{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T10:12:09Z","timestamp":1730283129076,"version":"3.28.0"},"reference-count":27,"publisher":"IEEE","license":[{"start":{"date-parts":[[2023,9,17]],"date-time":"2023-09-17T00:00:00Z","timestamp":1694908800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,9,17]],"date-time":"2023-09-17T00:00:00Z","timestamp":1694908800000},"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":[[2023,9,17]]},"DOI":"10.1109\/mlsp55844.2023.10285901","type":"proceedings-article","created":{"date-parts":[[2023,10,23]],"date-time":"2023-10-23T13:55:41Z","timestamp":1698069341000},"page":"1-6","source":"Crossref","is-referenced-by-count":0,"title":["Predicting Generalization in Deep Learning Using Data Augmentation and posterior Probability Estimators"],"prefix":"10.1109","author":[{"given":"Parisa","family":"Ghane","sequence":"first","affiliation":[{"name":"Texas A&M University,College Station,Department of Electrical and Computer Engineering,Texas,United States"}]},{"given":"Ulisses","family":"Braga-Neto","sequence":"additional","affiliation":[{"name":"Texas A&M University,College Station,Department of Electrical and Computer Engineering,Texas,United States"}]}],"member":"263","reference":[{"journal-title":"A study of Generalization in Deep Neural Networks","year":"2021","author":"madala","key":"ref13"},{"key":"ref12","first-page":"11723","article-title":"In search of robust measures of generalization","volume":"33","author":"dziugaite","year":"2020","journal-title":"Advances in neural information processing systems"},{"key":"ref15","article-title":"A pac-bayesian approach to spectrally-normalized margin bounds for neural networks","author":"neyshabur","year":"2017","journal-title":"arXiv preprint arXiv 1707 09562"},{"key":"ref14","article-title":"Computing nonvacuous generalization bounds for deep (stochastic) neural networks with many more parameters than training data","author":"dziugaite","year":"2017","journal-title":"arXiv preprint arXiv 1703 11008"},{"key":"ref11","article-title":"Robustness to augmentations as a generalization metric","author":"aithal","year":"2021","journal-title":"CoRR abs\/2101 06459"},{"key":"ref10","article-title":"Uncertainty quantification and deep ensembles","volume":"34","author":"rahaman","year":"2021","journal-title":"Advances in neural information processing systems"},{"key":"ref2","article-title":"Towards understanding the role of over-parametrization in generalization of neural networks","author":"neyshabur","year":"2018","journal-title":"arXiv preprint arXiv 1805 12076"},{"key":"ref1","article-title":"Do imagenet classifiers generalize to imagenet?","author":"recht","year":"2019","journal-title":"arXiv preprint arXiv 1902 10869"},{"key":"ref17","article-title":"Deterministic pac-bayesian generalization bounds for deep networks via generalizing noise-resilience","author":"nagarajan","year":"2019","journal-title":"arXiv preprint arXiv 1905 13378"},{"key":"ref16","article-title":"Spectrally-normalized margin bounds for neural networks","volume":"30","author":"bartlett","year":"2017","journal-title":"Advances in neural information processing systems"},{"key":"ref19","article-title":"Neurips 2020 competition: Predicting generalization in deep learning","author":"jiang","year":"2020","journal-title":"2012 arXiv preprint arXiv"},{"key":"ref18","article-title":"Predicting the generalization gap in deep networks with margin distributions","author":"jiang","year":"2018","journal-title":"arXiv preprint arXiv 1810 00069"},{"key":"ref24","article-title":"Fashionmnist: a novel image dataset for benchmarking machine learning algorithms","volume":"abs 1708 7747","author":"xiao","year":"2017","journal-title":"CoRR"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2012.6248092"},{"key":"ref26","article-title":"Robustness to augmentations as a generalization metric","author":"kashyap","year":"2021","journal-title":"arXiv preprint arXiv 2101 06286"},{"key":"ref25","article-title":"Representation based complexity measures for predicting generalization in deep learning","author":"natekar","year":"2020","journal-title":"2012 arXiv preprint arXiv"},{"journal-title":"Learning multiple layers of features from tiny images","year":"2009","author":"krizhevsky","key":"ref20"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ICVGIP.2008.47"},{"article-title":"Reading digits in natural images with unsupervised feature learning","year":"2011","author":"netzer","key":"ref21"},{"key":"ref27","article-title":"Ranking deep learning generalization using label variation in latent geometry graphs","author":"lassance","year":"2020","journal-title":"arXiv preprint arXiv 2011 12460"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2003.08.017"},{"key":"ref7","first-page":"170","article-title":"Methods and analysis of the first competition in predicting generalization of deep learning","author":"jiang","year":"2021","journal-title":"NeurIPS 2020 Competition and Demonstration Track"},{"key":"ref9","article-title":"Generalized re-substitution for classification error estimation","author":"ghane","year":"2021","journal-title":"arXiv preprint arXiv 2110 11223"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00275"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/3446776"},{"key":"ref6","article-title":"Fantastic generalization measures and where to find them","author":"jiang","year":"2019","journal-title":"arXiv preprint arXiv 1912 02178"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1186\/s40537-023-00727-2"}],"event":{"name":"2023 IEEE 33rd International Workshop on Machine Learning for Signal Processing (MLSP)","start":{"date-parts":[[2023,9,17]]},"location":"Rome, Italy","end":{"date-parts":[[2023,9,20]]}},"container-title":["2023 IEEE 33rd International Workshop on Machine Learning for Signal Processing (MLSP)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10285838\/10285858\/10285901.pdf?arnumber=10285901","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,13]],"date-time":"2023-11-13T14:03:26Z","timestamp":1699884206000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10285901\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,9,17]]},"references-count":27,"URL":"https:\/\/doi.org\/10.1109\/mlsp55844.2023.10285901","relation":{},"subject":[],"published":{"date-parts":[[2023,9,17]]}}}