Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Soufiani, Hossein Azari"'
Buyers (e.g., advertisers) often have limited financial and processing resources, and so their participation in auctions is throttled. Changes to auctions may affect bids or throttling and any change may affect what winners pay. This paper shows that
Externí odkaz:
http://arxiv.org/abs/1605.09171
Recommendation systems have been widely used by commercial service providers for giving suggestions to users. Collaborative filtering (CF) systems, one of the most popular recommendation systems, utilize the history of behaviors of the aggregate user
Externí odkaz:
http://arxiv.org/abs/1604.03757
In this paper, we take a statistical decision-theoretic viewpoint on social choice, putting a focus on the decision to be made on behalf of a system of agents. In our framework, we are given a statistical ranking model, a decision space, and a loss f
Externí odkaz:
http://arxiv.org/abs/1410.7856
The well-studied problem of statistical rank aggregation has been applied to comparing sports teams, information retrieval, and most recently to data generated by human judgment. Such human-generated rankings may be substantially different from tradi
Externí odkaz:
http://arxiv.org/abs/1311.0251
This paper discusses {General Random Utility Models (GRUMs)}. These are a class of parametric models that generate partial ranks over alternatives given attributes of agents and alternatives. We propose two preference elicitation scheme for GRUMs dev
Externí odkaz:
http://arxiv.org/abs/1309.6864
Random utility theory models an agent's preferences on alternatives by drawing a real-valued score on each alternative (typically independently) from a parameterized distribution, and then ranking the alternatives according to scores. A special case
Externí odkaz:
http://arxiv.org/abs/1211.2476
Publikováno v:
Journal of Machine Learning Research, Workshop & Conference Proceedings, vol. 22 (AISTATS), 2012
We introduce the graphlet decomposition of a weighted network, which encodes a notion of social information based on social structure. We develop a scalable inference algorithm, which combines EM with Bron-Kerbosch in a novel fashion, for estimating
Externí odkaz:
http://arxiv.org/abs/1203.2821