1,189 research outputs found
La politique / Aristote ; traduction de Champagne ; revue et corrigée par M. Hoefer. L'économique / Aristote ; traduction nouvelle de M. Hoefer. Lettre à Alexandre sur le monde / Aristote ; traduction de Batteux...
No full text[Politique (français)]Comprend : L'économique / Aristote ; traduction nouvelle de M. Hoefer ; Lettre à Alexandre sur le monde / Aristote ; traduction de BatteuxContient une table des matièresAvec mode text
Smoothness for simultaneous composition of mechanisms with admission
No full textWe study social welfare of learning outcomes in mechanisms with admission. In our repeated game there are n bidders and m mechanisms, and in each round each mechanism is available for each bidder only with a certain probability. Our scenario is an elementary case of simple mechanism design with incomplete information, where availabilities are bidder types. It captures natural applications in online markets with limited supply and can be used to model access of unreliable channels in wireless networks. If mechanisms satisfy a smoothness guarantee, existing results show that learning outcomes recover a significant fraction of the optimal social welfare. These approaches, however, have serious drawbacks in terms of plausibility and computational complexity. Also, the guarantees apply only when availabilities are stochastically independent among bidders. In contrast, we propose an alternative approach where each bidder uses a single no-regret learning algorithm and applies it in all rounds. This results in what we call availability-oblivious coarse correlated equilibria. It exponentially decreases the learning burden, simplifies implementation (e.g., as a method for channel access in wireless devices), and thereby addresses some of the concerns about Bayes-Nash equilibria and learning outcomes in Bayesian settings. Our main results are general composition theorems for smooth mechanisms when valuation functions of bidders are lattice-submodular. They rely on an interesting connection to the notion of correlation gap of submodular functions over product lattices
Combinatorial secretary problems with ordinal information
No full textThe secretary problem is a classic model for online decision making. Recently, combinatorial extensions such as matroid or matching secretary problems have become an important tool to study algorithmic problems in dynamic markets. Here the decision maker must know the numerical value of each arriving element, which can be a demanding informational assumption. In this paper, we initiate the study of combinatorial secretary problems with ordinal information, in which the decision maker only needs to be aware of a preference order consistent with the values of arrived elements. The goal is to design online algorithms with small competitive ratios. For a variety of combinatorial problems, such as bipartite matching, general packing LPs, and independent set with bounded local independence number, we design new algorithms that obtain constant competitive ratios. For the matroid secretary problem, we observe that many existing algorithms for special matroid structures maintain their competitive ratios even in the ordinal model. In these cases, the restriction to ordinal information does not represent any additional obstacle. Moreover, we show that ordinal variants of the submodular matroid secretary problems can be solved using algorithms for the linear versions by extending [18]. In contrast, we provide a lower bound of ω(√n/(log n)) for algorithms that are oblivious to the matroid structure, where n is the total number of elements. This contrasts an upper bound of O(log n) in the cardinal model, and it shows that the technique of thresholding is not sufficient for good algorithms in the ordinal model
ORATIO || M. VVOLFGANGI HOEVERI || De Fortuna.|| ... ||
No full textORATIO || M. VVOLFGANGI HOEVERI || DE FORTUNA.|| ... ||
ORATIO || M. VVOLFGANGI HOEVERI || De Fortuna.|| ... || (1)
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Oratio de fortuna (5)
Decanus Facultatis Philosophicae in Academia Lipsensi, &c. (29
ChemInform Abstract: A New Method for the Selective Bridge Functionalization of [2.2]Paracyclophanediene - Indenyl-Anellated [2.2]Paracyclophanedienes and Their Iron Complexes.
No full textSupplemental Material, 20171119_Supl_fig_2 - Hematological Parameters Outperform Plasma Markers in Predicting Long-Term Mortality After Coronary Angiography
Get PDFSupplemental Material, 20171119_Supl_fig_2 for Hematological Parameters Outperform Plasma Markers in Predicting Long-Term Mortality After Coronary Angiography by Crystel M. Gijsberts, Hester M. den Ruijter, Dominique P. V. de Kleijn, Albert Huisman, Maarten ten Berg, Mark de Groot, Richard H. A. van Wijk, Folkert W. Asselbergs, Michiel Voskuil, Gerard Pasterkamp, Wouter W. van Solinge, and Imo E. Hoefer in Angiology</p
On Stackelberg Pricing with Computationally Bounded Customers
No full textIn Stackelberg pricing a leader sets prices for items to maximize revenue from a follower purchasing a feasible subset of items. We consider computationally bounded followers who cannot optimize exactly over the range of all feasible subsets, but who apply publicly known algorithms to determine the items to purchase. This corresponds to general multidimensional pricing when customers cannot optimize their valuation functions efficiently but still aim to act rationally to the best of their ability. We consider two versions of this novel type of pricing problem. In the MIn-KNAPSACK variant items are weighted objects and the follower seeks to purchase a min-cost selection of objects of some bounded weight. When he uses a greedy 2-approximation algorithm, we provide a polynomial-time (2+ε) -approximation algorithm for the leader's revenue maximization problem based on so-called near-uniform price assignments. We also prove the problem to be strongly NP-hard. In the SET-COVER variant items are subsets of some ground set which the follower seeks to cover. When he uses a standard primal-dual approach, we prove that exact revenue maximization is possible in polynomial time when elements have frequency 2 (VERTEX-COVER variant). This stands in sharp contrast to APX-hardness for the problem with elements of frequency 3. © 2011 Wiley Periodicals, Inc. NETWORKS, 201
On Stackelberg Pricing with Computationally Bounded Consumers
No full textIn a Stackelberg pricing game a leader aims to set prices on a subset of a given collection of items, such as to maximize her revenue from a follower purchasing a feasible subset of the items. We focus on the case of computationally bounded followers who cannot optimize exactly over the range of all feasible subsets, but apply some publicly known algorithm to determine the set of items to purchase. This corresponds to general multi-dimensional pricing assuming that consumers cannot optimize over the full domain of their valuation functions but still aim to act rationally to the best of their ability.
We consider two versions of this novel type of Stackelberg pricing games. Assuming that items are weighted objects and the follower seeks to purchase a min-cost selection of objects of some minimum weight (the Min-Knapsack problem) and uses a simple greedy 2-approximate algorithm, we show how an extension of the known single-price algorithm can be used to derive a polynomial-time (2 + ε)-approximation algorithm for the leader’s revenue maximization problem based on so-called near-uniform price assignments. We also prove the problem to be strongly NP-hard.
Considering the case that items are subsets of some ground set which the follower seeks to cover (the Set-Cover problem) via a standard primal-dual approach, we prove that near-uniform price assignments fail to yield a good approximation guarantee. However, in the special case of elements with frequency 2 (the Vertex-Cover problem) it turns out that exact revenue maximization can be done in polynomial-time. This stands in sharp contrast to the fact that revenue maximization becomes APX-hard already for elements with frequency 3
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