David Wolpert

David H. Wolpert

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53EEDennis Huo, Qiaoyan Yu, David Wolpert, Paul Ampadu: A simulator for ballistic nanostructures in a 2-D electron gas. JETC 5(1): (2009)
52EEDavid Wolpert, Paul Ampadu: A Low-Power Safety Mode for Variation Tolerant Systems-on-Chip. DFT 2008: 33-41
51EEDev G. Rajnarayan, David Wolpert: Bias-Variance Techniques for Monte Carlo Optimization: Cross-validation for the CE Method CoRR abs/0810.0877: (2008)
50EEWilliam G. Macready, David Wolpert: Distributed Constrained Optimization with Semicoordinate Transformations CoRR abs/0811.0823: (2008)
49EEDavid Wolpert, Paul Ampadu: Adaptive Delay Correction for Runtime Variation in Dynamic voltage Scaling Systems. Journal of Circuits, Systems, and Computers 17(6): 1111-1128 (2008)
48EEDavid Wolpert, Paul Ampadu: Temperature-Robust Performance Yield through Supply Voltage Selection. ISCAS 2007: 2279-2282
47EEDavid H. Wolpert, Dev G. Rajnarayan: Parametric Learning and Monte Carlo Optimization CoRR abs/0704.1274: (2007)
46EEDavid H. Wolpert: Physical limits of inference CoRR abs/0708.1362: (2007)
45EEDavid H. Wolpert, William G. Macready: Using self-dissimilarity to quantify complexity. Complexity 12(3): 77-85 (2007)
44EEChien-Feng Huang, Stefan Bieniawski, David H. Wolpert, Charlie E. M. Strauss: A comparative study of probability collectives based multi-agent systems and genetic algorithms. GECCO 2005: 751-752
43EEDavid H. Wolpert: A Predictive Theory of Games CoRR abs/nlin/0512015: (2005)
42EEDavid H. Wolpert, William G. Macready: Coevolutionary free lunches. IEEE Trans. Evolutionary Computation 9(6): 721-735 (2005)
41EEStefan Bieniawski, David Wolpert: Adaptive, Distributed Control of Constrained Multi-Agent Systems. AAMAS 2004: 1230-1231
40EEChiu Fan Lee, David H. Wolpert: Product Distribution Theory for Control of Multi-Agent Systems. AAMAS 2004: 522-529
39EEDavid Wolpert: Information Theory - The Bridge Connecting Bounded Rational Game Theory and Statistical Physics CoRR cond-mat/0402508: (2004)
38EEDavid Wolpert, Stefan Bieniawski: Distributed Control by Lagrangian Steepest Descent CoRR cs.MA/0403012: (2004)
37EEDavid Wolpert: Metrics for more than two points at once CoRR nlin.AO/0404032: (2004)
36EEStéphane Airiau, Sandip Sen, David Wolpert, Kagan Tumer: Providing Effective Access to Shared Resources: A COIN Approach. Engineering Self-Organising Systems 2003: 249-264
35EEKagan Tumer, David Wolpert: Collectives for the Optimal Combination of Imperfect Objects CoRR cond-mat/0301459: (2003)
34EEDavid Wolpert: Product Distribution Field Theory CoRR cond-mat/0307630: (2003)
33EEDavid Wolpert, Kagan Tumer, Esfandiar Bandari: Improving Search Algorithms by Using Intelligent Coordinates CoRR math.OC/0301268: (2003)
32 John W. Lawson, David Wolpert: The Design of Collectives of Agents to Control Non-Markovian Systems. AAAI/IAAI 2002: 332-337
31EEDavid Wolpert, John W. Lawson: Designing agent collectives for systems with Markovian dynamics. AAMAS 2002: 1066-1073
30EEKagan Tumer, Adrian K. Agogino, David Wolpert: Learning sequences of actions in collectives of autonomous agents. AAMAS 2002: 378-385
29EEDavid Wolpert, Kagan Tumer: Collective Intelligence, Data Routing and Braess' Paradox. J. Artif. Intell. Res. (JAIR) 16: 359-387 (2002)
28 David Wolpert, Joseph Sill, Kagan Tumer: Reinforcement Learning in Distributed Domains: Beyond Team Games. IJCAI 2001: 819-824
27 Mario Köppen, David Wolpert, William G. Macready: Remarks on a recent paper on the "no free lunch" theorems. IEEE Trans. Evolutionary Computation 5(3): 295-296 (2001)
26 Kagan Tumer, David Wolpert: Collective Intelligence and Braess' Paradox. AAAI/IAAI 2000: 104-109
25EEDavid Wolpert, Sergey Kirshner, Christopher J. Merz, Kagan Tumer: Adaptivity in agent-based routing for data networks. Agents 2000: 396-403
24EEDavid Wolpert: On the computational capabilities of physical systems part I: the impossibility of infallible computation CoRR physics/0005058: (2000)
23EEDavid Wolpert: On the computational capabilities of physical systems part II: relationship with conventional computer science CoRR physics/0005059: (2000)
22EEDavid Wolpert, Kevin R. Wheeler, Kagan Tumer: General Principles of Learning-Based Multi-Agent Systems. Agents 1999: 77-83
21EEKagan Tumer, David Wolpert: Avoiding Braess' Paradox through Collective Intelligence CoRR cs.DC/9912012: (1999)
20EEDavid Wolpert, Kagan Tumer, Jeremy Frank: Using Collective Intelligence to Route Internet Traffic CoRR cs.LG/9905004: (1999)
19EEDavid Wolpert, Kevin R. Wheeler, Kagan Tumer: Collective Intelligence for Control of Distributed Dynamical Systems CoRR cs.LG/9908013: (1999)
18EEDavid Wolpert, Kagan Tumer: An Introduction to Collective Intelligence CoRR cs.LG/9908014: (1999)
17EEDavid Wolpert, Kevin R. Wheeler, Kagan Tumer: General Principles of Learning-Based Multi-Agent Systems CoRR cs.MA/9905005: (1999)
16EEDavid Wolpert, Sergey Kirshner, Christopher J. Merz, Kagan Tumer: Adaptivity in Agent-Based Routing for Data Networks CoRR cs.MA/9912011: (1999)
15 David Wolpert, William G. Macready: An Efficient Method To Estimate Bagging's Generalization Error. Machine Learning 35(1): 41-55 (1999)
14 Philip K. Chan, Salvatore J. Stolfo, David Wolpert: Guest Editors' Introduction. Machine Learning 36(1-2): 5-7 (1999)
13 Padhraic Smyth, David Wolpert: Linearly Combining Density Estimators via Stacking. Machine Learning 36(1-2): 59-83 (1999)
12EEDavid Wolpert, Kagan Tumer, Jeremy Frank: Using Collective Intelligence to Route Internet Traffic. NIPS 1998: 952-960
11 William G. Macready, David Wolpert: Bandit problems and the exploration/exploitation tradeoff. IEEE Trans. Evolutionary Computation 2(1): 2-22 (1998)
10 Padhraic Smyth, David Wolpert: Anytime Exploratory Data Analysis for Massive Data Sets. KDD 1997: 54-60
9 Padhraic Smyth, David Wolpert: Stacked Density Estimation. NIPS 1997
8 David Wolpert, William G. Macready: No free lunch theorems for optimization. IEEE Trans. Evolutionary Computation 1(1): 67-82 (1997)
7EEDavid Wolpert: On Bias Plus Variance. Neural Computation 9(6): 1211-1243 (1997)
6 Ron Kohavi, David Wolpert: Bias Plus Variance Decomposition for Zero-One Loss Functions. ICML 1996: 275-283
5 David Wolpert: Horizonal Generalization. ICML 1995: 566-574
4EEDavid Wolpert: Bayesian Backpropagation Over I-O Functions Rather Than Weights. NIPS 1993: 200-207
3EEDavid Wolpert: On the Use of Evidence in Neural Networks. NIPS 1992: 539-546
2EEDavid H. Wolpert: Stacked generalization. Neural Networks 5(2): 241-259 (1992)
1EEDavid H. Wolpert: Constructing a generalizer superior to NETtalk via a mathematical theory of generalization. Neural Networks 3(4): 445-452 (1990)

Coauthor Index

1Adrian K. Agogino [30]
2Stéphane Airiau [36]
3Paul Ampadu [48] [49] [52] [53]
4Esfandiar Bandari [33]
5Stefan Bieniawski [38] [41] [44]
6Philip K. Chan [14]
7Jeremy Frank [12] [20]
8Chien-Feng Huang [44]
9Dennis Huo [53]
10Sergey Kirshner [16] [25]
11Ron Kohavi [6]
12Mario Köppen [27]
13John W. Lawson [31] [32]
14Chiu Fan Lee [40]
15William G. Macready [8] [11] [15] [27] [42] [45] [50]
16Christopher J. Merz [16] [25]
17Dev G. Rajnarayan [47] [51]
18Sandip Sen [36]
19Joseph Sill [28]
20Padhraic Smyth [9] [10] [13]
21Salvatore J. Stolfo [14]
22Charlie E. M. Strauss [44]
23Kagan Tumer [12] [16] [17] [18] [19] [20] [21] [22] [25] [26] [28] [29] [30] [33] [35] [36]
24Kevin R. Wheeler [17] [19] [22]
25Qiaoyan Yu [53]

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Copyright © Sun May 17 03:24:02 2009 by Michael Ley (ley@uni-trier.de)