Committee Selection with a Weight Constraint Based on a Pairwise Dominance Relation,ly, we assume that we only have a classification of the items into ordered classes. We aim at generating the set of preferred subsets of items, according to a pairwise dominance relation between subsets that naturally extends the ordering relation over classes [4,16]. We first show that the problem
作者: concert 時(shí)間: 2025-3-26 23:54
作者: Hallmark 時(shí)間: 2025-3-27 04:10
作者: textile 時(shí)間: 2025-3-27 06:57
作者: duplicate 時(shí)間: 2025-3-27 10:35
作者: 確定方向 時(shí)間: 2025-3-27 15:05
Efficiently Eliciting Preferences from a Group of Users,ers, we can use the preferences of the users we have already processed to increase the efficiency of the elicitation process for the remaining users. However, current methods either require strong prior knowledge about the users’ preferences or can be overly cautious and inefficient. Our method, bas
作者: 沙草紙 時(shí)間: 2025-3-27 18:47
作者: ellagic-acid 時(shí)間: 2025-3-28 00:52
作者: Consensus 時(shí)間: 2025-3-28 04:07
Vote Elicitation with Probabilistic Preference Models: Empirical Estimation and Cost Tradeoffs,rement that participants provide full preference information in the form of a complete ranking of alternatives is a severe impediment to their practical deployment. Only recently have incremental elicitation schemes been proposed that allow winners to be determined with partial preferences; however,
作者: 做方舟 時(shí)間: 2025-3-28 08:25
Efficient Approximation Algorithms for Multi-objective Constraint Optimization, optimization. Our approach builds upon recent advances in multi-objective heuristic search over weighted AND/OR search spaces and uses an .-dominance relation between cost vectors to significantly reduce the set of non-dominated solutions. Our empirical evaluation on various benchmarks demonstrates
作者: 治愈 時(shí)間: 2025-3-28 13:35
Empirical Evaluation of Voting Rules with Strictly Ordered Preference Data,rive several million elections (more than all the existing studies combined) from a publicly available data, the Netflix Prize dataset. The Netflix data is derived from millions of Netflix users, who have an incentive to report sincere preferences, unlike random survey takers. We evaluate each of th
作者: 遍及 時(shí)間: 2025-3-28 17:51
作者: chisel 時(shí)間: 2025-3-28 22:08
On Minimizing Ordered Weighted Regrets in Multiobjective Markov Decision Processes,ediate reward functions, representing either individual payoffs in a multiagent problem or rewards with respect to different objectives. In this context, we focus on the determination of a policy that fairly shares regrets among agents or objectives, the regret being defined on each dimension as the
作者: noxious 時(shí)間: 2025-3-29 02:30
Scaling Invariance and a Characterization of Linear Objective Functions,sign of the selection method. If the representation of valuations of available alternatives is subject to invariance under linear scaling, such as the choice of the unit of measurement, a sensible way to compare choices is to compare weighted sums of individual valuations corresponding to these choi
作者: deceive 時(shí)間: 2025-3-29 06:37
作者: Implicit 時(shí)間: 2025-3-29 09:24
作者: STRIA 時(shí)間: 2025-3-29 12:36
Bribery in Path-Disruption Games,ersaries want to travel from a source vertex to a target vertex. In order to prevent them from doing so, the agents can form coalitions, and a coalition wins if it succeeds in blocking all paths for the adversaries. In this paper, we introduce the notion of bribery for path-disruption games. We anal
作者: 同時(shí)發(fā)生 時(shí)間: 2025-3-29 18:29
作者: integrated 時(shí)間: 2025-3-29 19:51
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/a/image/152918.jpg
作者: 兒童 時(shí)間: 2025-3-30 02:37
作者: Kinetic 時(shí)間: 2025-3-30 07:17
Arno Wolter,Michaela Grahl,J?rg Ehlerso specific judgment aggregation procedures to a whole class of such procedures, and we obtain stronger results by considering not only the classical complexity (NP-hardness) but the parameterized complexity (W[2]-hardness) of these problems with respect to natural parameters. Furthermore, we introdu
作者: 中和 時(shí)間: 2025-3-30 09:31
Dependable Computing – EDCC 2022 Workshopsn, and a value 0
作者: CHURL 時(shí)間: 2025-3-30 16:43
作者: Petechiae 時(shí)間: 2025-3-30 21:24
作者: forbid 時(shí)間: 2025-3-31 04:31
作者: 收養(yǎng) 時(shí)間: 2025-3-31 07:23
G. Masseboeuf,J. Pulou,J. L. Rainardning of the items. For that task, we compare two combinatorial approaches. The first one allows to calculate a consensus partition, namely the median partition of the profile, which is the partition of . whose sum of distances to the individual partitions is minimum. Then, the collective classes are
作者: Confess 時(shí)間: 2025-3-31 11:03
Silke Draber,Bernhard Eschermanners, we can use the preferences of the users we have already processed to increase the efficiency of the elicitation process for the remaining users. However, current methods either require strong prior knowledge about the users’ preferences or can be overly cautious and inefficient. Our method, bas
作者: Oratory 時(shí)間: 2025-3-31 15:09
https://doi.org/10.1007/3-540-48254-7 regulatory inspections of sites - and consequently losing revenue - is minimized. In the proposed decision model the regulatory authority is an adversary. The outcome of an inspection is a Bernoulli-distributed random variable whose parameter is a function of production decisions. Our goal is to op
作者: 考博 時(shí)間: 2025-3-31 17:56
Lecture Notes in Computer Science providing minimal and complete explanations, a problem relevant in critical situations where the stakes are very high. More specifically, we are after explanations with minimal cost supporting the fact that a choice is the weighted Condorcet winner in a multi-attribute problem. We introduce differe
作者: 菊花 時(shí)間: 2025-4-1 01:01
作者: gnarled 時(shí)間: 2025-4-1 02:42
作者: 團(tuán)結(jié) 時(shí)間: 2025-4-1 07:33
Irina Alam,Lara Dolecek,Puneet Guptarive several million elections (more than all the existing studies combined) from a publicly available data, the Netflix Prize dataset. The Netflix data is derived from millions of Netflix users, who have an incentive to report sincere preferences, unlike random survey takers. We evaluate each of th
作者: BRIEF 時(shí)間: 2025-4-1 11:13
Irina Alam,Lara Dolecek,Puneet Gupta 2-additive capacity step, the inconsistencies of the preferential information, given by the Decision Maker on the set of binary alternatives, is tested by using the MOPI conditions. Since a 2-additive capacity is related to all binary alternatives, this inconsistencies checking can be more complex
作者: transplantation 時(shí)間: 2025-4-1 16:28
Irina Alam,Lara Dolecek,Puneet Guptaediate reward functions, representing either individual payoffs in a multiagent problem or rewards with respect to different objectives. In this context, we focus on the determination of a policy that fairly shares regrets among agents or objectives, the regret being defined on each dimension as the
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