Podcast
Questions and Answers
Which output model inspired by XOR games is studied in the text?
Which output model inspired by XOR games is studied in the text?
Which output model has no dependency on output size for error reduction?
Which output model has no dependency on output size for error reduction?
What is the cost of standard error reduction techniques in the XOR model?
What is the cost of standard error reduction techniques in the XOR model?
Which technique has a factor reduced to O(k) for randomness removal in XOR model?
Which technique has a factor reduced to O(k) for randomness removal in XOR model?
Signup and view all the answers
What is the cost of standard randomness removal techniques in the XOR model?
What is the cost of standard randomness removal techniques in the XOR model?
Signup and view all the answers
Which technique is used for weak output models?
Which technique is used for weak output models?
Signup and view all the answers
Study Notes
- Communication complexity of functions with large outputs varies depending on output model
- Variety of output models studied, including open model and XOR model inspired by XOR games
- Focus on error-reduction in new output models
- Standard error reduction techniques in XOR model have linear cost in output size
- No dependency on output size necessary for error reduction in XOR model
- Standard randomness removal techniques have multiplicative cost of 2k in XOR model
- Factor reduced to O(k) for randomness removal in XOR model
- Similar results shown for other output models
- Some natural problems separate the models when Hamming weights of inputs is bounded
- Rank lower bound technique used for weak output models.
Studying That Suits You
Use AI to generate personalized quizzes and flashcards to suit your learning preferences.
Description
Test your knowledge on communication complexity and output models with this quiz! Learn about the different output models studied, including the open model and XOR model inspired by XOR games. Discover how error-reduction plays a crucial role in new output models, and explore standard techniques for randomness removal and linear cost in output size. Find out how some natural problems separate the models when Hamming weights of inputs are bounded, and get familiar with rank lower bound techniques used for weak output models. Sharpen your expertise on this fascinating
