{N}\left(y_{n}-\mathbf{x}_{n}^{\top} \mathbf{w}\right)^{2}+\frac{\lambda}{2} \sum_{d=1}^{D} w_{d}^{2} $$ Here, $\left\{\left(\mathbf{x}_{n} y_{n}\right)\rig... | [
") − y j ) 2 = ( ⟨ w, x j ⟩ − y j ) 2 {\\displaystyle V(f(x_{j}),y_{j})=(f(x_{j})-y_{j})^{2}=(\\langle w,x_{j}\\rangle -y_{j})^{2}} is used to compute the vector w {\\displaystyle w} that minimizes the empirical loss I n [ w ] = ∑ j = 1 n V ( ⟨ w, x j ⟩, y j ) = ∑ j = 1 n ( x j T w − y j ) 2 {\\displaystyle I_{n}[w... | [
"$\\operatorname{argmin}_{\\boldsymbol{\\alpha}} \\frac{1}{2} \\boldsymbol{\\alpha}^{\\top}\\left(\\mathbf{X X}^{\\top}+\\lambda \\mathbf{I}_{N}\\right) \\boldsymbol{\\alpha}-\\boldsymbol{\\alpha}^{\\top} \\mathbf{y}$",
"$\\operatorname{argmin}_{\\mathbf{w}} \\sum_{n=1}^{N}\\left[1-y_{n} \\mathbf{x}_{n}^{\\top} \... | ['$\\operatorname{argmin}_{\\boldsymbol{\\alpha}} \\frac{1}{2} \\boldsymbol{\\alpha}^{\\top}\\left(\\mathbf{X X}^{\\top}+\\lambda \\mathbf{I}_{N}\\right) \\boldsymbol{\\alpha}-\\boldsymbol{\\alpha}^{\\top} \\mathbf{y}$', '$\\operatorname{argmin}_{\\mathbf{w}}-\\log p(\\mathbf{y} \\mid \\mathbf{X}, \\mathbf{w}) p(\\math... |
1173 | In Text Representation learning, which of the following statements is correct? | [
"representation learning of a certain data type (e.g. text, image, audio, video) is to pretrain the model using large datasets of general context, unlabeled data. Depending on the context, the result of this is either a set of representations for common data segments (e.g. words) which new data can be broken into, ... | [
"Learning GloVe vectors can be done using SGD in a streaming fashion, by streaming through the input text only once.",
"Every recommender systems algorithm for learning a matrix factorization $\\boldsymbol{W} \\boldsymbol{Z}^{\\top}$ approximating the observed entries in least square sense does also apply to lear... | ['Every recommender systems algorithm for learning a matrix factorization $\\boldsymbol{W} \\boldsymbol{Z}^{\\top}$ approximating the observed entries in least square sense does also apply to learn GloVe word vectors.', 'If you fix all word vectors, and only train the remaining parameters, then FastText in the two-clas... |
1174 | Consider the following joint distribution on $X$ and $Y$, where both random variables take on the values $\{0,1\}: p(X=$ $0, Y=0)=0.1, p(X=0, Y=1)=0.2, p(X=1, Y=0)=0.3, p(X=1, Y=1)=0.4$. You receive $X=1$. What is the largest probability of being correct you can achieve when predicting $Y$ in this case? | [
"yle P(X\\mid Y=y)} is a model of the distribution of each label, and a model of the joint distribution is equivalent to a model of the distribution of label values P ( Y ) {\\displaystyle P(Y)}, together with the distribution of observations given a label, P ( X ∣ Y ) {\\displaystyle P(X\\mid Y)} symbolically, P (... | [
"$\\frac{1}{3}$",
"$\\frac{3}{4}$",
"$\\frac{1}{7}$",
"$0$",
"$1$",
"$\\frac{2}{3}$",
"$\\frac{6}{7}$",
"$\\frac{4}{7}$",
"$\\frac{3}{7}$",
"$\\frac{1}{4}$",
"$\\frac{2}{4}$"
] | $\frac{4}{7}$ |
1177 | Which of the following statements are correct? | [
"o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o oo o o o o o o o o o o o o o o o o o o o o oo o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o oo o o o o o o o o o o o o oo o o oo o o o o o o o o o o oo o o o oo o o o o o o o o o o o o o o o o o o o o o o o ... | [
"One iteration of standard SGD for SVM costs roughly $\\Theta(D)$, where $D$ is the dimension.",
"Unions of convex sets are convex.",
"Hinge loss (as in SVMs) is typically preferred over L2 loss (least squares loss) in classification tasks.",
"In PCA, the first principal direction is the eigenvector of the da... | ['Hinge loss (as in SVMs) is typically preferred over L2 loss (least squares loss) in classification tasks.', 'MSE (mean squared error) is typically more sensitive to outliers than MAE (mean absolute error)', 'One iteration of standard SGD for SVM costs roughly $\\Theta(D)$, where $D$ is the dimension'] |
1179 | (Backpropagation) Training via the backpropagation algorithm always learns a globally optimal neural network if there is only one hidden layer and we run an infinite number of iterations and decrease the step size appropriately over time. | [
", backpropagation can be understood in terms of automatic differentiation, where backpropagation is a special case of reverse accumulation (or \"reverse mode\"). Intuition Motivation The goal of any supervised learning algorithm is to find a function that best maps a set of inputs to their correct output. The moti... | [
"True",
"False"
] | False |
1183 | Which of the following statements about the $\mathrm{SVD}$ of an $N \times D$ matrix $\mathbf{X}$ are correct? | [
"is 0 thereafter. We claim that UKU<unk> KX = UKU<unk> KUSV<unk>= US(K)V<unk>. (2) With this interpretation, the lemma states that the best rank-K approximation to a matrix X is obtained by com- puting the SVD and by setting all the singular values sj, j ≥K + 1 to zero. The claim (2) is easily seen by checking that... | [
"We can compute the singular values of $\\mathbf{X}$ by computing the eigenvalues of $\\mathbf{X X}^{\\top}$. This has complexity $O\\left(N^{3}\\right)$.",
"We can compute the singular values of $\\mathbf{X}$ by computing the eigenvalues of $\\mathbf{X X}^{\\top}$. This has complexity $O\\left(D^{3}\\right)$.",
... | ['We can compute the singular values of $\\mathbf{X}$ by computing the eigenvalues of $\\mathbf{X}^{\\top} \\mathbf{X}$. This has complexity $O\\left(D^{3}\\right)$.', 'We can compute the singular values of $\\mathbf{X}$ by computing the eigenvalues of $\\mathbf{X X}^{\\top}$. This has complexity $O\\left(N^{3}\\right)... |
1184 | Consider a linear regression problem with $N$ samples where the input is in $D$-dimensional space, and all output values are $y_{i} \in\{-1,+1\}$. Which of the following statements is correct? | [
",\\Theta _{1},\\ldots,\\Theta _{M})={\\frac {1}{M}}\\sum _{j=1}^{M}m_{n}(\\mathbf {x},\\Theta _{j})}. For regression trees, we have m n = ∑ i = 1 n Y i 1 X i ∈ A n ( x, Θ j ) N n ( x, Θ j ) {\\displaystyle m_{n}=\\sum _{i=1}^{n}{\\frac {Y_{i}\\mathbf {1} _{\\mathbf {X} _{i}\\in A_{n}(\\mathbf {x},\\Theta _{j})}}{N... | [
"(a) linear regression cannot \"work\" if $N \\gg D$",
"(b) linear regression cannot \"work\" if $N \\ll D$",
"(c) linear regression can be made to work perfectly if the data is linearly separable"
] | (c) |
1185 | Consider a matrix factorization problem of the form $\mathbf{X}=\mathbf{W Z}^{\top}$ to obtain an item-user recommender system where $x_{i j}$ denotes the rating given by $j^{\text {th }}$ user to the $i^{\text {th }}$ item . We use Root mean square error (RMSE) to gauge the quality of the factorization obtained. Selec... | [
"Matrix Factorization (ScalableNMF), Distributed Stochastic Singular Value Decomposition. Online: how to update the factorization when new data comes in without recomputing from scratch, e.g., see online CNSC Collective (joint) factorization: factorizing multiple interrelated matrices for multiple-view learning, e.... | [
"Given a new item and a few ratings from existing users, we need to retrain the already trained recommender system from scratch to generate robust ratings for the user-item pairs containing this item.",
"Regularization terms for $\\mathbf{W}$ and $\\mathbf{Z}$ in the form of their respective Frobenius norms are a... | None of the other options are correct. |
1191 | Consider the composite function $f(x)=g(h(x))$, where all functions are $\mathbb{R}$ to $\mathbb{R}$. Which of the following is the weakest condition that guarantees that $f(x)$ is convex? | [
"x^{*}}. If the convex function f {\\displaystyle f} is defined on the whole line and is everywhere differentiable, then f ∗ ( p ) = sup x ∈ I ( p x − f ( x ) ) = ( p x − f ( x ) ) | x = ( f ′ ) − 1 ( p ) {\\displaystyle f^{*}(p)=\\sup _{x\\in I}(px-f(x))=\\left(px-f(x)\\right)|_{x=(f')^{-1}(p)}} can be interpreted... | [
"$g(x)$ and $h(x)$ are convex and $g(x)$ and $h(x)$ are increasing",
"$g(x)$ is convex and $g(x)$ is increasing",
"$g(x)$ and $h(x)$ are convex and $h(x)$ is increasing",
"$g(x)$ and $h(x)$ are convex and $g(x)$ is increasing",
"$g(x)$ is convex and $g(x)$ and $h(x)$ are increasing",
"$h(x)$ is convex and... | $g(x)$ and $h(x)$ are convex and $g(x)$ is increasing |
1193 | Matrix Factorizations: The function $f(\mathbf{v}):=g\left(\mathbf{v} \mathbf{v}^{\top}\right)$ is convex over the vectors $\mathbf{v} \in \mathbb{R}^{2}$, when $g: \mathbb{R}^{2 \times 2} \rightarrow \mathbb{R}$ is defined as | [
"function f : E →R is convex if f((1 -t)x + ty) ≤(1 -t)f(x) + tf(y) for all x, y ∈E and all t ∈[0, 1]. There are several reasons why convexity is a delightful property to have in optimization. One of them is that convex functions do not have non-global local minima. Theorem 4.2. [Proof for exam 2025] If f is convex... | [
"(a) if we define $g: \\mathbb{R}^{2 \\times 2} \\rightarrow \\mathbb{R}$ as $g(\\mathbf{X}):=X_{11}$.",
"(b) if we define $g: \\mathbb{R}^{2 \\times 2} \\rightarrow \\mathbb{R}$ as $g(\\mathbf{X}):=X_{11}+X_{22}$."
] | ['(a)', '(b)'] |
1194 | (Neural networks) Training only the first layer of a deep neural network using the logistic loss is equivalent to training a logistic regression over a transformed feature space. | [
"data in the same way as we learn the weights of the linear classifier? This is what neural networks allow us to do. There is currently a lot of excitement about neural networks and its many applications. At the end of this short tutorial you will unlikely be able to program a neural net to play Go like a grandmast... | [
"True",
"False"
] | False |
1196 | Our task is to classify whether an animal is a dog (class 0) or a cat (class 1) based on the following features:
egin{itemize}
\item $x_1$: height
\item $x_2$: length of whiskers
\item $x_3$: thickness of fur
\end{itemize}
We perform standard normal scaling on the tr... | [
"testing data is a critical one for pattern classification. In some simple examples of function learning, a relationship that could be explicitly stated for the complete set of possible feature vectors is learned. However, in classification problems we often have a huge or even infinite number of potential feature ... | [
"$w_1 < w_2 < w_3$",
"$w_1 < w_3 < w_2$",
"$w_2 < w_1 < w_3$",
"$w_2 < w_3 < w_1$",
"$w_3 < w_1 < w_2$",
"$w_3 < w_2 < w_1$"
] | $w_1 < w_3 < w_2$$w_1 < w_3 < w_2$. When the features are standardized, a below-average height $x_1$ becomes negative. Negative heights increase the probability that the animal is a cat, so the height and cat probability are inversely correlated, and therefore $w_1 < 0$. Conversely, a positive whisker length $x_2$ incr... |
1201 | Consider two fully connected networks, A and B, with a constant width for all layers, inputs and outputs.
Network A has depth $3L$ and width $H$, network B has depth $L$ and width $2H$.
Everything else is identical for the two networks and both $L$ and $H$ are large.
In this case, performing a single iteration of ba... | [
": Write down the network pre- tending that all the parameters are independent. Run the backpropagation algorithm. The gradient for a particular pa- rameter for the model where some weights are equal is now just the sum of the gradients (of the model where weights are independent) of all the edges that share the sa... | [
"True",
"False"
] | TrueTrue.
The number of multiplications required for backpropagation is linear in the depth and quadratic in the width, $3LH^2 < L (2H)^2 = 4LH^2$. |
1207 | Consider the loss function $L: \R^d o \R$, $L(\wv) = rac{eta}{2}\|\wv\|^2$, where $eta > 0$ is a constant. We run gradient descent on $L$ with a stepsize $\gamma > 0$ starting from some $\wv_0
eq 0$. Which of the statements below is true? | [
"{\\displaystyle m\\geq 1}, where h m ∈ H {\\displaystyle h_{m}\\in {\\mathcal {H}}} is a base learner function. Unfortunately, choosing the best function h m {\\displaystyle h_{m}} at each step for an arbitrary loss function L is a computationally infeasible optimization problem in general. Therefore, we restrict ... | [
"Gradient descent converges to the global minimum for any stepsize $\\gamma > 0$.",
"Gradient descent with stepsize $\\gamma = \frac{2}{\beta}$ produces iterates that diverge to infinity ($\\|\\wv_t\\| \to \\infty$ as $t\to \\infty$).",
"Gradient descent converges in two steps for $\\gamma = \frac{1}{\beta}$ (i... | Gradient descent converges to the global minimum for any stepsize in the interval $\gamma \in ig( 0, rac{2}{eta}ig)$.The update rule is $\wv_{t+1} = \wv_t - \gammaeta \wv_t = (1 - \gammaeta) \wv_t$. Therefore we have that the sequence $\{\|\wv_{t}\|\}_t$ is given by $\|\wv_{t+1}\| = \lvert 1 - \gammaeta
vert \|\... |
1216 | 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... | [
"\" competition to find a program to better predict user preferences and improve the accuracy of its existing Cinematch movie recommendation algorithm by at least 10%. A joint team made up of researchers from AT&T Labs-Research in collaboration with the teams Big Chaos and Pragmatic Theory built an ensemble model t... | [
"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. |
1217 | 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 $\... | [
". The two historically common activation functions are both sigmoids, and are described by y ( v i ) = tanh ( v i ) and y ( v i ) = ( 1 + e − v i ) − 1 {\\displaystyle y(v_{i})=\\tanh(v_{i})~~{\\textrm {and}}~~y(v_{i})=(1+e^{-v_{i}})^{-1}}. The first is a hyperbolic tangent that ranges from −1 to 1, while the ot... | [
"$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 $T$",
"$C_{g, \frac{1}{2}}$, $C_{h, 0}$, a... | $C_{g, rac{1}{2}}$, $C_{h, 0}$, and $C_{q, 0}$ have the same accuracy as $C_{f, rac{1}{2}}$ on $T$
Since the threshold $ rac{1}{2}$ for sigmoid corresponds to the input to the last activation function being positive, $C_{h, 0}$ is true. Moreover, multiplying the weights by 2 does not change the sign ... |
1224 | Assume we have $N$ training samples $(\xx_1, y_1), \dots, (\xx_N, y_N)$ where for each sample $i \in \{1, \dots, N\}$ we have that $\xx_i \in \R^d$ and $y_i \in \{-1, 1\}$. We want to classify the dataset using the exponential loss $L(\ww) = rac{1}{N} \sum_{i=1}^N \exp (-y_i \xx_i^ op \ww )$ for $\ww \in \R^d$.
Whic... | [
"is assumed that the training set consists of a sample of independent and identically distributed pairs, ( x i, y i ) {\\displaystyle (x_{i},\\;y_{i})}. In order to measure how well a function fits the training data, a loss function L : Y × Y → R ≥ 0 {\\displaystyle L:Y\\times Y\\to \\mathbb {R} ^{\\geq 0}} is defi... | [
"This corresponds to doing logistic regression as seen in class.",
"The loss function $L$ is non-convex in $\\ww$.",
"If I find a vector $\\ww^\\star$ such that $L(\\ww^\\star) < 1 / N$, then $\\ww^*$ linearly separates my dataset.",
"There exists a vector $\\ww^\\star$ such that $L(\\ww^\\star) = 0$.",
"\"... | If I find a vector $\ww^\star$ such that $L(\ww^\star) < 1 / N$, then $\ww^*$ linearly separates my dataset.$L(w^\star) < 1 / N$ implies $\exp(- y_i \xx_i op w^*) < 1$ $ orall i$, which means that $y_i \xx_i op w^\star > 0$ $ orall i$. |
1404 | Which of the following is correct regarding Louvain algorithm? | [
"In classical mechanics, a Liouville dynamical system is an exactly solvable dynamical system in which the kinetic energy T and potential energy V can be expressed in terms of the s generalized coordinates q as follows: T = 1 2 { u 1 ( q 1 ) + u 2 ( q 2 ) + ⋯ + u s ( q s ) } { v 1 ( q 1 ) q ̇ 1 2 + v 2 ( q 2 ) q ̇ ... | [
"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 commun... | ['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'] |
1410 | 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: | [
"versions). A pair d i {\\displaystyle d_{i}} and d j {\\displaystyle d_{j}} is concordant if both r a {\\displaystyle r_{a}} and r b {\\displaystyle r_{b}} agree in how they order d i {\\displaystyle d_{i}} and d j {\\displaystyle d_{j}}. It is discordant if they disagree. Information retrieval quality Information... | [
"1/2",
"5/12",
"3/4",
"7/24"
] | ['5/12'] |
1415 | Which of the following is true? | [
"o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o oo o o o o o o o o o o o o o o o o o o o o oo o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o oo o o o o o o o o o o o o oo o o oo o o o o o o o o o o oo o o o oo o o o o o o o o o o o o o o o o o o o o o o o ... | [
"High precision implies low recall",
"High precision hurts recall",
"High recall hurts precision",
"High recall implies low precision"
] | ['High precision hurts recall', 'High recall hurts precision'] |
1416 | The inverse document frequency of a term can increase | [
",d); augmented frequency, to prevent a bias towards longer documents, e.g. raw frequency divided by the raw frequency of the most frequently occurring term in the document: t f ( t, d ) = 0.5 + 0.5 ⋅ f t, d max { f t ′, d : t ′ ∈ d } {\\displaystyle \\mathrm {tf} (t,d)=0.5+0.5\\cdot {\\frac {f_{t,d}}{\\max\\{f_{t'... | [
"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 |
1417 | Which of the following is wrong regarding Ontologies? | [
"(2008). \"Ontology (Science)\". In Eschenbach, C.; Gruninger, M. (eds.). Formal Ontology in Information Systems, Proceedings of FOIS 2008. ISO Press. pp. 21–35. CiteSeerX 10.1.1.681.2599. Staab, S.; Studer, R., eds. (2009). \"What is an Ontology?\". Handbook on Ontologies (2nd ed.). Springer. pp. 1–17. doi:10.1007... | [
"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'] |
1418 | 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)? | [
". Examples of ranking quality measures: Mean average precision (MAP); DCG and NDCG; Precision@n, NDCG@n, where \"@n\" denotes that the metrics are evaluated only on top n documents; Mean reciprocal rank; Kendall's tau; Spearman's rho. DCG and its normalized variant NDCG are usually preferred in academic research w... | [
"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'] |
1420 | What is true regarding Fagin's algorithm? | [
"This time assumes a statistical model subject to Poincaré recurrence. A much simplified way of thinking about this time is in a model where the universe's history repeats itself arbitrarily many times due to properties of statistical mechanics; this is the time scale when it will first be somewhat similar (for a r... | [
"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'] |
1422 | Which of the following is WRONG for Ontologies? | [
"(2008). \"Ontology (Science)\". In Eschenbach, C.; Gruninger, M. (eds.). Formal Ontology in Information Systems, Proceedings of FOIS 2008. ISO Press. pp. 21–35. CiteSeerX 10.1.1.681.2599. Staab, S.; Studer, R., eds. (2009). \"What is an Ontology?\". Handbook on Ontologies (2nd ed.). Springer. pp. 1–17. doi:10.1007... | [
"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.'] |
1424 | What is the benefit of LDA over LSI? | [
", supervised Latent Dirichlet Allocation with covariates (SLDAX) has been specifically developed to combine latent topics identified in texts with other manifest variables. This approach allows for the integration of text data as predictors in statistical regression analyses, improving the accuracy of mental healt... | [
"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, co... | ['LDA has better theoretical explanation, and its empirical results are in general better than LSI’s'] |
1426 | Maintaining the order of document identifiers for vocabulary construction when partitioning the document collection is important | [
"Document classification or document categorization is a problem in library science, information science and computer science. The task is to assign a document to one or more classes or categories. This may be done \"manually\" (or \"intellectually\") or algorithmically. The intellectual classification of documents... | [
"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 |
1427 | Which of the following is correct regarding Crowdsourcing? | [
"s rely on the power of the crowd hopefully. For example, suppose we want to identify a picture according to the people in a picture is adult or not, this is a Bernoulli labeling problem, and all of us can do in one or two seconds, this is an easy task for human being. However, if we have tens of thousands picture ... | [
"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 |
1428 | When computing PageRank iteratively, the computation ends when... | [
"Computation PageRank can be computed either iteratively or algebraically. The iterative method can be viewed as the power iteration method or the power method. The basic mathematical operations performed are identical. Iterative At t = 0 {\\displaystyle t=0}, an initial probability distribution is assumed, usually... | [
"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... | ['The norm of the difference of rank vectors of two subsequent iterations falls below a predefined threshold'] |
1430 | How does LSI querying work? | [
"ing CBWFQ and LLQ External links Low Latency Queuing (LLQ) Cisco QoS – Low Latency Queuing Bandwidth Sharing within CBWFQ/LLQ",
"A query-level feature or QLF is a ranking feature utilized in a machine-learned ranking algorithm. Example QLFs: How many times has this query been run in the last month? How many word... | [
"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 ortho... | The query vector is treated as an additional document; then cosine similarity is computed
|
1433 | Suppose that an item in a leaf node N exists in every path. Which one is correct? | [
"of the ring where id starts with 1. The routing table therefore contains log2(n) rows populated as follows. Level 0: 1* -> this enables to forward to any node with an id starting with a 1 Level 1: 00* -> this enables to forward to any node with an id starting with a 00 Level 2: 010*-> this enables to forward to an... | [
"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.'] |
1434 | 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)? | [
". Examples of ranking quality measures: Mean average precision (MAP); DCG and NDCG; Precision@n, NDCG@n, where \"@n\" denotes that the metrics are evaluated only on top n documents; Mean reciprocal rank; Kendall's tau; Spearman's rho. DCG and its normalized variant NDCG are usually preferred in academic research w... | [
"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+ |
1439 | 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 | [
"Frequent pattern discovery (or FP discovery, FP mining, or Frequent itemset mining) is part of knowledge discovery in databases, Massive Online Analysis, and data mining; it describes the task of finding the most frequent and relevant patterns in large datasets. The concept was first introduced for mining transact... | [
"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'] |
1441 | 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.) | [
"The network probability matrix describes the probability structure of a network based on the historical presence or absence of edges in a network. For example, individuals in a social network are not connected to other individuals with uniform random probability. The probability structure is much more complex. Int... | [
"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'] |
1444 | Which of the following methods does not exploit statistics on the co-occurrence of words in a text? | [
"s focuses on the meanings of common words and the relations between common words, unlike text mining, which tends to focus on whole documents, document collections, or named entities (names of people, places, and organizations). Statistical semantics is a subfield of computational semantics, which is in turn a sub... | [
"Word embeddings\n\n\n",
"Transformers\n\n\n",
"Vector space retrieval\n\n\n",
"Fasttext"
] | ['Vector space retrieval\n\n\n'] |
1449 | Which attribute gives the best split?A1PNa44b44A2PNx51y33A3PNt61j23 | [
"al splitting method [7, Algorithm 3.1] can therefore be used to solve (12). EPFL 2021 | Mathematical Foundations of Signal Processing M. Simeoni, B. Bejar & J. Fageot 28 Primal-Dual Splitting Method Algorithm 5 Primal-Dual Splitting (PDS) Method 1: procedure PDS(τ,σ,ρ,x0,z0) 2: for all n ≥1 do 3: ̃xn = proxτG ¡ xn... | [
"A1",
"A3",
"A2",
"All the same"
] | ['A3'] |
1450 | 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? | [
"more than k objects. We denote the set of k nearest neighbors as Nk(A). This distance is used to define what is called reachability distance: reachability-distance k ( A, B ) = max { k -distance ( B ), d ( A, B ) } {\\displaystyle {\\text{reachability-distance}}_{k}(A,B)=\\max\\{k{\\text{-distance}}(B),d(A,B)\\}} ... | [
"{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'] |
1451 | In User-Based Collaborative Filtering, which of the following is correct, assuming that all the ratings are positive? | [
"Instead, we want to embrace the collaborative aspect of sharing observations online with a digital community, and celebrate the healing power of nature as people document their local biodiversity to the best of their ability.\" This change remained in effect for following years. Results Reference: References Exter... | [
"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 v... | ['If the ratings of two users have both variance equal to 0, then their Cosine Similarity is maximized'] |
1452 | The term frequency of a term is normalized | [
"M F T | M F T ⟩ {\\displaystyle {\\mathcal {N}}={\\frac {\\left\\langle \\mathrm {MFT} \\right|\\left.\\mathrm {RPA} \\right\\rangle }{\\left\\langle \\mathrm {MFT} \\right|\\left.\\mathrm {MFT} \\right\\rangle }}} The normalization can be calculated by ⟨ R P A | R P A ⟩ = N 2 ⟨ M F T | e z i ( q ~ i ) 2 / 2 e z j... | [
"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 |
1454 | Which is an appropriate method for fighting skewed distributions of class labels in classification? | [
"model based on the sample-label pair: (xt, yt). Recently, a new learning paradigm called progressive learning technique has been developed. The progressive learning technique is capable of not only learning from new samples but also capable of learning new classes of data and yet retain the knowledge learnt thus f... | [
"Include an over-proportional number of samples from the larger class",
"Use leave-one-out cross validation",
"Construct the validation set such that the class label distribution approximately matches the global distribution of the class labels",
"Generate artificial data points for the most frequent classes"... | ['Use leave-one-out cross validation', 'Construct the validation set such that the class label distribution approximately matches the global distribution of the class labels'] |
1456 | Thang, Jeremie and Tugrulcan have built their own search engines. For a query Q, they got precision scores of 0.6, 0.7, 0.8 respectively. Their F1 scores (calculated by same parameters) are same. Whose search engine has a higher recall on Q? | [
"PageRank (PR) is an algorithm used by Google Search to rank web pages in their search engine results. It is named after both the term \"web page\" and co-founder Larry Page. PageRank is a way of measuring the importance of website pages. According to Google: PageRank works by counting the number and quality of lin... | [
"Thang",
"Jeremie",
"Tugrulcan",
"We need more information"
] | ['Thang', 'Tugrulcan'] |
1458 | When compressing the adjacency list of a given URL, a reference list | [
"ots \\\\\\$vdots &&\\ell (p_{i},p_{j})&$ell (p_{N},p_{1})&\\cdots &&\\ell (p_{N},p_{N})\\end{bmatrix}}\\mathbf {R} } where the adjacency function l ( p i, p j ) {\\displaystyle \\ell (p_{i},p_{j})} is the ratio between number of links outbound from page j to page i to the total number of outbound links of page j. ... | [
"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
|
1461 | Data being classified as unstructured or structured depends on the: | [
"Structured data analysis is the statistical data analysis of structured data. This can arise either in the form of an a priori structure such as multiple-choice questionnaires or in situations with the need to search for structure that fits the given data, either exactly or approximately. This structure can then b... | [
"Degree of abstraction",
"Level of human involvement",
"Type of physical storage",
"Amount of data "
] | ['Degree of abstraction'] |
1462 | With negative sampling a set of negative samples is created for
| [
"In statistics, non-sampling error is a catch-all term for the deviations of estimates from their true values that are not a function of the sample chosen, including various systematic errors and random errors that are not due to sampling. Non-sampling errors are much harder to quantify than sampling errors. Non-sa... | [
"For each word of the vocabulary",
"For each word-context pair",
"For each occurrence of a word in the text",
"For each occurrence of a word-context pair in the text",
""
] | For each occurrence of a word-context pair in the text
|
1463 | 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? | [
"versions). A pair d i {\\displaystyle d_{i}} and d j {\\displaystyle d_{j}} is concordant if both r a {\\displaystyle r_{a}} and r b {\\displaystyle r_{b}} agree in how they order d i {\\displaystyle d_{i}} and d j {\\displaystyle d_{j}}. It is discordant if they disagree. Information retrieval quality Information... | [
"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'] |
1465 | In the χ2 statistics for a binary feature, we obtain P(χ2 | DF = 1) > 0.05. This means in this case, it is assumed: | [
"P4 metric (also known as FS or Symmetric F ) enables performance evaluation of the binary classifier. It is calculated from precision, recall, specificity and NPV (negative predictive value). P4 is designed in similar way to F1 metric, however addressing the criticisms leveled against F1. It may be perceived as it... | [
"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 |
1467 | Which of the following is correct regarding the use of Hidden Markov Models (HMMs) for entity recognition in text documents? | [
"genomes of unculturable bacteria) based on a model of already labeled data. Hidden Markov models Hidden Markov models (HMMs) are a class of statistical models for sequential data (often related to systems evolving over time). An HMM is composed of two mathematical objects: an observed state‐dependent process X 1, ... | [
"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 prev... | ['An HMM model can be built using words enhanced with morphological features as input.'] |
1468 | 10 itemsets out of 100 contain item A, of which 5 also contain B. The rule A -> B has: | [
"d a A B A B a long a A and B are disjoint set or more generally A A Am A A Am when Ai Aj for all i j The case where the set have element in common is di erent Combining the Sum and Product Rule Example Suppose variable name in a programming language can be either a single letter or a letter followed by a digit Fin... | [
"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 |
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