A Mathematical Theory of Generalization: Part I. - David H. Wolpert (Complex Syst., 1990)

A Mathematical Theory of Generalization: Part II. - David H. Wolpert (Complex Syst., 1990)

The Relationship Between Occam's Razor and Convergent Guessing. - David H. Wolpert (Complex Syst., 1990)

Constructing a generalizer superior to NETtalk via a mathematical theory of generalization. - David H. Wolpert (Neural Networks, 1990)

On the Use of Evidence in Neural Networks. - David H. Wolpert (NIPS, 1992)

On the Connection between In-sample Testing and Generalization Error. - David H. Wolpert (Complex Syst., 1992)

Stacked generalization. - David H. Wolpert (Neural Networks, 1992)

Bayesian Backpropagation Over I-O Functions Rather Than Weights. - David H. Wolpert (NIPS, 1993)

Horizonal Generalization. - David H. Wolpert (ICML, 1995)

Bias Plus Variance Decomposition for Zero-One Loss Functions. - Ron Kohavi; David H. Wolpert (ICML, 1996)

What makes an optimization problem hard? - William G. Macready; David H. Wolpert (Complex., 1996)

The Lack of A Priori Distinctions Between Learning Algorithms. - David H. Wolpert (Neural Comput., 1996)

The Existence of A Priori Distinctions Between Learning Algorithms. - David H. Wolpert (Neural Comput., 1996)

Anytime Exploratory Data Analysis for Massive Data Sets. - Padhraic Smyth; David H. Wolpert (KDD, 1997)

Stacked Density Estimation. - Padhraic Smyth; David H. Wolpert (NIPS, 1997)

On Bias Plus Variance. - David H. Wolpert (Neural Comput., 1997)

No free lunch theorems for optimization. - David H. Wolpert; William G. Macready (IEEE Trans. Evol. Comput., 1997)

Using Collective Intelligence to Route Internet Traffic. - David H. Wolpert; Kagan Tumer; Jeremy Frank (NIPS, 1998)

Some results concerning off-training-set and IID error for the Gibbs and the Bayes optimal generalizers. - David H. Wolpert; Emanuel Knill; Tal Grossman (Stat. Comput., 1998)

Bandit problems and the exploration/exploitation tradeoff. - William G. Macready; David H. Wolpert (IEEE Trans. Evol. Comput., 1998)

General Principles of Learning-Based Multi-Agent Systems. - David H. Wolpert; Kevin R. Wheeler; Kagan Tumer (Agents, 1999)

Avoiding Braess' Paradox through Collective Intelligence - Kagan Tumer; David H. Wolpert (CoRR, 1999)

Collective Intelligence for Control of Distributed Dynamical Systems - David H. Wolpert; Kevin R. Wheeler; Kagan Tumer (CoRR, 1999)

An Introduction to Collective Intelligence - David H. Wolpert; Kagan Tumer (CoRR, 1999)

Guest Editors' Introduction. - Philip K. Chan; Salvatore J. Stolfo; David H. Wolpert (Mach. Learn., 1999)

Linearly Combining Density Estimators via Stacking. - Padhraic Smyth; David H. Wolpert (Mach. Learn., 1999)

An Efficient Method To Estimate Bagging's Generalization Error. - David H. Wolpert; William G. Macready (Mach. Learn., 1999)

Collective Intelligence and Braess' Paradox. - Kagan Tumer; David H. Wolpert (AAAI/IAAI, 2000)

Adaptivity in agent-based routing for data networks. - David H. Wolpert; Sergey Kirshner; Christopher J. Merz; Kagan Tumer (Agents, 2000)

On the computational capabilities of physical systems part I: the impossibility of infallible computation - David H. Wolpert (CoRR, 2000)

On the computational capabilities of physical systems part II: relationship with conventional computer science - David H. Wolpert (CoRR, 2000)

Reinforcement Learning in Distributed Domains: Beyond Team Games. - David H. Wolpert; Joseph Sill; Kagan Tumer (IJCAI, 2001)

Optimal Payoff Functions for Members of Collectives. - David H. Wolpert; Kagan Tumer (Adv. Complex Syst., 2001)

Remarks on a recent paper on the "no free lunch" theorems. - Mario Köppen; David H. Wolpert; William G. Macready (IEEE Trans. Evol. Comput., 2001)

The Design of Collectives of Agents to Control Non-Markovian Systems. - John W. Lawson; David H. Wolpert (AAAI/IAAI, 2002)

Learning sequences of actions in collectives of autonomous agents. - Kagan Tumer; Adrian K. Agogino; David H. Wolpert (AAMAS, 2002)

Designing agent collectives for systems with Markovian dynamics. - David H. Wolpert; John W. Lawson (AAMAS, 2002)

Collective Intelligence, Data Routing and Braess' Paradox. - David H. Wolpert; Kagan Tumer (J. Artif. Intell. Res., 2002)

Providing Effective Access to Shared Resources: A COIN Approach. - Stéphane Airiau; Sandip Sen; David H. Wolpert; Kagan Tumer (Engineering Self-Organising Systems, 2003)

Collectives for the Optimal Combination of Imperfect Objects - Kagan Tumer; David H. Wolpert (CoRR, 2003)

Product Distribution Field Theory - David H. Wolpert (CoRR, 2003)

Improving Search Algorithms by Using Intelligent Coordinates - David H. Wolpert; Kagan Tumer; Esfandiar Bandari (CoRR, 2003)

Adaptive, Distributed Control of Constrained Multi-Agent Systems. - Stefan Bieniawski; David H. Wolpert (AAMAS, 2004)

Product Distribution Theory for Control of Multi-Agent Systems. - Chiu Fan Lee; David H. Wolpert (AAMAS, 2004)

Distributed control by Lagrangian steepest descent. - David H. Wolpert; Stefan Bieniawski (CDC, 2004)

Distributed Adaptive Control: Beyond Single-Instant, Discrete Control Variables. - David H. Wolpert; Stefan Bieniawski (MSRAS, 2004)

Information Theory - The Bridge Connecting Bounded Rational Game Theory and Statistical Physics - David H. Wolpert (CoRR, 2004)

Metrics for more than two points at once - David H. Wolpert (CoRR, 2004)

A comparative study of probability collectives based multi-agent systems and genetic algorithms. - Chien-Feng Huang; Stefan Bieniawski; David H. Wolpert; Charlie E. M. Strauss (GECCO, 2005)

A Predictive Theory of Games - David H. Wolpert (CoRR, 2005)

Coevolutionary free lunches. - David H. Wolpert; William G. Macready (IEEE Trans. Evol. Comput., 2005)

Advances in Distributed Optimization Using Probability Collectives. - David H. Wolpert; Charlie E. M. Strauss; Dev G. Rajnarayan (Adv. Complex Syst., 2006)

Using self-dissimilarity to quantify complexity. - David H. Wolpert; William G. Macready (Complex., 2007)

Parametric Learning and Monte Carlo Optimization - David H. Wolpert; Dev G. Rajnarayan (CoRR, 2007)

Physical limits of inference - David H. Wolpert (CoRR, 2007)

Managing Multiple Interacting Adaptive Systems Via Game Theory. - David H. Wolpert; Nilesh V. Kulkarni (AHS, 2008)

Bias-Variance Techniques for Monte Carlo Optimization: Cross-validation for the CE Method - Dev G. Rajnarayan; David H. Wolpert (CoRR, 2008)

Distributed Constrained Optimization with Semicoordinate Transformations - William G. Macready; David H. Wolpert (CoRR, 2008)

What does Newcomb's paradox teach us? - David H. Wolpert; Gregory Benford (CoRR, 2009)

Trembling hand perfection for mixed quantal/best response equilibria. - David H. Wolpert (Int. J. Game Theory, 2009)

Inference Concerning Physical Systems. - David H. Wolpert (CiE, 2010)

PGT: A Statistical Approach to Prediction and Mechanism Design. - David H. Wolpert; James W. Bono (SBP, 2010)

Hysteresis effects of changing parameters of noncooperative games - David H. Wolpert; Michael Harré; Eckehard Olbrich; Nils Bertschinger; Jürgen Jost (CoRR, 2010)

Why income comparison is rational. - David H. Wolpert (Games Econ. Behav., 2010)

Bias-Variance Trade-offs: Novel Applications. - Dev G. Rajnarayan; David H. Wolpert (Encyclopedia of Machine Learning, 2010)

Game theoretic modeling of pilot behavior during mid-air encounters - Ritchie Lee; David H. Wolpert (CoRR, 2011)

Using Supervised Learning to Improve Monte Carlo Integral Estimation - Brendan D. Tracey; David H. Wolpert; Juan J. Alonso (CoRR, 2011)

Towards a bayesian network game framework for evaluating DDoS attacks and defense. - Guanhua Yan; Ritchie Lee; Alex Kent; David H. Wolpert (CCS, 2012)

Predicting the behavior of interacting humans by fusing data from multiple sources. - Erik J. Schlicht; Ritchie Lee; David H. Wolpert; Mykel J. Kochenderfer; Brendan D. Tracey (UAI, 2012)

Counter-Factual Reinforcement Learning: How to Model Decision-Makers That Anticipate The Future - Ritchie Lee; David H. Wolpert; James W. Bono; Scott Backhaus; Russell Bent; Brendan D. Tracey (CoRR, 2012)

Using Machine Learning to Improve Stochastic Optimization. - David H. Wolpert; Dev G. Rajnarayan (AAAI (Late-Breaking Developments), 2013)

Estimating Functions of Distributions Defined over Spaces of Unknown Size. - David H. Wolpert; Simon DeDeo (Entropy, 2013)

Predicting Behavior in Unstructured Bargaining with a Probability Distribution. - David H. Wolpert; James W. Bono (J. Artif. Intell. Res., 2013)

The lesson of Newcomb's paradox. - David H. Wolpert; Gregory Benford (Synth., 2013)

Cyber-Physical Security: A Game Theory Model of Humans Interacting Over Control Systems. - Scott Backhaus; Russell Bent; James W. Bono; Ritchie Lee; Brendan D. Tracey; David H. Wolpert; Dongping Xie; Yildiray Yildiz (IEEE Trans. Smart Grid, 2013)

Ubiquity symposium: Evolutionary computation and the processes of life: what the no free lunch theorems really mean: how to improve search algorithms. - David H. Wolpert (Ubiquity, 2013)

Counter-Factual Reinforcement Learning: How to Model Decision-Makers That Anticipate the Future. - Ritchie Lee; David H. Wolpert; James W. Bono; Scott Backhaus; Russell Bent; Brendan D. Tracey (Decision Making and Imperfection, 2013)

Information geometry of influence diagrams and noncooperative games. - Nils Bertschinger; David H. Wolpert; Eckehard Olbrich; Jürgen Jost (CoRR, 2014)

A framework for optimal high-level descriptions in science and engineering - preliminary report. - David H. Wolpert; Joshua A. Grochow; Eric Libby; Simon DeDeo (CoRR, 2014)

Bayesian Optimization with a Finite Budget: An Approximate Dynamic Programming Approach. - Rémi Lam; Karen Willcox; David H. Wolpert (NIPS, 2016)

A Likelihood Ratio Detector for Identifying Within-Perimeter Computer Network Attacks. - Justin Grana; David H. Wolpert; Joshua Neil; Dongping Xie; Tanmoy Bhattacharya 001; Russell Bent (CoRR, 2016)

Thermodynamic cost due to changing the initial distribution over states. - Artemy Kolchinsky; David H. Wolpert (CoRR, 2016)

The Free Energy Requirements of Biological Organisms; Implications for Evolution. - David H. Wolpert (Entropy, 2016)

Correction: Wolpert, D.H. The Free Energy Requirements of Biological Organisms; Implications for Evolution. Entropy 2016, 18, 138. - David H. Wolpert (Entropy, 2016)

A likelihood ratio anomaly detector for identifying within-perimeter computer network attacks. - Justin Grana; David H. Wolpert; Joshua Neil; Dongping Xie; Tanmoy Bhattacharya 001; Russell Bent (J. Netw. Comput. Appl., 2016)

Modeling Social Organizations as Communication Networks. - David H. Wolpert; Justin Grana; Brendan D. Tracey; Tim Kohler; Artemy Kolchinsky (CoRR, 2017)

The minimal hidden computer needed to implement a visible computation. - David H. Wolpert; Artemy Kolchinsky; Jeremy A. Owen (CoRR, 2017)

Number of hidden states needed to physically implement a given conditional distribution. - Jeremy A. Owen; Artemy Kolchinsky; David H. Wolpert (CoRR, 2017)

Constraints on physical reality arising from a formalization of knowledge. - David H. Wolpert (CoRR, 2017)

Coarse-Graining and the Blackwell Order. - Johannes Rauh; Pradeep Kr. Banerjee; Eckehard Olbrich; Jürgen Jost; Nils Bertschinger; David H. Wolpert (Entropy, 2017)

Bias-Variance Trade-Offs: Novel Applications. - Dev G. Rajnarayan; David H. Wolpert (Encyclopedia of Machine Learning and Data Mining, 2017)

Exact, complete expressions for the thermodynamic costs of circuits. - David Hilton Wolpert; Artemy Kolchinsky (CoRR, 2018)

Beyond Number of Bit Erasures: New Complexity Questions Raised by Recently Discovered Thermodynamic Costs of Computation. - Joshua A. Grochow; David H. Wolpert (SIGACT News, 2018)

Stochastic thermodynamics of computation. - David H. Wolpert (CoRR, 2019)

Thermodynamic Computing. - Tom Conte 001; Erik DeBenedictis; Natesh Ganesh; Todd Hylton; John Paul Strachan; R. Stanley Williams; Alexander A. Alemi; Lee Altenberg; Gavin E. Crooks; James P. Crutchfield; Lídia del Rio; Josh Deutsch; et al. (CoRR, 2019)

Uncertainty relations and fluctuation theorems for Bayes nets. - David H. Wolpert (CoRR, 2019)

Thermodynamic costs of Turing Machines. - Artemy Kolchinsky; David H. Wolpert (CoRR, 2019)

Nonlinear Information Bottleneck. - Artemy Kolchinsky; Brendan D. Tracey; David H. Wolpert (Entropy, 2019)

How Much Would You Pay to Change a Game before Playing It? - David H. Wolpert; Justin Grana (Entropy, 2019)

Deep Reinforcement Learning for Event-Driven Multi-Agent Decision Processes. - Kunal Menda; Yi-Chun Chen 004; Justin Grana; James W. Bono; Brendan D. Tracey; Mykel J. Kochenderfer; David H. Wolpert (IEEE Trans. Intell. Transp. Syst., 2019)

Minimum entropy production in multipartite processes due to neighborhood constraints. - David H. Wolpert (CoRR, 2020)

What is important about the No Free Lunch theorems? - David H. Wolpert (CoRR, 2020)

Entropy production and thermodynamics of information under protocol constraints. - Artemy Kolchinsky; David H. Wolpert (CoRR, 2020)

Noisy Deductive Reasoning: How Humans Construct Math, and How Math Constructs Universes. - David H. Wolpert; David Kinney (CoRR, 2020)

The state dependence of integrated, instantaneous, and fluctuating entropy production in quantum and classical processes. - Artemy Kolchinsky; David H. Wolpert (CoRR, 2021)

The Implications of the No-Free-Lunch Theorems for Meta-induction. - David H. Wolpert (CoRR, 2021)

The Past as a Stochastic Process. - David H. Wolpert; Michael H. Price; Stefani A. Crabtree; Timothy A. Kohler; Jürgen Jost; James Evans; Peter F. Stadler; Hajime Shimao; Manfred D. Laubichler (CoRR, 2021)

What can we know about that which we cannot even imagine? - David H. Wolpert (CoRR, 2022)

Social Scale and Collective Computation: Does Information Processing Limit Rate of Growth in Scale? - Timothy A. Kohler; Darcy Bird; David H. Wolpert (J. Soc. Comput., 2022)

The fundamental thermodynamic costs of communication. - Farita Tasnim; Nahuel Freitas; David H. Wolpert (CoRR, 2023)

Game Manipulators - the Strategic Implications of Binding Contracts. - Maria Alejandra Ramirez; Yoav Kolumbus; Rosemarie Nagel; David H. Wolpert; Jürgen Jost (CoRR, 2023)

Is stochastic thermodynamics the key to understanding the energy costs of computation? - David H. Wolpert; Jan Korbel; Christopher Lynn; Farita Tasnim; Joshua A. Grochow; Gülce Kardes; James B. Aimone; Vijay Balasubramanian; Eric De Giuli; David Doty; Nahuel Freitas; Matteo Marsili; et al. (CoRR, 2023)

Stochastic Thermodynamics of Multiple Co-Evolving Systems - Beyond Multipartite Processes. - Farita Tasnim; David H. Wolpert (Entropy, 2023)

Implications of computer science theory for the simulation hypothesis. - David H. Wolpert (CoRR, 2024)

The computational power of a human society: a new model of social evolution. - David H. Wolpert; Kyle Harper (CoRR, 2024)

Stochastic Process Turing Machines. - David H. Wolpert; Jordan Scharnhorst (CoRR, 2024)

Memory Systems, the Epistemic Arrow of Time, and the Second Law. - David H. Wolpert; Jens Kipper (Entropy, 2024)

Non-coercive extortion in game theory. - Maria Alejandra Ramirez; Rosemarie Nagel; David H. Wolpert; Jürgen Jost (CoRR, 2025)