Results 271 to 280 of about 34,082,428 (320)
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Value Maximization, Stakeholder Theory, and the Corporate Objective Function*
Business Ethics Quarterly, 2001: In this article, I offer a proposal to clarify what I believe is the proper relation between value maximization and stakeholder theory, which I call enlightened value maximization.
M. C. Jensen
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On Learning Vector-Valued Functions
Neural Computation, 2005In this letter, we provide a study of learning in a Hilbert space of vector-valued functions. We motivate the need for extending learning theory of scalar-valued functions by practical considerations and establish some basic results for learning vector-valued functions that should prove useful in applications.
Micchelli, Charles A. +1 more
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Deep soccer analytics: learning an action-value function for evaluating soccer players
Data mining and knowledge discovery, 2020Guiliang Liu +3 more
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The Cluster Function of Single-Valued Functions
Set-Valued Analysis, 2006Let \(X\) and \(Y\) be topological spaces and let \(F : X \to 2^{Y}\) be a multifunction. Then the cluster set and the reduced cluster set of \(F\) at a point \(x \in X\) are \[ C(F; x) = \bigcap_{U \in {\mathcal U}(x)} \text{cl}_{Y}(F(U)) \quad \text{and}\quad C^{r}(F; x) = \bigcap_{U \in {\mathcal U}(x)} \text{cl}_{Y}(F(U \setminus \{x\})), \] where \
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On η-valued functionally complete truth functions
Journal of Symbolic Logic, 1967It is well known that the familiar Sheffer stroke function of the 2-valued propositional calculus is functionally complete (i.e., for any m, all 22m truth functions of m variables can be defined1 in terms of the stroke function). Indeed, it is not difficult to show that of the 16 2-valued functions of two variables, exactly two of them are functionally
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1970
Imagine a particle moving in the plane ℝ2, which is at the point z at time t. Its motion gives us a function ζ: I ↔ ℝ2, where I is the time interval of its motion, and ζ(t) is its position at time t.
H. B. Griffiths, P. J. Hilton
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Imagine a particle moving in the plane ℝ2, which is at the point z at time t. Its motion gives us a function ζ: I ↔ ℝ2, where I is the time interval of its motion, and ζ(t) is its position at time t.
H. B. Griffiths, P. J. Hilton
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Two-Timescale Networks for Nonlinear Value Function Approximation
International Conference on Learning Representations, 2019Wesley Chung +3 more
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