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Eric B. Baum
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2020 – today
- 2023
- [j16]Eric B. Baum:
TruthSift: A Platform for Collective Rationality. Neural Comput. 35(3): 536-553 (2023)
2000 – 2009
- 2006
- [c15]Eric B. Baum:
A Working Hypothesis for General Intelligence. AGI 2006: 55-74 - [c14]Stan Franklin, Hugo de Garis, Sam S. Adams, Eric B. Baum, Pei Wang, Steve Grand, Ben Goertzel, Phil Goetz:
Panel Discussion: What are the bottlenecks, and how soon to AGI? AGI 2006: 283-293 - 2004
- [b1]Eric B. Baum:
What is thought? MIT Press 2004, ISBN 978-0-262-02548-5, pp. I-IX, 1-478 - 2002
- [j15]Gary William Flake, Eric B. Baum
:
Rush Hour is PSPACE-complete, or "Why you should generously tip parking lot attendants". Theor. Comput. Sci. 270(1-2): 895-911 (2002) - 2001
- [j14]Eric B. Baum
Where Genetic Algorithms Excel. Evol. Comput. 9(1): 93-124 (2001) - [j13]Eric B. Baum
Evolution of Cooperative Problem Solving in an Artificial Economy. Neural Comput. 12(12): 2743-2775 (2001) - 2000
- [c13]Eric B. Baum
An Artificial Economy of Post Production Systems. IWLCS 2000: 3-20
1990 – 1999
- 1999
- [j12]Eric B. Baum:
Toward a Model of Intelligence as an Economy of Agents. Mach. Learn. 35(2): 155-185 (1999) - [j11]Eric B. Baum
Propagating Distributions Up Directed Acyclic Graphs. Neural Comput. 11(1): 215-227 (1999) - [e2]Laura F. Landweber, Eric B. Baum:
DNA Based Computers, Proceedings of a DIMACS Workshop, Princeton, New Jersey, USA, June 10-12, 1996. DIMACS Series in Discrete Mathematics and Theoretical Computer Science 44, DIMACS/AMS 1999, ISBN 978-0-8218-0756-9 [contents] - 1998
- [j10]Eric B. Baum, Warren D. Smith:
A Bayesian approach to relevance in game playing. J. Int. Comput. Games Assoc. 21(1): 43 (1998) - 1997
- [j9]Eric B. Baum
A Bayesian Approach to Relevance in Game Playing. Artif. Intell. 97(1-2): 195-242 (1997) - 1996
- [c12]Eric B. Baum, Dan Boneh:
Running dynamic programming algorithms on a DNA computer. DNA Based Computers 1996: 77-85 - [c11]Eric B. Baum:
DNA sequences useful for computation. DNA Based Computers 1996: 235-241 - [c10]Eric B. Baum:
Toward a Model of Mind as a Laissez-Faire Economy of Idiots. ICML 1996: 28-36 - 1995
- [c9]Eric B. Baum
On Genetic Algorithms. COLT 1995: 230-239 - [c8]Eric B. Baum:
A DNA associative memory potentially larger than the brain. DNA Based Computers 1995: 23-28 - [e1]Richard J. Lipton, Eric B. Baum:
DNA Based Computers, Proceedings of a DIMACS Workshop, Princeton, New Jersey, USA, April 4, 1995. DIMACS Series in Discrete Mathematics and Theoretical Computer Science 27, DIMACS/AMS 1995, ISBN 978-0-8218-0973-0 [contents] - 1992
- [c7]Eric B. Baum:
On Optimal Game Tree Propagation for Imperfect Players. AAAI 1992: 507-512 - 1991
- [j8]Eric B. Baum
The Transition to Perfect Generalization in Perceptrons. Neural Comput. 3(3): 386-401 (1991) - [j7]Eric B. Baum:
Neural net algorithms that learn in polynomial time from examples and queries. IEEE Trans. Neural Networks 2(1): 5-19 (1991) - 1990
- [j6]Eric B. Baum
On learning a union of half spaces. J. Complex. 6(1): 67-101 (1990) - [j5]Eric B. Baum
The Perceptron Algorithm is Fast for Nonmalicious Distributions. Neural Comput. 2(2): 248-260 (1990) - [j4]Eric B. Baum
A Polynomial Time Algorithm That Learns Two Hidden Unit Nets. Neural Comput. 2(4): 510-522 (1990) - [c6]Eric B. Baum:
Polynomial Time Algorithms for Learning Neural Nets. COLT 1990: 258-272 - [c5]Eric B. Baum
When Are k-Nearest Neighbor and Back Propagation Accurate for Feasible Sized Sets of Examples? EURASIP Workshop 1990: 2-25 - [c4]Eric B. Baum, Kevin J. Lang:
Constructing Hidden Units Using Examples and Queries. NIPS 1990: 904-910
1980 – 1989
- 1989
- [j3]Eric B. Baum
What Size Net Gives Valid Generalization? Neural Comput. 1(1): 151-160 (1989) - [j2]Eric B. Baum
A Proposal for More Powerful Learning Algorithms. Neural Comput. 1(2): 201-207 (1989) - [c3]Eric B. Baum:
The Perceptron Algorithm Is Fast for Non-Malicious Distributions. NIPS 1989: 676-685 - 1988
- [j1]Eric B. Baum
On the capabilities of multilayer perceptrons. J. Complex. 4(3): 193-215 (1988) - [c2]Eric B. Baum, David Haussler:
What Size Net Gives Valid Generalization? NIPS 1988: 81-90 - 1987
- [c1]Eric B. Baum, Frank Wilczek:
Supervised Learning of Probability Distributions by Neural Networks. NIPS 1987: 52-61
Coauthor Index
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