COMPLEXITY - Carlos Eduardo Maldonado
... complexity of the best algorithm solving that problem A problem is tractable (or easy) if there exists a Ptime algorithm to solve it A problem is intractable (or difficult) if no P-time algorithm exists to solve the problem C/A complexity theory of problems deals with decision problems. A deci ...
... complexity of the best algorithm solving that problem A problem is tractable (or easy) if there exists a Ptime algorithm to solve it A problem is intractable (or difficult) if no P-time algorithm exists to solve the problem C/A complexity theory of problems deals with decision problems. A deci ...
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... terms, and other domain-specific words and phrases as they are used in a specific scientific or technical context relevant to grades 6–8 texts and topics. Integration of Knowledge and Ideas • Integrate quantitative or technical information expressed in words in a text with a version of that informa ...
... terms, and other domain-specific words and phrases as they are used in a specific scientific or technical context relevant to grades 6–8 texts and topics. Integration of Knowledge and Ideas • Integrate quantitative or technical information expressed in words in a text with a version of that informa ...
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... It is interesting to note that although integer factorization and discrete logarithms cannot be solved in polynomial-time on a classical digital computer, they all can be solved in polynomial-time on a quantum computer, provided that a practical quantum computer with several thousand quantum bits ca ...
... It is interesting to note that although integer factorization and discrete logarithms cannot be solved in polynomial-time on a classical digital computer, they all can be solved in polynomial-time on a quantum computer, provided that a practical quantum computer with several thousand quantum bits ca ...
CS4618 - Computer Science
... Lecturer(s): Staff, Department of Computer Science Module Objective: Students will explore the state of the art in Artificial Intelligence (AI). Module Content: Topics will be selected from the following and others: advanced AI search; natural language processing; randomised search heuristics (e.g., ...
... Lecturer(s): Staff, Department of Computer Science Module Objective: Students will explore the state of the art in Artificial Intelligence (AI). Module Content: Topics will be selected from the following and others: advanced AI search; natural language processing; randomised search heuristics (e.g., ...
CS 446-546 Syllabus v0 5a
... Additional learning outcomes for CS546 students: 5. critically read and understand research articles that describe the use of computational network analysis in life sciences applications; 6. design a computational workflow to analyze a given biological network using established algorithms (see outco ...
... Additional learning outcomes for CS546 students: 5. critically read and understand research articles that describe the use of computational network analysis in life sciences applications; 6. design a computational workflow to analyze a given biological network using established algorithms (see outco ...
A short survey of automated reasoning
... However, it seems at present that neither a systematic algorithmic approach nor a heuristic human-oriented approach is capable of proving a wide range of difficult mathematical theorems automatically. Besides, one might object that even if it were possible, it is hardly desirable to automate proofs ...
... However, it seems at present that neither a systematic algorithmic approach nor a heuristic human-oriented approach is capable of proving a wide range of difficult mathematical theorems automatically. Besides, one might object that even if it were possible, it is hardly desirable to automate proofs ...
DISCOURSE LEARNING: Learning I
... the discourse level, and dialogue acts can also be useful for other applications, such as resolving ambiguity in speech recognition. But, often, a dialogue act cannot be directly inferred from a literal reading of an utterance. Machine learning offers promise as a means of discovering patterns in co ...
... the discourse level, and dialogue acts can also be useful for other applications, such as resolving ambiguity in speech recognition. But, often, a dialogue act cannot be directly inferred from a literal reading of an utterance. Machine learning offers promise as a means of discovering patterns in co ...
Theoretical computer science
Theoretical computer science is a division or subset of general computer science and mathematics that focuses on more abstract or mathematical aspects of computing and includes the theory of computation.It is not easy to circumscribe the theory areas precisely and the ACM's Special Interest Group on Algorithms and Computation Theory (SIGACT) describes its mission as the promotion of theoretical computer science and notes:Template:""To this list, the ACM's journal Transactions on Computation Theory adds coding theory, computational learning theory and theoretical computer science aspects of areas such as databases, information retrieval, economic models and networks. Despite this broad scope, the ""theory people"" in computer science self-identify as different from the ""applied people."" Some characterize themselves as doing the ""(more fundamental) 'science(s)' underlying the field of computing."" Other ""theory-applied people"" suggest that it is impossible to separate theory and application. This means that the so-called ""theory people"" regularly use experimental science(s) done in less-theoretical areas such as software system research. It also means that there is more cooperation than mutually exclusive competition between theory and application.