{"list":"other","total":79,"rows":[{"id":"1502.03167","title":"Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift","created":"2015-02-11","cited_by_count":7005},{"id":"1706.06083","title":"Towards Deep Learning Models Resistant to Adversarial Attacks","created":"2017-06-19","cited_by_count":6415},{"id":"2003.01690","title":"Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks","created":"2020-03-03","cited_by_count":1451},{"id":"1609.04836","title":"On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima","created":"2016-09-15","cited_by_count":1352},{"id":"1902.02918","title":"Certified Adversarial Robustness via Randomized Smoothing","created":"2019-02-08","cited_by_count":1340},{"id":"1802.00420","title":"Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples","created":"2018-02-01","cited_by_count":1268},{"id":"1705.07204","title":"Ensemble Adversarial Training: Attacks and Defenses","created":"2017-05-19","cited_by_count":840},{"id":"1312.6120","title":"Exact solutions to the nonlinear dynamics of learning in deep linear neural networks","created":"2013-12-20","cited_by_count":763},{"id":"1702.01135","title":"Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks","created":"2017-02-03","cited_by_count":744},{"id":"1706.08498","title":"Spectrally-normalized margin bounds for neural networks","created":"2017-06-26","cited_by_count":686},{"id":"1511.04508","title":"Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks","created":"2015-11-14","cited_by_count":678},{"id":"1706.08947","title":"Exploring Generalization in Deep Learning","created":"2017-06-27","cited_by_count":600},{"id":"1711.00851","title":"Provable defenses against adversarial examples via the convex outer adversarial polytope","created":"2017-11-02","cited_by_count":567},{"id":"1703.11008","title":"Computing Nonvacuous Generalization Bounds for Deep (Stochastic) Neural Networks with Many More Parameters than Training Data","created":"2017-03-31","cited_by_count":533},{"id":"1912.02178","title":"Fantastic Generalization Measures and Where to Find Them","created":"2019-12-04","cited_by_count":513},{"id":"1704.01155","title":"Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks","created":"2017-04-04","cited_by_count":486},{"id":"1802.03471","title":"Certified Robustness to Adversarial Examples with Differential Privacy","created":"2018-02-09","cited_by_count":468},{"id":"1906.04584","title":"Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers","created":"2019-06-09","cited_by_count":330},{"id":"1707.09564","title":"A PAC-Bayesian Approach to Spectrally-Normalized Margin Bounds for Neural Networks","created":"2017-07-29","cited_by_count":314},{"id":"1802.05666","title":"Adversarial Risk and the Dangers of Evaluating Against Weak Attacks","created":"2018-02-15","cited_by_count":221},{"id":"1705.10941","title":"Spectral Norm Regularization for Improving the Generalizability of Deep Learning","created":"2017-05-31","cited_by_count":182},{"id":"1809.03113","title":"Certified Adversarial Robustness with Additive Noise","created":"2018-09-10","cited_by_count":180},{"id":"2002.05990","title":"Skip Connections Matter: On the Transferability of Adversarial Examples Generated with ResNets","created":"2020-02-14","cited_by_count":167},{"id":"2002.08118","title":"Randomized Smoothing of All Shapes and Sizes","created":"2020-02-19","cited_by_count":147},{"id":"1805.12514","title":"Scaling provable adversarial defenses","created":"2018-05-31","cited_by_count":143},{"id":"1511.06422","title":"All you need is a good init","created":"2015-11-19","cited_by_count":124},{"id":"1506.04091","title":"On the properties of variational approximations of Gibbs posteriors","created":"2015-06-12","cited_by_count":121},{"id":"2003.08904","title":"RAB: Provable Robustness Against Backdoor Attacks","created":"2020-03-19","cited_by_count":118},{"id":"2006.14768","title":"Deep Partition Aggregation: Provable Defense against General Poisoning Attacks","created":"2020-06-26","cited_by_count":115},{"id":"2001.02378","title":"MACER: Attack-free and Scalable Robust Training via Maximizing Certified Radius","created":"2020-01-08","cited_by_count":114},{"id":"2007.12911","title":"Tighter risk certificates for neural networks","created":"2020-07-25","cited_by_count":112},{"id":"2002.03018","title":"Certified Robustness to Label-Flipping Attacks via Randomized Smoothing","created":"2020-02-07","cited_by_count":108},{"id":"2002.10733","title":"(De)Randomized Smoothing for Certifiable Defense against Patch Attacks","created":"2020-02-25","cited_by_count":98},{"id":"1805.10408","title":"The Singular Values of Convolutional Layers","created":"2018-05-26","cited_by_count":95},{"id":"2008.04495","title":"Intrinsic Certified Robustness of Bagging against Data Poisoning Attacks","created":"2020-08-11","cited_by_count":94},{"id":"2106.08283","title":"CRFL: Certifiably Robust Federated Learning against Backdoor Attacks","created":"2021-06-15","cited_by_count":91},{"id":"1909.01492","title":"Achieving Verified Robustness to Symbol Substitutions via Interval Bound Propagation","created":"2019-09-03","cited_by_count":88},{"id":"1712.09376","title":"Entropy-SGD optimizes the prior of a PAC-Bayes bound: Generalization properties of Entropy-SGD and data-dependent priors","created":"2017-12-26","cited_by_count":81},{"id":"2010.11924","title":"In Search of Robust Measures of Generalization","created":"2020-10-22","cited_by_count":79},{"id":"2211.13609","title":"PAC-Bayes Compression Bounds So Tight That They Can Explain Generalization","created":"2022-11-24","cited_by_count":76},{"id":"1811.07457","title":"Generalizable Adversarial Training via Spectral Normalization","created":"2018-11-19","cited_by_count":68},{"id":"1906.04948","title":"Tight Certificates of Adversarial Robustness for Randomly Smoothed Classifiers","created":"2019-06-12","cited_by_count":65},{"id":"2006.10929","title":"On the role of data in PAC-Bayes bounds","created":"2020-06-19","cited_by_count":64},{"id":"2006.13057","title":"PAC-Bayes Analysis Beyond the Usual Bounds","created":"2020-06-23","cited_by_count":63},{"id":"2008.10715","title":"Certified Robustness of Graph Neural Networks against Adversarial Structural Perturbation","created":"2020-08-24","cited_by_count":57},{"id":"2002.03239","title":"Curse of Dimensionality on Randomized Smoothing for Certifiable Robustness","created":"2020-02-08","cited_by_count":56},{"id":"2008.12952","title":"Efficient Robustness Certificates for Discrete Data: Sparsity-Aware Randomized Smoothing for Graphs, Images and More","created":"2020-08-29","cited_by_count":56},{"id":"1608.05610","title":"A Strongly Quasiconvex PAC-Bayesian Bound","created":"2016-08-19","cited_by_count":54},{"id":"1912.09899","title":"Certified Robustness for Top-k Predictions against Adversarial Perturbations via Randomized Smoothing","created":"2019-12-20","cited_by_count":54},{"id":"2002.12463","title":"Certified Defense to Image Transformations via Randomized Smoothing","created":"2020-02-27","cited_by_count":51},{"id":"1503.08329","title":"Risk Bounds for the Majority Vote: From a PAC-Bayesian Analysis to a Learning Algorithm","created":"2015-03-28","cited_by_count":50},{"id":"2002.12398","title":"TSS: Transformation-Specific Smoothing for Robustness Certification","created":"2020-02-27","cited_by_count":49},{"id":"2103.03046","title":"PointGuard: Provably Robust 3D Point Cloud Classification","created":"2021-03-04","cited_by_count":49},{"id":"2007.03730","title":"Detection as Regression: Certified Object Detection by Median Smoothing","created":"2020-07-07","cited_by_count":47},{"id":"2106.06946","title":"Boosting Randomized Smoothing with Variance Reduced Classifiers","created":"2021-06-13","cited_by_count":47},{"id":"2002.09169","title":"Black-Box Certification with Randomized Smoothing: A Functional Optimization Based Framework","created":"2020-02-21","cited_by_count":46},{"id":"2203.06020","title":"Enhancing Adversarial Training with Second-Order Statistics of Weights","created":"2022-03-11","cited_by_count":42},{"id":"1905.10259","title":"Dichotomize and Generalize: PAC-Bayesian Binary Activated Deep Neural Networks","created":"2019-05-24","cited_by_count":38},{"id":"2010.06651","title":"Higher-Order Certification for Randomized Smoothing","created":"2020-10-13","cited_by_count":37},{"id":"2012.04351","title":"Data-Dependent Randomized Smoothing","created":"2020-12-08","cited_by_count":37},{"id":"2009.08061","title":"Certifying Confidence via Randomized Smoothing","created":"2020-09-17","cited_by_count":36},{"id":"2107.00228","title":"Scalable Certified Segmentation via Randomized Smoothing","created":"2021-07-01","cited_by_count":35},{"id":"2010.05983","title":"How does Weight Correlation Affect the Generalisation Ability of Deep Neural Networks","created":"2020-10-12","cited_by_count":32},{"id":"2006.13508","title":"A Limitation of the PAC-Bayes Framework","created":"2020-06-24","cited_by_count":25},{"id":"2206.04310","title":"GSmooth: Certified Robustness against Semantic Transformations via Generalized Randomized Smoothing","created":"2022-06-09","cited_by_count":23},{"id":"2206.00024","title":"Online PAC-Bayes Learning","created":"2022-05-31","cited_by_count":22},{"id":"2207.00614","title":"Integral Probability Metrics PAC-Bayes Bounds","created":"2022-07-01","cited_by_count":19},{"id":"2107.00996","title":"DeformRS: Certifying Input Deformations with Randomized Smoothing","created":"2021-07-02","cited_by_count":17},{"id":"2302.02829","title":"Collective Robustness Certificates: Exploiting Interdependence in Graph Neural Networks","created":"2023-02-06","cited_by_count":16},{"id":"2012.01274","title":"How Robust are Randomized Smoothing based Defenses to Data Poisoning?","created":"2020-12-02","cited_by_count":15},{"id":"2102.11069","title":"A PAC-Bayes Analysis of Adversarial Robustness","created":"2021-02-19","cited_by_count":13},{"id":"2009.05872","title":"Certified Robustness of Graph Classification against Topology Attack with Randomized Smoothing","created":"2020-09-12","cited_by_count":12},{"id":"2112.12084","title":"Input-Specific Robustness Certification for Randomized Smoothing","created":"2021-12-21","cited_by_count":11},{"id":"2206.00706","title":"Split-kl and PAC-Bayes-split-kl Inequalities for Ternary Random Variables","created":"2022-06-01","cited_by_count":11},{"id":"2501.13273","title":"Enhancing Robust Fairness via Confusional Spectral Regularization","created":"2025-01-22","cited_by_count":11},{"id":"2207.02152","title":"UniCR: Universally Approximated Certified Robustness via Randomized Smoothing","created":"2022-07-05","cited_by_count":10},{"id":"2210.11289","title":"Tighter PAC-Bayes Generalisation Bounds by Leveraging Example Difficulty","created":"2022-10-20","cited_by_count":9},{"id":"2211.14207","title":"Invariance-Aware Randomized Smoothing Certificates","created":"2022-11-25","cited_by_count":7},{"id":"2212.11746","title":"Certified Policy Smoothing for Cooperative Multi-Agent Reinforcement Learning","created":"2022-12-22","cited_by_count":7}],"next_cursor":null}