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We examine the problem of learning a set of parameters from a distributed dataset. We assume the datasets are collected by agents over a distributed ad-hoc network, and that the communication of the actual raw data is prohibitive due to either privacy cons ...
Social media is emerging as a powerful source of communication, information dissemination and mining. Being colloquial and ubiquitous in nature makes it easier for users to express their opinions and preferences in a seamless, dynamic manner. Epidemic surv ...
Selection and aggregation of ranking criteria became an important topic in information retrieval as search is getting more specialized and as volume of electronically available information grows. In this context, document ranking has undergone a shift from ...
We revisit a recently developed iterative learning algorithm that enables systems to learn from a repeated operation with the goal of achieving high tracking performance of a given trajectory. The learning scheme is based on a coarse dynamics model of the ...
We study the task of learning to rank images given a text query, a problem that is complicated by the issue of multiple senses. That is, the senses of interest are typically the visually distinct concepts that a user wishes to retrieve. In this paper, we p ...
In conventional vector space model for information retrieval, query vector generation is imperfect for retrieval of precise documents which are de-sired by user. In this paper, we present a stochastic based approach for optimiz-ing query vector without use ...
This paper explores a crowdsourcing approach to the evaluation of a document recommender system intended for use in meetings. The system uses words from the conversation to perform just-in-time document retrieval. We compare several versions of the system, ...
Very often, the only reliable information available to perform change detection is the description of some unchanged regions. Since sometimes these regions do not contain all the relevant information to identify their counterpart (the changes), we consider ...
Institute of Electrical and Electronics Engineers2013
Our research addresses the need for an efficient, effective, and interactive access to large-scale image collections. Image retrieval needs are evolving beyond the capabilities of the traditional indexing based on manual annotation, and the most desirable ...
Machine Learning techniques play an increasingly vital role in the analysis of Biomedical imagery, as in all other areas of Computer Vision. However, in this specific context, they suffer from the fact that experimental conditions and protocols change ofte ...
