Decision-theoretic Harmony: A First Step
Liangrong Yi and Judy Goldsmith
International Journal of Approximate Reasoning, Special Issue on Bayesian Applications, to appear.
Planning for Welfare to Work
Liangrong Yi, Raphael Finkel and Judy Goldsmith
Proc. Florida AI Research Symposium (FLAIRS ’08), pp. 696–702.
The Conference Paper Assignment Problem
Judy Goldsmith and Robert H. Sloan
Proc. AAAI Workshop on Preference Handling in AI, 2007.
A Benchmark Model for Decision-Theoretic Planning with Constraints
Kendra Renee Gehlbach, Brandon Laracuente, Cynthia Isenhour, Judy Goldsmith, Beth Goldstein and Mirosław Truszczyński
The Fourth Bayesian Modelling Applications Workshop during UAI 2006.
Factored MDP Elicitation and Plan Display
Krol Kevin Mathias, Casey Lengacher, Derek Williams, Austin Cornett, Alex Dekhtyar and Judy Goldsmith
ISDN, AAAI ’06.
When Domains Require Modeling Adaptations
Krol Kevin Mathias, Cynthia Isenhour, Alex Dekhtyar, Judy Goldsmith and Beth Goldstein
The Fourth Bayesian Modelling Applications Workshop during UAI 2006.
Adaptive decision support for planning under hard and soft constraints
Alex Dekhtyar, Raphael Finkel, Judy Goldsmith, Beth Goldstein and Joan Mazur
Proc. AAAI Spring Symposium on Decision Support in a Changing World, AAAI Press, 2005.
Interactive Preferences and Decision-Theoretic Planning
D. Williams, K. Bailey, A. Dekhtyar, R. Finkel, J. Goldsmith, B. Goldstein and J. Mazur
Proc. IJCAI Workshop on Preference Handling, 2005.
The Bayesian advisor project I: modeling academic advising
Alexander Dekhtyar, Judy Goldsmith, Huazhi Li and Brett Young
UK CS Dept. Tech Report 323-01.
Finding the k Best Policies
Peng Dai and Judy Goldsmith
Proc. 1st International Conference on Algorithmic Decision Theory, 2009.
When plans distinguish Bayes nets
Alex Dekhtyar, Jan Pearce and Judy Goldsmith
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems (IJUFKS) Vol 11, Suppl, pp. 1-24, November 2003.
Nonapproximability results for partially observable Markov decision processes
C. Lusena, J. Goldsmith and M. Mundhenk
Journal of AI Research 14: 83–103, 2001.
When plans distinguish Bayes nets
Alex Dekhtyar, Judy Goldsmith and Jan Pearce
KI-2001 workshop ”Uncertainty in Artificial Intelligence”, September, 2001.
The complexity of finite-horizon Markov decision process problems
M. Mundhenk, C. Lusena, J. Goldsmith and E. Allender
Journal of the ACM 47: (4), 681-720, July 2000.
The complexity of model aggregation
J. Goldsmith and R.H. Sloan
Proc. AI, Planning and Scheduling (AIPS '00).
More theory revision with queries
J. Goldsmith, R.H. Sloan, Balázs Szörényi and György Turán
Proc. 2000 ACM Symposium on Theory of Computing, May, 2000.
Complexity issues in Markov decision processes
Judy Goldsmith and Martin Mundhenk
Proc. IEEE Conference on Computational Complexity 1998.
The complexity of plan existence and evaluation in probabilistic domains
M.L. Littman, M. Mundhenk and J. Goldsmith
Journal of AI Research, 1998.
Also appeared in: Proc. Conference on Uncertainty in AI, August 1997.
The Computational Complexity of Probabilistic Planning
M. Littman, J. Goldsmith and M. Mundhenk
The Journal of AI Research, volume 9, pages 1–36, 1998.
The complexity of deterministically observable finite-horizon Markov decision processes
Judy Goldsmith, Christopher Lusena and Martin Mundhenk
UK CS Department Technical Report 268-96.
The complexity of unobservable finite-horizon Markov decision processes (extended abstract)
M. Mundhenk, J. Goldsmith and E. Allender
UK CS Department Technical Report 269-96.
More recent version. A shorter version appeared in the Proc. MFCS '97.
The Complexity of Probabilistic Lobbying
Gabor Erdelyi, Henning Fernau, Judy Goldsmith, Nicholas Mattei, Daniel Raible and Jörg Rothe
Proc. 1st International Conference on Algorithmic Decision Theory, 2009.
Complexity of DNF minimization and isomorphism testing for monotone formulas
Judy Goldsmith, Matthias Hagen and Martin Mundhenk
Information and Computation, Vol 206/6 pp 760-775, June 2008.
Proc. Mathematical Foundations of Computer Science (MFCS ’05), Springer Lecture Notes in Computer Science, Vol. 3618, 2005.
Competition Adds Complexity
Martin Mundhenk and Judy Goldsmith
Proc. Neural Information Processing Systems (NIPS 2007), pp. 561–568.
Preferences and Domination
J. Goldsmith
Dagstuhl Electronic Proceedings, 2005.
Dagstuhl Seminar Proceedings, Seminar 04421, 2004.
Tally NP sets and easy census functions
J. Goldsmith, M. Ogihara and J. Rothe
Information and Computation 158: (1) 29-52 APR 10 2000.
Proc. MFCS ’98, Springer-Verlag Lecture Notes in Computer Science 1450: 483-492, 1998.
An algorithm for the class of pure implicational formulas
J. Franco, J. Goldsmith, J. Schlipf, E. Speckenmeyer and R. Swaminathan
Discrete Applied Mathematics 97: 89-106 OCT 15 1999.
Also appeared in: Siena Workshop on Satisfiability, Università degli Studi di Siena, Siena, Italy, May, 1996.
Downward separation fails catastrophically for limited nondeterminism classes
Richard Beigel and Judy Goldsmith
SIAM J. Comp. 5: 1998.
Also appeared in: Proc. 10th Structure in Complexity Theory Conference (1994).
L-printable sets
L. Fortnow, J. Goldsmith, M. Levy and S. Mahaney
SIAM J. Comp. 28: (1) 137-151 1998.
Also appeared in: Proc. Conference on Computational Complexity (Formerly the Structure in Complexity Theory Conference) (May, 1996).
Sharply bounded alternation and quasilinear time
Stephen Bloch, Jonathan Buss and Judy Goldsmith
Theory of Computing Systems (formerly Mathematical System Theory) 31: (2) 187-214 MAR-APR 1998.
Limited Nondeterminism
Judy Goldsmith, Matthew Levy and Martin Mundhenk
UK CS Department Technical Report 267-96.
Appeared without the appendix in the Complexity Theory Column of SIGACT News, June, 1996.
Scalability and the isomorphism problem
Judy Goldsmith and Steve Homer
Information Processing Letters 57: (3) 137-143 FEB 12 1996.
Sharply bounded alternation with P
S. Bloch, J. Buss and J. Goldsmith
Proc. DMTCS’96, Springer-Verlag Lecture Notes in Computer Science (1996).
How hard are n2-hard problems?
Stephen Bloch, Jonathan Buss and Judy Goldsmith
SIGACT News 91 (1994), 83–85.
A note on bi-immunity and p-closeness of p-cheatable sets in P/poly
J. Goldsmith, D. Joseph and P. Young
Journal of Computer System Science 46: (3) 349-362 JUN 1993.
Nondeterminism within P
J. Buss and J. Goldsmith
SIAM Journal of Computing 22: (3) 560-572 JUN 1993.
Also appeared in: Proceedings Symposium on Theoretical Computer Science, Springer-Verlag Lecture Notes in Computer Science #480 (1991), 348–359.
Relativized isomorphisms of NP-complete sets
J. Goldsmith and D. Joseph
Computational Complexity, 186–205, 1993.
Using self-reducibility to characterize polynomial time
J. Goldsmith, D. Joseph and P. Young
Information and Computation 104: (2) 288-308 JUN 1993.
On the structure and complexity of infinite sets with minimal perfect hash functions
J. Goldsmith, L. Hemachandra and K. Kunen
Computational Complexity 2: 18–39, 1992.
Also appeared in: Proceedings of the 11th Foundations of Software Technology and Theoretical Computer Science Conference, Springer-Verlag Lecture Notes in Computer Science 560: 212-223 1991.
Near-testable sets
J. Goldsmith, L. Hemachandra, D. Joseph and P. Young
SIAM Journal of Computing, 20:3, 1991.
Polynomial Isomorphisms and Near-Testable Sets
J. Goldsmith
PhD. Thesis, University of Wisconsin-Madison (1988). Also available as University of Wisconsin Technical Report # 816 (1989).
Self-reducibility, near-testability, and p-cheatable sets: The effect of internal structure on the complexity of a set
J. Goldsmith, D. Joseph and P. Young
Proceedings of the Second Annual Structure in Complexity Theory Conference, IEEE Computer Society (1987), 50-60.
Three results on the polynomial isomorphisms of sets
J. Goldsmith, D. Joseph
Proc. Twenty-seventh Foundations of Computer Science Conference, IEEE Computer Society (1986), 390-397.
New Horn Revision Algorithms
Judy Goldsmith and Robert H. Sloan
Journal of Machine Learning Research, 6(Dec):1919–1938, 2005.
Revision algorithms using queries: results and problems
J. Goldsmith, R.H. Sloan, Balázs Szörényi and György Turán
Proc. NIPS Foundations of Active Learning workshop, December, 2005.
Theory revision with queries: results and problems
J. Goldsmith, R.H. Sloan, B. Szörényi and G. Turán
Proc. Workshop on Learning with Logics and Logics for Learning, Japan, 2005.
Theory Revision with Queries: Horn, Read-once, and Parity Formulas
J. Goldsmith, R.H. Sloan, Balázs Szörényi and György Turán
Artificial Intelligence Journal 156: (2) 139–176, July 2004.
New Revision Algorithms
J. Goldsmith, R.H. Sloan, Balázs Szörényi and György Turán
Proc. Conference on Algorithmic Learning Theory (ALT ’04), pp. 395 - 409, September, 2004.
Theory Revision with Queries: DNF Formulas
Judy Goldsmith, Robert H. Sloan and György Turán
Machine Learning 47(2-3): 257-295, May/June 2002.
Improved algorithms for theory revision with queries (extended abstract)
J. Goldsmith and R.H. Sloan
Proc. 2000 Conference on Computational Learning Theory, June, 2000.
Editors’ introduction to the special issue on model views in Bayesian applications
Judy Goldsmith and Kathy Laskey
International Journal on Approximate Reasoning, to appear.
Preference Handling for Artificial Intelligence
Judy Goldsmith and Ulrich Junker
AI Magazine, Winter, 2008.
Crisis or opportunity?
Judy Goldsmith
in the Complexity Theory Column of SIGACT News 27, 1996.
Expediting RL by Using Graphical Structures
Peng Dai, Alexander Strehl and Judy Goldsmith
Proc. The 7th Internat’l Conference on Autonomous Agents and Multiagent Systems (AAMAS ’08), pp. 1325-1328.
Multi-threaded BLAO* Algorithm
Peng Dai and Judy Goldsmith
FLAIRS 2007.
Topological Value Iteration Algorithm for Markov Decision Processes
Peng Dai and Judy Goldsmith
Proc. IJCAI 2007.
LAO*, RLAO* or BLAO*
Peng Dai and Judy Goldsmith
Proc. AAAI Workshop on Heuristic Search, Memory Based Heuristics and Their Applications, 2006.
Bidirectional LAO*
Kiran Bhuma and Judy Goldsmith
First Indian International Conference on Artificial Intelligence, pp. 980–992, December, 2003.
Genetic algorithms for approximating solutions to POMDPs
C.Wells, C. Lusena and J. Goldsmith
UK CS Dept Tech Report 290-99.
My brain is full: When more memory helps
C.D. Lusena, T. Li, S. Sittinger, C.A. Wells and Judy Goldsmith
Proc. Uncertainty in AI, July, 1999.
The computational complexity of dominance and consistency in CP-nets
Judy Goldsmith, Jérôme Lang, Mirosław Truszczyński and Nic Wilson
Journal of Artificial Intelligence Research, Volume 33, pages 403–432, 2008.
Proc. 21st International Joint Conference on AI (IJCAI ’05).
Preferences and Domination
J. Goldsmith
Dagstuhl Electronic Proceedings, 2005.
Dagstuhl Seminar Proceedings, Seminar 04421, 2004.
POET, The Online Preference Elicitation Tool
James Royalty, Derek Williams, Robert Holland, Judy Goldsmith and Alex Dekhtyar
Proc. AAAI Workshop on Preferences in AI and CP: A Symbolic Approach, July, 2002.
A Framework for Management of Semistructured Probabilistic Data
Wenzhong Zhao, Alex Dekhtyar and Judy Goldsmith
Journal of Intelligent Information Systems 25:3, 2005.
Building Bayes Nets with Semistructured Probabilistic DBMS
Wenzhong Zhao, Alex Dekhtyar, Judy Goldsmith, Erik Jessup and Jiangyu Li
GI-EMISA Forum (ISBN 1610-3351), 1:29-30, 2004.
Databases for Interval Probabilities
Wenzhong Zhao, Alex Dekhtyar and Judy Goldsmith
International Journal of Intelligent Systems, 19: (9) 789–815, September, 2004.
Can Probabilistic Databases Help Elect Qualified Officials?
Judy Goldsmith, Alex Dekhtyar and Wenzhong Zhao
Proc. Florida AI Research Symposium, May, 2003.
Representing Probabilistic Information in XML
Wenzhong Zhao, Alex Dekhtyar and Judy Goldsmith
University of Kentucky Department of Computer Science Tech. Report 770-03 April, 2003.
Query Algebra Operations for Interval Probabilities
Wenzhong Zhao, Alex Dekhtyar and Judy Goldsmith
Proc. 14th International Conference on Database and Expert Systems Applications, September, 2003. Available in Springer Lecture Notes in Computer Science 2736, pp. 527 - 536.
Conditionalization for Interval Probabilities
Alex Dekhtyar and Judy Goldsmith
Proc. Workshop on Conditionals, Information, and Inference, May, 2002.
Semistructured Probabilistic Databases
A. Dekhtyar, S. Hawkes and J. Goldsmith
Proc. Statistical and Scientific Database Management Systems, June, 2001.
Write it Right
Judy Goldsmith and Robert H. Sloan
IEEE Professional Communication Society Newsletter
Efficiently Eliciting Many Probabilities Online
Jiangyu Li, Alex Dekhtyar and Judy Goldsmith
Tech Report, 2002.
The Bayesian Advisor Project
Alex Dekhtyar and Judy Goldsmith
Tech Report, 2002.
Planning for success: The interdisciplinary approach to building Bayesian models
Alex Dekhtyar, Judy Goldsmith, Beth Goldstein, Krol Kevin Mathias and Cynthia Isenhour
International Journal of Approximate Reasoning, Volume 50, Issue 3, March 2009, Pages 416–428, Special Section on Bayesian Modelling.
Social Construction of Technology in the Welfare to Work Project
Joan Mazur, Beth Goldstein and Judy Goldsmith
UAI Workshop on Bayesian Applications, 2004.
Uncertainty as the Source of Knowledge Transfer Opportunity
Alexander Dekhtyar, Jane Hayes and Judy Goldsmith
Proc. 1st International Workshop on Living with Uncertainties (IWLU01), 2007.
Markov Indecision Processes: A Formal Model of Decision-Making Under Extreme Confusion
Harry Q. Bovik, Judy Q. Goldsmith, Andrew Q. Klapper and Michael Q. Littman
Journal of Machine Learning Gossip, 1(Apr):1-9, 2003.
Public key cryptosystems with partial secrecy
Judy Goldsmith and Andrew Klapper
Tech Report, 1996.
The 1D Illumination Problem: When Crossing Doesn’t Help
Judy Goldsmith, Jacqueline Dodgson and Tracy Kowalski
ACM Student Poster Competion (1994).