Prescriptive analytics with differential privacy

[1]  Santu Rana,et al.  Scalable Backdoor Detection in Neural Networks , 2020, ECML/PKDD.

[2]  Dimitris Bertsimas,et al.  From Predictive to Prescriptive Analytics , 2014, Manag. Sci..

[3]  Santu Rana,et al.  Bayesian Optimization with Unknown Search Space , 2019, NeurIPS.

[4]  Jishen Zhao,et al.  DeepInspect: A Black-box Trojan Detection and Mitigation Framework for Deep Neural Networks , 2019, IJCAI.

[5]  Ben Y. Zhao,et al.  Neural Cleanse: Identifying and Mitigating Backdoor Attacks in Neural Networks , 2019, 2019 IEEE Symposium on Security and Privacy (SP).

[6]  Peng Liu,et al.  Multidimensional Correlation Hierarchical Differential Privacy for Medical Data with Multiple Privacy Requirements , 2018 .

[7]  Fang Liu,et al.  Generalized Gaussian Mechanism for Differential Privacy , 2016, IEEE Transactions on Knowledge and Data Engineering.

[8]  Svetha Venkatesh,et al.  Differentially Private Prescriptive Analytics , 2018, 2018 IEEE International Conference on Data Mining (ICDM).

[9]  Svetha Venkatesh,et al.  Prescriptive Analytics Through Constrained Bayesian Optimization , 2018, PAKDD.

[10]  Neil D. Lawrence,et al.  Differentially Private Regression with Gaussian Processes , 2018, AISTATS.

[11]  Benjamin Van Roy,et al.  A Tutorial on Thompson Sampling , 2017, Found. Trends Mach. Learn..

[12]  Philip S. Yu,et al.  $\textsf{LoPub}$ : High-Dimensional Crowdsourced Data Publication With Local Differential Privacy , 2016, IEEE Transactions on Information Forensics and Security.

[13]  Stefan Spinler,et al.  Prescriptive analytics in airline operations: Arrival time prediction and cost index optimization for short-haul flights , 2018 .

[14]  Roger N. Anderson.  'Petroleum Analytics Learning Machine' for optimizing the Internet of Things of today's digital oil field-to-refinery petroleum system , 2017, 2017 IEEE International Conference on Big Data (Big Data).

[15]  Pei-Ju Wu,et al.  The green fleet optimization model for a low-carbon economy: A prescriptive analytics , 2017, 2017 International Conference on Applied System Innovation (ICASI).

[16]  William Nick Street,et al.  Generalized Inverse Classification , 2016, SDM.

[17]  William Nick Street,et al.  A Budget-Constrained Inverse Classification Framework for Smooth Classifiers , 2016, 2017 IEEE International Conference on Data Mining Workshops (ICDMW).

[18]  Svetha Venkatesh,et al.  Extracting Key Challenges in Achieving Sobriety Through Shared Subspace Learning , 2016, ADMA.

[19]  Svetha Venkatesh,et al.  Understanding Behavioral Differences Between Short and Long-Term Drinking Abstainers from Social Media , 2016, ADMA.

[20]  Andreas Wespi,et al.  Security 360°: Enterprise security for the cognitive era , 2016, IBM J. Res. Dev..

[21]  Neil D. Lawrence,et al.  Differentially Private Gaussian Processes , 2016, ArXiv.

[22]  Tarun Kumar,et al.  Asset health management using predictive and prescriptive analytics for the electric power grid , 2016, IBM J. Res. Dev..

[23]  Nando de Freitas,et al.  Taking the Human Out of the Loop: A Review of Bayesian Optimization , 2016, Proceedings of the IEEE.

[24]  Svetha Venkatesh,et al.  Differentially Private Random Forest with High Utility , 2015, 2015 IEEE International Conference on Data Mining.

[25]  Sungho Shin,et al.  Design of Marketing Scenario Planning Based on Business Big Data Analysis , 2015, HCI.

[26]  Roman Garnett,et al.  Differentially Private Bayesian Optimization , 2015, ICML.

[27]  Claudius Steinhardt,et al.  Model-based decision support for optimal brochure pricing: applying advanced analytics in the tour operating industry , 2014, OR Spectr..

[28]  Bernhard Mitschang,et al.  Prescriptive Analytics for Recommendation-Based Business Process Optimization , 2014, BIS.

[29]  Jasper Snoek,et al.  Bayesian Optimization with Unknown Constraints , 2014, UAI.

[30]  Myunggwon Hwang,et al.  Research Advising System Based on Prescriptive Analytics , 2014 .

[31]  Anand D. Sarwate,et al.  Stochastic gradient descent with differentially private updates , 2013, 2013 IEEE Global Conference on Signal and Information Processing.

[32]  Chih-Lin Chi,et al.  Individualized Patient-centered Lifestyle Recommendations: an Expert System for Communicating Patient Specific Cardiovascular Risk Information and Prioritizing Lifestyle Options , 2022 .

[33]  Chen Yang,et al.  10-year CVD risk prediction and minimization via InverseClassification , 2012, IHI '12.

[34]  Ling Huang,et al.  Learning in a Large Function Space: Privacy-Preserving Mechanisms for SVM Learning , 2009, J. Priv. Confidentiality.

[35]  Gaël Varoquaux,et al.  Scikit-learn: Machine Learning in Python , 2011, J. Mach. Learn. Res..

[36]  Anand D. Sarwate,et al.  Differentially Private Empirical Risk Minimization , 2009, J. Mach. Learn. Res..

[37]  Nando de Freitas,et al.  A Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning , 2010, ArXiv.

[38]  Assaf Schuster,et al.  Data mining with differential privacy , 2010, KDD.

[39]  Charu C. Aggarwal,et al.  The Inverse Classification Problem , 2010, Journal of Computer Science and Technology.

[40]  Andreas Krause,et al.  Information-Theoretic Regret Bounds for Gaussian Process Optimization in the Bandit Setting , 2009, IEEE Transactions on Information Theory.

[41]  Ling Liu,et al.  Encyclopedia of Database Systems , 2009, Encyclopedia of Database Systems.

[42]  Aaron Roth,et al.  Differentially Private Approximation Algorithms , 2009, ArXiv.

[43]  Kamalika Chaudhuri,et al.  Privacy-preserving logistic regression , 2008, NIPS.

[44]  Vitaly Shmatikov,et al.  Robust De-anonymization of Large Sparse Datasets , 2008, 2008 IEEE Symposium on Security and Privacy (sp 2008).

[45]  Adam D. Smith,et al.  Composition attacks and auxiliary information in data privacy , 2008, KDD.

[46]  Daniel A. Spielman,et al.  Spectral Graph Theory and its Applications , 2007, 48th Annual IEEE Symposium on Foundations of Computer Science (FOCS'07).

[47]  Kunal Talwar,et al.  Mechanism Design via Differential Privacy , 2007, 48th Annual IEEE Symposium on Foundations of Computer Science (FOCS'07).

[48]  Cynthia Dwork,et al.  Privacy, accuracy, and consistency too: a holistic solution to contingency table release , 2007, PODS.

[49]  Kamalika Chaudhuri,et al.  When Random Sampling Preserves Privacy , 2006, CRYPTO.

[50]  Cynthia Dwork,et al.  Calibrating Noise to Sensitivity in Private Data Analysis , 2006, TCC.

[51]  T. Davenport.  Competing on analytics. , 2006, Harvard business review.

[52]  Cynthia Dwork,et al.  Privacy-Preserving Datamining on Vertically Partitioned Databases , 2004, CRYPTO.

[53]  Irit Dinur,et al.  Revealing information while preserving privacy , 2003, PODS.

[54]  Latanya Sweeney,et al.  k-Anonymity: A Model for Protecting Privacy , 2002, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[55]  Ramakrishnan Srikant,et al.  Privacy-preserving data mining , 2000, SIGMOD '00.

[56]  R. Tibshirani.  Regression Shrinkage and Selection via the Lasso , 1996 .

[57]  Jonas Mockus,et al.  Application of Bayesian approach to numerical methods of global and stochastic optimization , 1994, J. Glob. Optim..

[58]  Henryk Wozniakowski,et al.  The statistical security of a statistical database , 1984, TODS.

[59]  Gultekin Özsoyoglu,et al.  Auditing and Inference Control in Statistical Databases , 1982, IEEE Transactions on Software Engineering.

[60]  Jonas Mockus,et al.  On Bayesian Methods for Seeking the Extremum and their Application , 1977, IFIP Congress.

[61]  Jonas Mockus,et al.  On Bayesian Methods for Seeking the Extremum , 1974, Optimization Techniques.

[62]  W. R. Thompson.  ON THE LIKELIHOOD THAT ONE UNKNOWN PROBABILITY EXCEEDS ANOTHER IN VIEW OF THE EVIDENCE OF TWO SAMPLES , 1933 .