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Models of Distribution Testing

Note: the information here is (always) incomplete and updated often
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Closeness Distance :

Farness Distance :

Bound :

Query Complexity of Model vs Model setup
SAMP DUAL PAIRCOND SUBCOND COND
SAMP  
DUAL    
PAIRCOND      
SUBCOND        
COND          
FULL          
Maintained by: Uddalok Sarkar and Yash Pote

 

References

  1. Testing Closeness of Discrete Distributions [ ArXiv | ]
    @article{batu2013testing, title={Testing closeness of discrete distributions}, author={Batu, Tu{\u{g}}kan and Fortnow, Lance and Rubinfeld, Ronitt and Smith, Warren D and White, Patrick}, journal={Journal of the ACM (JACM)}, volume={60}, number={1}, pages={1--25}, year={2013}, publisher={ACM New York, NY, USA} }
  2. An Automatic Inequality Prover and Instance Optimal Identity Testing [ ArXiv | ]
    @article{valiant2017automatic, title={An Automatic Inequality Prover and Instance Optimal Identity Testing}, author = {Gregory Valiant and Paul Valiant}, journal={{SIAM} J. Comput.}, volume = {46}, number = {1}, pages = {429--455}, year = {2017} }
  3. On Distribution Testing in the Conditional Sampling Model [ ArXiv | ]
    @article{narayanan2020distribution, author = {Shyam Narayanan}, title = {Tolerant Distribution Testing in the Conditional Sampling Model}, journal = {CoRR}, volume = {abs/2007.09895}, year = {2020} }
  4. Property Testing of Joint Distributions using Conditional Samples [ ArXiv | ]
    @article{bhattacharyya2018property, author = {Rishiraj Bhattacharyya and Sourav Chakraborty}, title = {Property Testing of Joint Distributions using Conditional Samples}, journal = {CoRR}, volume = {abs/1702.01454}, year = {2017} }
  5. Testing Bayesian Networks [ ArXiv | ]
    @inproceedings{canonne2017testing, title={Testing bayesian networks}, author={Canonne, Cl{\'e}ment L and Diakonikolas, Ilias and Kane, Daniel M and Stewart, Alistair}, booktitle={Conference on Learning Theory}, pages={370--448}, year={2017}, organization={PMLR} }
  6. Testing probability distributions using conditional samples [ ArXiv | ]
    @article{canonne2015testing, title={Testing probability distributions using conditional samples}, author={Canonne, Cl{\'e}ment L and Ron, Dana and Servedio, Rocco A}, journal={SIAM Journal on Computing}, volume={44}, number={3}, pages={540--616}, year={2015}, publisher={SIAM} }
  7. On the power of conditional samples in distribution testing [ ArXiv | ]
    @inproceedings{chakraborty2013power, title={On the power of conditional samples in distribution testing}, author={Chakraborty, Sourav and Fischer, Eldar and Goldhirsh, Yonatan and Matsliah, Arie}, booktitle={Proceedings of the 4th conference on Innovations in Theoretical Computer Science}, pages={561--580}, year={2013} }
  8. On Scalable Testing of Samplers [ OpenReview | ]
    @inproceedings{potescalable, title={On Scalable Testing of Samplers}, author={Pote, Yash and Meel, Kuldeep S}, booktitle={Advances in Neural Information Processing Systems} }
  9. Faster Algorithms for Testing under Conditional Sampling [ PMLR | ]
    @inproceedings{falahatgar2015faster, title={Faster algorithms for testing under conditional sampling}, author={Falahatgar, Moein and Jafarpour, Ashkan and Orlitsky, Alon and Pichapati, Venkatadheeraj and Suresh, Ananda Theertha}, booktitle={Conference on Learning Theory}, pages={607--636}, year={2015}, organization={PMLR} }