Algorithms (with Sanjoy Dasgupta and Umesh Vazirani)

Target entity: Algorithms (with Sanjoy Dasgupta and Umesh Vazirani)
Context triple: [Christos H. Papadimitriou, notableWork, Algorithms (with Sanjoy Dasgupta and Umesh Vazirani)]

• A. Introduction to Algorithms
  Introduction to Algorithms is a widely used, comprehensive textbook on algorithms and data structures, renowned for its rigorous yet accessible coverage of theoretical and practical topics in computer science.
• B. Probably Approximately Correct learning (PAC learning)
  Probably Approximately Correct (PAC) learning is a foundational framework in computational learning theory that formalizes what it means for an algorithm to efficiently learn a concept from examples with high probability and small error.
• C. The Design and Analysis of Computer Algorithms
  The Design and Analysis of Computer Algorithms is a classic computer science textbook that systematically presents fundamental techniques and theoretical foundations for designing and analyzing efficient algorithms.
• D. P, NP, and NP-Completeness: The Basics of Complexity Theory
  "P, NP, and NP-Completeness: The Basics of Complexity Theory" is a foundational textbook by Oded Goldreich that introduces the core concepts, problems, and techniques of computational complexity theory, with a focus on the classes P, NP, and NP-complete problems.
• E. Papadimitriou: Computational Complexity
  "Papadimitriou: Computational Complexity" is a widely used graduate-level textbook that systematically develops the theory of computational complexity, including classes like P and NP and the foundations of NP-completeness.
• F. None of above. chosen
• G. Unsure - the case is ambiguous/there is not enough information to decide.

Target entity: Algorithms (with Sanjoy Dasgupta and Umesh Vazirani)
Target entity description: "Algorithms (with Sanjoy Dasgupta and Umesh Vazirani)" is a widely used introductory textbook that presents the design and analysis of algorithms with an emphasis on clarity, rigor, and practical applications in computer science.

• A. Introduction to Algorithms
  Introduction to Algorithms is a widely used, comprehensive textbook on algorithms and data structures, renowned for its rigorous yet accessible coverage of theoretical and practical topics in computer science.
• B. Probably Approximately Correct learning (PAC learning)
  Probably Approximately Correct (PAC) learning is a foundational framework in computational learning theory that formalizes what it means for an algorithm to efficiently learn a concept from examples with high probability and small error.
• C. The Design and Analysis of Computer Algorithms
  The Design and Analysis of Computer Algorithms is a classic computer science textbook that systematically presents fundamental techniques and theoretical foundations for designing and analyzing efficient algorithms.
• D. P, NP, and NP-Completeness: The Basics of Complexity Theory
  "P, NP, and NP-Completeness: The Basics of Complexity Theory" is a foundational textbook by Oded Goldreich that introduces the core concepts, problems, and techniques of computational complexity theory, with a focus on the classes P, NP, and NP-complete problems.
• E. Papadimitriou: Computational Complexity
  "Papadimitriou: Computational Complexity" is a widely used graduate-level textbook that systematically develops the theory of computational complexity, including classes like P and NP and the foundations of NP-completeness.
• F. None of above. chosen