Fetching the paper…
Reading the bibliography…
The following problem is considered: given a joint distribution $P_{XY}$ and an event $E$, bound $P_{XY}(E)$ in terms of $P_XP_Y(E)$ (where $P_XP_Y$ is the product of the marginals of $P_{XY}$) and a measure of dependence of $X$ and $Y$.
J. P. Ioannidis, “Why most published research findings are false,” PLoS medicine , vol. 2, no. 8, p. e124, 2005
2005
Earlier work this paper cites.
D. P. Palomar and S. Verdú, “Lautum information,” IEEE transactions on information theory , vol. 54, no. 3, pp. 964–975, 2008
2008
Earlier work this paper cites.
C. Braun, K. Chatzikokolakis, and C. Palamidessi, “Quantitative notions of leakage for one-try attacks,” Electronic Notes in Theoretical Computer Science , vol. 249, pp. 75–91, 2009
2009
Earlier work this paper cites.
S. Shalev-Shwartz, O. Shamir, N. Srebro, and K. Sridharan, “Learnability, stability and uniform convergence,” Journal of Machine Learning Research , vol. 11, no. Oct, pp. 2635–2670, 2010
2010
Earlier work this paper cites.
J. P. Simmons, L. D. Nelson, and U. Simonsohn, “False-positive psychology: Undisclosed flexibility in data collection and analysis allows presenting anything as significant,” Psychological science , vol. 22, no. 11, pp. 1359–1366, 2011
2011
Earlier work this paper cites.
S. Boucheron, G. Lugosi, and P. Massart, Concentration inequalities: A nonasymptotic theory of independence . Oxford university press, 2013
2013
Earlier work this paper cites.
M. Hardt and J. Ullman, “Preventing false discovery in interactive data analysis is hard,” in Foundations of Computer Science (FOCS), 2014 IEEE 55th Annual Symposium on . IEEE, 2014, pp. 454–463
2014
Cited alongside, same era.
T. van Erven and P. Harremos, “Rényi divergence and Kullback-Leibler divergence,” IEEE Trans. Inf. Theory , vol. 60, no. 7, pp. 3797–3820, July 2014
2014
Cited alongside, same era.
C. Dwork, V. Feldman, M. Hardt, T. Pitassi, O. Reingold, and A. L. Roth, “Preserving statistical validity in adaptive data analysis,” in Proceedings of the forty-seventh annual ACM symposium on Theory of computing . ACM, 2015, pp. 117–126
2015
Cited alongside, same era.
2015
Cited alongside, same era.
I. Issa, S. Kamath, and A. B. Wagner, “An operational measure of information leakage,” in Proc. of 50th Ann. Conf. on Information Sciences and Systems (CISS) , Mar. 2016
2016
Later among the works it cites.
2017
Later among the works it cites.
J. Jiao, Y. Han, and T. Weissman, “Dependence measures bounding the exploration bias for general measurements,” in Proc. IEEE Int. Symp. Inf. Theory (ISIT) . IEEE, June 2017, pp. 1475–1479
2017
Later among the works it cites.
2017
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
R. Bassily, K. Nissim, A. Smith, T. Steinke, U. Stemmer, and J. Ullman, “Algorithmic Stability for Adaptive Data Analysis,” ArXiv e-prints , Nov. 2015
2015
Cited alongside, same era.
D. Russo and J. Zou, “Controlling bias in adaptive data analysis using information theory,” in Artificial Intelligence and Statistics , 2016, pp. 1232–1240
2016
Cited alongside, same era.
2018
Later among the works it cites.
R. Bassily, S. Moran, I. Nachum, J. Shafer, and A. Yehudayoff, “Learners that use little information,” in Proceedings of Algorithmic Learning Theory , ser. Proceedings of Machine Learning Research, F. Janoos, M. Mohri, and K. Sridharan, Eds., vol. 83. PMLR, 07–09 Apr 2018, pp. 25–55. [Online]. Available: http://proceedings.mlr.press/v83/bassily18a.html
2018
Later among the works it cites.