{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T07:22:43Z","timestamp":1774941763421,"version":"3.50.1"},"reference-count":29,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,11,1]],"date-time":"2022-11-01T00:00:00Z","timestamp":1667260800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,11,1]],"date-time":"2022-11-01T00:00:00Z","timestamp":1667260800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,11,1]]},"DOI":"10.1109\/itw54588.2022.9965850","type":"proceedings-article","created":{"date-parts":[[2022,12,7]],"date-time":"2022-12-07T15:47:00Z","timestamp":1670428020000},"page":"440-445","source":"Crossref","is-referenced-by-count":1,"title":["Formal limitations of sample-wise information-theoretic generalization bounds"],"prefix":"10.1109","author":[{"given":"Hrayr","family":"Harutyunyan","sequence":"first","affiliation":[{"name":"USC Information Sciences Institute"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Greg Ver","family":"Steeg","sequence":"additional","affiliation":[{"name":"USC Information Sciences Institute"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aram","family":"Galstyan","sequence":"additional","affiliation":[{"name":"USC Information Sciences Institute"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref10","first-page":"25","author":"bassily","year":"2018","journal-title":"Algorithmic Learning Theory"},{"key":"ref11","first-page":"11 015","article-title":"Information-theoretic generalization bounds for sgld via data-dependent estimates","author":"negrea","year":"2019","journal-title":"Advances in neural information processing systems"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/JSAIT.2020.2991139"},{"key":"ref13","first-page":"3437","article-title":"Reasoning About Generalization via Conditional Mutual Information","volume":"125","author":"steinke","year":"2020","journal-title":"Proceedings of Thirty Third Conference on Learning Theory"},{"key":"ref14","first-page":"9925","article-title":"Sharpened generalization bounds based on conditional mutual information and an application to noisy, iterative algorithms","volume":"33","author":"haghifam","year":"2020","journal-title":"Advances in neural information processing systems"},{"key":"ref15","article-title":"Information-theoretic generalization bounds for sgld via data-dependent estimates","author":"negrea","year":"2019","journal-title":"NeurIPS"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1017\/9781108616799.011"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/JSAIT.2020.3040992"},{"key":"ref18","article-title":"Information-theoretic generalization bounds for black-box learning algorithms","author":"harutyunyan","year":"2021","journal-title":"Advances in neural information processing systems"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2021.3085190"},{"key":"ref28","first-page":"1","article-title":"On random subset generalization error bounds and the stochastic gradient langevin dynamics algorithm","author":"g\u00e1lvez","year":"2021","journal-title":"2020 IEEE Information Theory Workshop (ITW)"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1145\/267460.267466"},{"key":"ref27","article-title":"Pac-bayes analysis beyond the usual bounds","volume":"abs 2006 13057","author":"rivasplata","year":"2020"},{"key":"ref3","first-page":"11 723","article-title":"In search of robust measures of generalization","volume":"33","author":"dziugaite","year":"2020","journal-title":"Advances in neural information processing systems"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/307400.307435"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/ISIT45174.2021.9518016"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1023\/A:1007618624809"},{"key":"ref8","article-title":"User-friendly introduction to pac-bayes bounds","author":"alquier","year":"2021"},{"key":"ref7","article-title":"Pac-bayesian supervised classification: The thermodynamics of statistical learning","volume":"56","author":"catoni","year":"2007","journal-title":"Lecture Notes-Monograph Series"},{"key":"ref2","article-title":"Fantastic generalization measures and where to find them","author":"jiang","year":"2020","journal-title":"International Conference on Learning Representations"},{"key":"ref9","first-page":"2524","article-title":"Information-theoretic analysis of generalization capability of learning algorithms","author":"xu","year":"2017","journal-title":"Advances in neural information processing systems"},{"key":"ref1","article-title":"Understanding deep learning requires rethinking generalization","author":"zhang","year":"2016"},{"key":"ref20","article-title":"Computing nonvacuous generalization bounds for deep (stochastic) neural networks with many more parameters than training data","author":"dziugaite","year":"2017","journal-title":"Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence UAI 2017 Sydney Australia August 11-15 2017"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ISIT45174.2021.9518043"},{"key":"ref21","article-title":"Tighter risk certificates for neural networks","volume":"22","author":"p\u00e9rez-ortiz","year":"2021","journal-title":"Journal of Machine Learning Research"},{"key":"ref24","article-title":"Tighter expected generalization error bounds via wasserstein distance","volume":"34","author":"rodr\u00edguez g\u00e1lvez","year":"2021","journal-title":"Advances in neural information processing systems"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ITW46852.2021.9457642"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1145\/1553374.1553419"},{"key":"ref25","article-title":"Bounds for averaging classifiers","author":"langford","year":"2001"}],"event":{"name":"2022 IEEE Information Theory Workshop (ITW)","location":"Mumbai, India","start":{"date-parts":[[2022,11,1]]},"end":{"date-parts":[[2022,11,9]]}},"container-title":["2022 IEEE Information Theory Workshop (ITW)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9965754\/9965755\/09965850.pdf?arnumber=9965850","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,26]],"date-time":"2022-12-26T14:42:23Z","timestamp":1672065743000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9965850\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,11,1]]},"references-count":29,"URL":"https:\/\/doi.org\/10.1109\/itw54588.2022.9965850","relation":{},"subject":[],"published":{"date-parts":[[2022,11,1]]}}}