The Experts below are selected from a list of 153291 Experts worldwide ranked by ideXlab platform
Pär Holmberg - One of the best experts on this subject based on the ideXlab platform.
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unique supply function equilibrium with capacity constraints
Energy Economics, 2008Co-Authors: Pär HolmbergAbstract:Consider a market where producers submit supply functions to a procurement auction — e.g. an electric power auction — under uncertainty, before demand has been realized. In the Supply Function Equilibrium (SFE), every firm commits to the supply function maximizing his expected profit given the supply functions of the competitors. The presence of multiple equilibria is one basic weakness of SFE. This paper shows that with (i) symmetric producers, (ii) inelastic demand, (iii) a reservation price, and (iiii) capacity constraints that bind with a Positive Probability, there is a unique symmetric SFE.
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unique supply function equilibrium with capacity constraints
Energy Economics, 2008Co-Authors: Pär HolmbergAbstract:Consider a market where producers submit supply functions to a procurement auction — e.g. an electric power auction — under uncertainty, before demand has been realized. In the Supply Function Equilibrium (SFE), every firm commits to the supply function maximizing his expected profit given the supply functions of the competitors. The presence of multiple equilibria is one basic weakness of SFE. This paper shows that with (i) symmetric producers, (ii) inelastic demand, (iii) a reservation price, and (iiii) capacity constraints that bind with a Positive Probability, there is a unique symmetric SFE.
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Asymmetric Supply Function Equilibrium with Constant Marginal Costs
2005Co-Authors: Pär HolmbergAbstract:In a real-time electric power auction, the bids of producers consist of committed supply as a function of price. The bids are submitted under uncertainty, before the demand by the Independent System Operator has been realized. In the Supply Function Equilibrium (SFE), every producer chooses the supply function maximizing his expected profit given his residual demand. I consider a uniform-price auction with a reservation price, where demand is inelastic and exceed the market capacity with a Positive Probability, and firms have identical constant marginal costs but asymmetric capacities. I show that under these conditions, there is a unique SFE, which is piece-wise symmetric.
Rasmus Pagh - One of the best experts on this subject based on the ideXlab platform.
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approximate range emptiness in constant time and optimal space
Symposium on Discrete Algorithms, 2015Co-Authors: Mayank Goswami, Allan Gronlund, Kasper Green Larsen, Rasmus PaghAbstract:This paper studies the e-approximate range emptiness problem, where the task is to represent a set S of n points from {0, . . ., U − 1} and answer emptiness queries of the form "[a; b] ∩ S ≠ O ?" with a Probability of false Positives allowed. This generalizes the functionality of Bloom filters from single point queries to any interval length L. Setting the false Positive rate to e/L and performing L queries, Bloom filters yield a solution to this problem with space O(n lg(L/e)) bits, false Positive Probability bounded by e for intervals of length up to L, using query time O(L lg(L/e)). Our first contribution is to show that the space/error trade-off cannot be improved asymptotically: Any data structure for answering approximate range emptiness queries on intervals of length up to L with false Positive Probability e, must use space Ω(n lg(L/e)) − O(n) bits. On the Positive side we show that the query time can be improved greatly, to constant time, while matching our space lower bound up to a lower order additive term. This result is achieved through a succinct data structure for (non-approximate 1d) range emptiness/reporting queries, which may be of independent interest.
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approximate range emptiness in constant time and optimal space
arXiv: Data Structures and Algorithms, 2014Co-Authors: Mayank Goswami, Allan Gronlund, Kasper Green Larsen, Rasmus PaghAbstract:This paper studies the \emph{$\varepsilon$-approximate range emptiness} problem, where the task is to represent a set $S$ of $n$ points from $\{0,\ldots,U-1\}$ and answer emptiness queries of the form "$[a ; b]\cap S \neq \emptyset$ ?" with a Probability of \emph{false Positives} allowed. This generalizes the functionality of \emph{Bloom filters} from single point queries to any interval length $L$. Setting the false Positive rate to $\varepsilon/L$ and performing $L$ queries, Bloom filters yield a solution to this problem with space $O(n \lg(L/\varepsilon))$ bits, false Positive Probability bounded by $\varepsilon$ for intervals of length up to $L$, using query time $O(L \lg(L/\varepsilon))$. Our first contribution is to show that the space/error trade-off cannot be improved asymptotically: Any data structure for answering approximate range emptiness queries on intervals of length up to $L$ with false Positive Probability $\varepsilon$, must use space $\Omega(n \lg(L/\varepsilon)) - O(n)$ bits. On the Positive side we show that the query time can be improved greatly, to constant time, while matching our space lower bound up to a lower order additive term. This result is achieved through a succinct data structure for (non-approximate 1d) range emptiness/reporting queries, which may be of independent interest.
Umer Salim - One of the best experts on this subject based on the ideXlab platform.
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gaussian half duplex relay networks improved constant gap and connections with the assignment problem
IEEE Transactions on Information Theory, 2014Co-Authors: Martina Cardone, Daniela Tuninetti, Raymond Knopp, Umer SalimAbstract:This paper considers a Gaussian relay network where a source transmits a message to a destination with the help of $N$ half-duplex relays. The information theoretic cut-set upper bound to the capacity is shown to be achieved to within $1.96(N+2)$ bits by noisy network coding, thereby reducing the previously known gap. This gap is obtained as a special case of a more general constant gap result for Gaussian half-duplex multicast networks. It is then shown that the generalized degrees-of-freedom of this network is the solution of a linear program, where the coefficients of the linear inequality constraints are proved to be the solution of several linear programs referred as the assignment problem in graph theory, for which efficient numerical algorithms exist. The optimal schedule, that is, the optimal value of the $2^{N}$ possible transmit-receive configuration states for the relays, is investigated and known results for diamond networks are extended to general relay networks. It is shown, for the case of $N=2$ relays, that only $N+1=3$ out of the $2^{N}=4$ possible states have a strictly Positive Probability and suffice to characterize the capacity to within a constant gap. Extensive experimental results show that, for a general $N$ -relay network with $N\leq 8$ , the optimal schedule has at most $N+1$ states with a strictly Positive Probability. As an extension of a conjecture presented for diamond networks, it is conjectured that this result holds for any half-duplex relay network and any number of relays. Finally, a network with $N=2$ relays is studied in detail to illustrate the channel conditions under which selecting the best relay is not optimal, and to highlight the nature of the rate gain due to multiple relays.
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gaussian half duplex relay networks improved constant gap and connections with the assignment problem
arXiv: Information Theory, 2013Co-Authors: Martina Cardone, Daniela Tuninetti, Raymond Knopp, Umer SalimAbstract:This paper considers a general Gaussian relay network where a source transmits a message to a destination with the help of N half-duplex relays. It proves that the information theoretic cut-set upper bound to the capacity can be achieved to within 2:021(N +2) bits with noisy network coding, thereby reducing the previously known gap. Further improved gap results are presented for more structured networks like diamond networks. It is then shown that the generalized Degrees-of-Freedom of a general Gaussian half-duplex relay network is the solution of a linear program, where the coefficients of the linear inequality constraints are proved to be the solution of several linear programs, known in graph theory as the assignment problem, for which efficient numerical algorithms exist. The optimal schedule, that is, the optimal value of the 2^N possible transmit-receive configurations/states for the relays, is investigated and known results for diamond networks are extended to general relay networks. It is shown, for the case of 2 relays, that only 3 out of the 4 possible states have strictly Positive Probability. Extensive experimental results show that, for a general N-relay network with N<9, the optimal schedule has at most N +1 states with strictly Positive Probability. As an extension of a conjecture presented for diamond networks, it is conjectured that this result holds for any HD relay network and any number of relays. Finally, a 2-relay network is studied to determine the channel conditions under which selecting the best relay is not optimal, and to highlight the nature of the rate gain due to multiple relays.
Thomas A Trikalinos - One of the best experts on this subject based on the ideXlab platform.
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constructions for a bivariate beta distribution
Statistics & Probability Letters, 2015Co-Authors: Ingram Olkin, Thomas A TrikalinosAbstract:We provide a new bivariate distribution with beta marginal distributions, Positive Probability over the unit square, and correlations over the full range. We discuss its extension to three or more dimensions.
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constructions for a bivariate beta distribution
arXiv: Methodology, 2014Co-Authors: Ingram Olkin, Thomas A TrikalinosAbstract:The beta distribution is a basic distribution serving several purposes. It is used to model data, and also, as a more flexible version of the uniform distribution, it serves as a prior distribution for a binomial Probability. The bivariate beta distribution plays a similar role for two probabilities that have a bivariate binomial distribution. We provide a new multivariate distribution with beta marginal distributions, Positive Probability over the unit square, and correlations over the full range. We discuss its extension to three or more dimensions.
Oded Stark - One of the best experts on this subject based on the ideXlab platform.
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a gain with a drain evidence from rural mexico on the new economics of the brain drain
2009Co-Authors: Stephen R Boucher, Oded Stark, Edward J TaylorAbstract:Recent theoretical work suggests conditions under which a Positive Probability of migration from a developing country stimulates human capital formation in that country and improves the welfare of migrants and non-migrants alike (Stark et al., 1997, 1998; Stark and Wang, 2002). This ‘brain gain’ hypothesis contrasts with the received, long-held ‘brain drain’ argument, which stipulates that the migration of skilled workers depletes the human capital stock and lowers welfare in the sending country (Usher, 1977; Blomqvist, 1986). The ‘brain gain’ view is that a strictly Positive Probability of migrating to destinations where the returns to human capital are higher than at origin creates incentives to acquire more human capital in migrant-sending areas.
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rethinking the brain drain
World Development, 2004Co-Authors: Oded StarkAbstract:When productivity is fostered by both the individual's human capital and by the average level of human capital in the economy, individuals under-invest in human capital. A strictly Positive Probability of migration to a richer country, by raising both the level of human capital formed by optimizing individuals in the home country and the average level of human capital of non-migrants in the country, can enhance welfare and nudge the economy toward the social optimum. Under a well-controlled restrictive migration policy the welfare of all workers is higher than in the absence of this policy.
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human capital depletion human capital formation and migration a blessing or a curse
Economics Letters, 1998Co-Authors: Oded Stark, Christian Helmenstein, Alexia PrskawetzAbstract:Abstract We specify conditions under which a strictly Positive Probability of employment in a foreign country raises the level of human capital formed by optimizing workers in the home country. While some workers migrate, “taking along” more human capital than if they had migrated without factoring in the possibility of migration (a form of brain drain), other workers stay at home with more human capital than they would have formed in the absence of the possibility of migration (a form of brain gain).
