Publications

Robert H. Sloan and Richard Warner. “Algorithms and Human Freedom”. Santa Clara High Tech. L.J. 35.2 (2019). 34 pages. Available at: https://digitalcommons.law.scu.edu/chtlj/vol35/iss4/2/.

Robert H. Sloan and Richard Warner. “How Much Should We Spend to Protect Privacy?: Data Breaches and the Need for Information We Do Not Have”. Journal of Law, Economics, & Policy 15.1 (2019), pp. 119–140. Available at: http://jlep.net/home/issues/

Robert H. Sloan and Richard Warner. “When Is an Algorithm Transparent?: Predictive Analytics, Privacy, and Public Policy”. IEEE Security & Privacy 16.3 (2018), pp. 18–25.

Richard Warner and Robert H. Sloan. “The Ethics of the Algorithm: Autonomous Systems and the Wrapper of Human Control”. Cumberland Law Review 48.1 (2018), pp. 101–131.

Tanya Berger-Wolf et al. “A Biology-themed Introductory CS Course at a Large, Diverse Public University”. In: Proc. 49th ACM SIGCSE Technical Symposium on Computer Science Education. 2018, pp. 233–238.

Richard Warner and Robert H. Sloan. “Defending Our Data: The Need for Information We Do Not Have”. In: Value of Information: Intellectual Property, Privacy, and Big Data. Peter Luck Publish- ing, 2018, pp. 149–165.

Stellan Ohlsson et al. “Measuring an artificial intelligence system’s performance on a Verbal IQ test for young children”. Journal of Experimental & Theoretical Artificial Intelligence 29.4 (2017), pp. 679–693. DOI: https://doi.org/10.1080/0952813X.2016.1213060.

Robert H Sloan, Despina Stasi, and György Turán. “Hydras: Directed hypergraphs and Horn formulas”. Theoretical Computer Science 658 (2017), pp. 417–428. DOI: https://doi.org/10.1016/j.tcs.2016.05.036.

Robert H Sloan and Richard Warner. “Relational Privacy: Surveillance, Common Knowledge, and Coordination”. U. St. Thomas JL & Pub. Pol’y 11 (2017), pp. 1–24. Available at: https://ir.stthomas.edu/cgi/viewcontent.cgi?article=1115&context=ustjlpp.

Robert H. Sloan, Cynthia Taylor, and Richard Warner. “Initial Experiences with a CS + Law Introduction to Computer Science (CS 1)”. In: Proceedings of the 2017 ACM Conference on Innovation and Technology in Computer Science Education. ITiCSE ’17. 2017, pp. 40–45. DOI: 10.1145/ 3059009.3059029. Available at: http://doi.acm.org/10.1145/3059009.3059029.

Robert H Sloan and Richard Warner. ““I’ll See”: How Surveillance Undermines Privacy by Eroding Trust”. Santa Clara High Tech. L.J. 32 (2016), pp. 221–267. Available at: http://digitalcommons.law.scu.edu/cgi/viewcontent.cgi?article=1614&context=chtlj.

Robert H Sloan and Richard Warner. “The Self, the Stasi, the NSA: Privacy, Knowledge, and Complicity in the Surveillance State”. Minnesota Journal of Law, Science and Technology 17 (2016). Also on SSRN., pp. 347–408. Available at: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2577308.

Robert H. Sloan. “Why Computer Science?” In: Computer Science for the Curious: Why Study Computer Science? Ed. by Kishor Vaidya. 2016.

Judy Goldsmith, Nicholas Mattei, and Robert H. Sloan. “Who is Watching You Eat?” AI Matters 1 (2015). Preliminary version appeared in 8th Multidisciplinary Workshop on Advances in Preference Handling (MPREF), 2014., pp. 13–22. Available at: http://dl.acm.org/citation.cfm?doid=2757001.2757004.

Robert H. Sloan and Richard Warner. “The Harm in Merely Knowing: Privacy, Surveillance, and the Self”. Journal of Internet Law 19 (2015).

Robert H. Sloan and Richard Warner. “Beyond notice and Choice: Privacy, Norms, and Consent”. Journal of High Technology Law 14.2 (2014), pp. 370–412.

Richard Warner and Robert H Sloan. “Self, Privacy, and Power: Is It All Over?” Tulane Journal of Technology & Intellectual Property 17 (2014), pp. 61–108.

Tanya Berger-Wolf et al. “Commonsense knowledge bases and network analysis”. In: Proc. 11th Int. Symp. On Logical Formalizations of Commonsense Reasoning, 2013. Available at: http://www.commonsense2013.cs.ucy.ac.cy/program.html.

S. Ohlsson et al. “Verbal IQ of a Four-Year Old Achieved by an AI System”. In: Proc. Annu. Conf. Assoc. Advancement Artificial Intelligence (AAAI). 2013.

Robert H Sloan and Richard Warner. “Big Data and the “New” Privacy Tradeoff”. In: Big Data & Privacy: Workshop Paper Collection. Future of Privacy Forum. 2013. Available at: http://www.futureofprivacy.org/big-data-privacy-workshop-paper-collection.

D. Diochnos, R. H. Sloan, and György Turán. “On multiple-instance learning of halfspaces”. Information Processing Letters 112.23 (2012), pp. 933–936.

Robert H. Sloan, Despina Stasi, and György Turán. “Random Horn Formulas and Propagation Connectivity for Directed Hypergraphs”. Discrete Mathematics and Theoretical Computer Science 14 (2012), pp. 29–36.

R. Warner and R. Sloan. “Vulnerable Software: Product-Risk Norms and the Problem of Unauthorized Access”. University of Illinois Journal of Technology, Law & Policy 2012.1 (2012), pp. 101– 150.

Richard Warner and Robert H Sloan. “Behavioral Advertising: From One-Sided Chicken to Informational Norms”. Vanderbilt Journal of Entertainment & Technology Law 15 (2012), pp. 49–83.

Kira Adaricheva et al. “Horn Belief Contraction: Remainders, Envelopes and Complexity”. In: Proc. 13th Int. Conf. Principles of Knowledge Representation and Reasoning (KR). Preliminary version appeared in Commonsense Workshop in 2011. May 2012. Available at: https://www.aaai.org/ocs/index.php/KR/KR12/paper/view/4497

Stellan Ohlsson et al. “An Approach to Evaluate AI Commonsense Reasoning Systems”. In: Proc. 25th Int. Florida Artificial Intelligence Research Society Conference. 2012, pp. 371–374.

Robert H. Sloan, Despina Stasi, and György Turán. “Hydra formulas and related problems for Horn minimization”. In: Graph-Theoretic Concepts in Computer Science (WG). LNCS. Springer, 2012, pp. 237–248.

Richard Warner and Robert H. Sloan. “The Undermining Impact of Information Processing on In- formational Privacy”. In: Rights of Personality in The XXI Century. Ed. by Justyna Balcarczyk. Wolters-Kluwer, 2012, pp. 384–402.

M.B. Russom, Richard Warner, and Robert H. Sloan. “Legal concepts meet technology: a 50- state survey of privacy laws”. In: Proc. 2011 Workshop on Governance of Technology, Information, and Policies (GTIP). 2011, pp. 29–37. Available at: http://www.cs.uic.edu/∼sloan/papers/RussomEtAl50StateSurvey.pdf.

Marina Langlois and Robert H. Sloan. “Reinforcement learning via approximation of the Q-function”. Journal of Experimental & Theoretical Artificial Intelligence 22.3 (2010), pp. 219–235. ISSN: 0952-813X.

Robert H Sloan and Richard Warner. “Developing foundations for accountability systems: informational norms and context-sensitive judgments”. In: Proc. 2010 Workshop on Governance of Technology, Information and Policies (GTIP). GTIP ’10. New York, NY, USA, 2010, pp. 21–26. ISBN: 978-1-4503-0446-7. DOI: 10.1145/1920320.1920324. Available at: http://www.acsac.org/2010/workshop/p21-sloan.pdf.

R. H. Sloan, B. Szörényi, and G. Turán. “Learning Boolean functions with queries”. In: Boolean Models and Methods in Mathematics, Computer Science, and Engineering. Vol. 134. Encyclopedia of Mathematics and its Applications. Cambridge University Press, 2010, pp. 221–256.

Marina Langlois, Robert H. Sloan, and György Turán. “Horn Upper Bounds and Renaming”. JSAT: Journal on Satisfiability, Boolean Modeling and Computation 7 (2009), pp. 1–15.

Marina Langlois et al. “Combinatorial problems for Horn clauses”. In: Graph Theory, Computational Intelligence and Thought. Springer, 2009, pp. 54–65.

Robert H. Sloan, Balázs Szörényi, and György Turán. “On k-term DNF with the maximal number of prime implicants”. SIAM J. Discret. Math. 21.4 (2008), pp. 987–998. ISSN: 0895-4801. DOI: http://dx.doi.org/10.1137/050632026.

Robert H. Sloan, Balázs Szörényi, and György Turán, “Projective DNF formulae and their revision”. Discrete Appl. Math. 156.4 (2008), pp. 530–544. ISSN: 0166-218X. DOI: http://dx.doi.org/10.1016/j.dam.2006.06.021.

Lillian N Cassel et al. “Curriculum update from the ACM education board: CS2008 and a report on masters degrees”. In: ACM SIGCSE Bulletin. Vol. 40. 1. ACM. 2008, pp. 530–531.

Marina Langlois et al. “Combinatorial problems for Horn clauses”. In: Tenth Int. Symp. Artificial Intelligence and Mathematics (ISAIM). 2008. Available at: http://isaim2008.unl.edu/index.php?page=proceedings.

Marina Langlois et al. “Horn Complements: Towards Horn-to-Horn Belief Revision”. In: Proc. AAAI 2008. 2008, pp. 466–471.

R. H. Sloan and P. Troy. “CS 0.5: a better approach to introductory computer science for majors”. In: Proc. 39th ACM SIGCSE technical symposium on Computer Science Education. 2008, pp. 271–275.

Piotr Berman et al. “The inverse protein folding problem on 2D and 3D lattices”. Discrete Appl. Math. 155 (2007), pp. 719–732.

Robert H. Sloan, Balázs Szörényi, and György Turán. “Revising threshold functions”. Theor. Comput. Sci. 382.3 (2007), pp. 198–208. ISSN: 0304-3975. DOI: http://dx.doi.org/10.1016/j.tcs.2007.03.034.

Lillian N Cassel et al. “An Initiative to Attract Students to Computing”. In: Proc. 38th SIGCSE Technical Symposium on Computer Science Education. 2007, pp. 133–134.

Lillian N. Cassel et al. “The Computing Ontology Project—The Computing Education Application”. In: Proc. 38th ACM SIGCSE Technical Symposium on Computer Science Education. 2007, pp. 519– 520.

Judy Goldsmith and Robert H. Sloan. “The Conference Paper Assignment Problem”. In: Proc. AAAI Workshop on Preference Handling for Artificial Intelligence. 2007.

Marina Langlois, Robert H. Sloan, and György Turán. “Horn Upper Bounds and Renaming”. In: Proc. SAT 2007: Tenth Int. Conf. Theory and Applications of Satisfiability Testing. Vol. 4501. Lecture Notes in Computer Science. 2007, pp. 80–93.

Z. Füredi et al. “On set systems with a threshold property”. Discrete Appl. Math. 306 (2006), pp. 3096–3111.

Lillian Boots Cassel, Andrew McGettrick, and Robert H. Sloan. “A Comprehensive Representation of the Computing and Information Disciplines”. In: Proc. 37th ACM SIGCSE Technical Symposium on Computer Science Education. 2006, pp. 199–200.

Stephen Dranger, Robert H. Sloan, and Jon A. Solworth. “The Complexity of Discretionary Access Control”. In: Proc. Advances in Information and Computer Security, First Intl. Workshop on Security (IWSEC 06). Lecture Notes in Computer Science. Springer, 2006, pp. 405–420.

Marina Langlois, Robert H. Sloan, and György Turán. “Horn Upper Bounds of Random 3-CNF: A Computational Study”. In: Ninth Int. Symp. Artificial Intelligence and Mathematics (ISAIM). 2006. Available at: http://anytime.cs.umass.edu/aimath06.

Russell Shackelford et al. “Computing Curricula 2005: The Overview Report”. In: Proc. 37th ACM SIGCSE Technical Symposium on Computer Science Education. 2006, pp. 456–457.

Judy Goldsmith and Robert H. Sloan. “New Horn Revision Algorithms”. J. Machine Learning Research 6 (2005), pp. 1919–1938.

Lillian Boots Cassel, Russell Shackelford, and Robert H. Sloan. “A Synthesis and Ontology of All of Computing”. In: Proc. 36th ACM SIGCSE Technical Symposium on Computer Science Education. 2005, pp. 65–66.

Judy Goldsmith et al. “Theory Revision with Queries: Results and Problems”. In: Proceedings of the Workshop on Learning with Logics and Logics for Learning (LLLL). 2005, pp. 39–44.

Marina Irodova and Robert H. Sloan. “Reinforcement Learning and Function Approximation”. In: Proc. 18th International Florida Artificial Intelligence Research Symposium Conference—FLAIRS 2005. 2005, pp. 455–460.

J. Goldsmith et al. “Theory revision with queries: Horn, read-once, and parity formulas”. Artificial Intelligence 156.2 (2004), pp. 139–176.

Piotr Berman et al. “The Protein Sequence Design Problem in Canonical Model on 2D and 3D Lattices”. In: Proc. 15th Annual Symp. Combinatorial Pattern Matching (CPM). Vol. 3109. Lecture Notes in Computer Science. Springer, 2004, pp. 244–253.

Judy Goldsmith et al. “New Revision Algorithms”. In: Proc. Algorithmic Learning Theory (ALT). Vol. 3244. Lecture Notes in Artificial Intelligence. Springer, 2004, pp. 395–409.

Russell Shackelford et al. “Computing Curricula 2004: The Overview Project”. In: Proc. 35th ACM SIGCSE Technical Symposium on Computer Science Education. 2004, p. 501.

Jon A Solworth and Robert H Sloan. “Security Property Based Administrative Controls”. In: Proc. 9th European Symposium on Research in Computer Security (ESORICS). Vol. 3139. Lecture Notes in Computer Science. Springer, 2004, pp. 244–259.

Jon A. Solworth and Robert H. Sloan. “A Layered Design of Discretionary Access Controls with Decidable Safety Properties”. In: Proc. 2004 IEEE Symposium on Security and Privacy. 2004.

Judy Goldsmith, Robert H Sloan, and György Turán. “Theory revision with queries: DNF formulas”. Machine Learning 47.2-3 (2002), pp. 257–295.

Tamás Horváth, Robert H. Sloan, and György Turán. “Learning Logic Programs with Unary Partial Function Graph Background Knowledge”. In: First International Workshop on Mining Graphs, Trees and Sequences (MGTS-2003). 2003. Available at: http://www.ar.sanken.osaka-u.ac.jp/MGTS-2003CFP.html.

John Impagliazzo et al. “Computer Engineering Computing Curricula”. In: Proc. 34th ACM SIGCSE Technical Symposium on Computer Science Education. 2003, pp. 355–356. ISBN: 1-58113-648-X. DOI: 10.1145/611892.611915.

Robert H. Sloan, B. Szörényi, and Gyögy Turán. “Projective DNF Formulae and Their Revision”. In: Proc. COLT 2003: 16th Annual Conf. on Learning Theory. Vol. 2777. Lecture Notes in Artificial Intelligence. Springer, 2003, pp. 625–639.

Robert H. Sloan and Balázs Szörényi. “Revising projective DNF in the presence of noise”. In: Proc. Kalmár Workshop on Logic and Computer Science. Szeged, Hungary: Dept. of Informatics, University of Szeged, 2003, pp. 143–152.

Thomas S. Messerges, Ezzat A Dabbish, and Robert H Sloan. “Examining smart-card security under the threat of power analysis attacks”. IEEE Transactions on Computers 51.5 (2002), pp. 541–552.

Eric Roberts et al. “Computing Curricula 2001 implementing the recommendations”. In: Proc. 33rd ACM SIGCSE Technical Symposium on Computer Science Education. 2002, pp. 167–168.

U Buy and Robert H. Sloan. “Automatic real-time analysis of reactive systems with the PARTS toolset”. Automated Software Engineering 8.3-4 (2001), pp. 227–273.

Judy Goldsmith and Robert H. Sloan. “More Theory Revision with Queries”. In: Proc. 32nd Annu. ACM Sympos. Theory Comput. 2000, pp. 441–448.

Judy Goldsmith and Robert H. Sloan. “The Complexity of Model Aggregation”. In: Proc. 5th Int. Conf. Artificial Intelligence Planning & Scheduling (AIPS). 2000, pp. 122–129.

Judy Goldsmith et al. “Improved Algorithms for Theory Revision with Queries”. In: Proc. 13th Annu. Conf. on Comput. Learning Theory. 2000, pp. 236–247.

C. K. Chang et al. “Curricula 2001: Bringing the Future to the Classroom”. IEEE Computer (1999).

T. S. Messerges, E. A. Dabbish, and R. H. Sloan. “Investigations of Power Analysis Attacks on Smartcards”. In: Proceedings of the USENIX Workshop on Smartcard Technology. 1999, pp. 151– 161.

T. S. Messerges, E. A. Dabbish, and R. H. Sloan. “Power Analysis Attacks of Modular Exponentiation in Smartcards”. In: Workshop on Cryptographic Hardware and Embedded Systems. Springer-Verlag, 1999, pp. 144–157.

Robert H. Sloan and György Turán. “On Theory Revision with Queries”. In: Proc. 12th Annu. Conf. on Comput. Learning Theory. 1999, pp. 41–52.

A. Prasad Sistla et al. “Towards a theory of cost management for digital libraries and electronic commerce”. ACM Transactions on Database Systems (TODS) 23.4 (1998), pp. 411–452.

R. H. Sloan, K. Takata, and G. Turán. “On Frequent Sets of Boolean Matrices”. Annals of Mathematics and Artificial Intelligence 24 (1998), pp. 193–209.

Dana Angluin et al. “Malicious Omissions and Errors in Answers to Membership Queries”. Machine Learning 28 (1997), pp. 211–255.

Tamás Horváth, Robert H. Sloan, and György Turán. “Learning Logic Programs by using the Product Homomorphism Method”. In: Proc. 10th Annual Conf. Computational Learning Theory. ACM Press, 1997, pp. 10–20.

Robert H. Sloan and Ugo Buy. “Reduction rules for time Petri nets”. Acta Informatica 33 (1996), pp. 687–706.

T. Horváth, R. H. Sloan, and G. Turán. “Learning Logic Programs with Random Classification Noise”. In: Proc. 6th Int. Workshop on Inductive Logic Programming (ILP-96). Vol. 1314. Lecture Notes in Artificial Intelligence. Springer, 1996, pp. 97–118.

Robert H. Sloan. “Pac Learning, Noise, and Geometry”. In: Learning and Geometry: Computational Approaches. Birkhäuser, 1996, pp. 21–41.

Sally A. Goldman and Robert H. Sloan. “Can PAC Learning Algorithms Tolerate Random Attribute Noise?” Algorithmica 14 (1995), pp. 70–84.

Robert H. Sloan. “Four types of noise in data for PAC learning”. Information Processing Letters 54 (1995), pp. 157–162.

Sally A Goldman and Robert H Sloan. “The power of self-directed learning”. Machine Learning 14.3 (1994), pp. 271–294.

Ronald L. Rivest and Robert Sloan. “A Formal Model of Hierarchical Concept-Learning”. Inform. Comput. 114 (1994), pp. 88–114.

Ugo Buy and Robert H. Sloan. “Analysis of Real-Time Programs with Simple Time Petri Nets”. In: Proc. 1994 Int. Symp. Software Testing and Analysis. 1994, pp. 228–239.

Ronald L. Rivest and Robert H. Sloan. “On Choosing between Experimenting and Thinking when Learning”. Inform. Comput. 106 (1993), pp. 1–25.

Ugo Buy and Robert Sloan. “A Petri-Net-Based Approach to Real-Time Program Analysis”. In: Proc. Seventh Int. Workshop Software Specification and Design. 1993, pp. 56–60.

David Helmbold, Robert Sloan, and Manfred K. Warmuth. “Learning Integer Lattices”. SIAM Journal on Computing 21.2 (1992), pp. 240–266.

David Helmbold, Robert Sloan, and Manfred K. Warmuth. “Learning Nested Differences of Intersection-Closed Concept Classes”. Machine Learning 5.2 (1990), pp. 165–196.

David Helmbold, Robert Sloan, and Manfred K. Warmuth. “Learning Integer Lattices”. In: Proc. 3rd Annu. Workshop on Comput. Learning Theory. Morgan Kaufmann. 1990, p. 288.

D. Helmbold, R. Sloan, and M. K. Warmuth. “Learning nested differences of intersection-closed concept classes”. In: Proceedings of the Second Annual Workshop on Computational Learning Theory. San Mateo, CA: Morgan Kaufmann, 1989, pp. 41–56.

R. L. Rivest and R. Sloan. “A New Model for Inductive Inference”. In: Proc. of the Second Conference on Theoretical Aspects of Reasoning about Knowledge. Morgan Kaufmann, Mar. 1988, pp. 13– 27.

Ronald L Rivest and Robert H Sloan. “Learning Complicated Concepts Reliably and Usefully.” In: AAAI. 1988, pp. 635–640.

Robert Sloan. “Types of noise in data for concept learning”. In: Proc. 1st Annu. Workshop on Comput. Learning Theory. Morgan Kaufmann, 1988, pp. 91–96.

Silvio Micali, Charles Rackoff, and Bob Sloan. “The notion of security for probabilistic cryptosys- tems”. In: Proceedings on Advances in cryptology—CRYPTO’86. Springer-Verlag. 1987, pp. 381– 392.