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Results 11 - 20
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106
Off-line Signature Verification Using Enhanced Modified Direction Features in Conjunction with Neural Classifiers and Support Vector Machines
"... As a biometric, signatures have been widely used to identify people. In the context of static image processing, the lack of dynamic information such as velocity, pressure and the direction and sequence of strokes has made the realization of accurate off-line signature verification systems more chall ..."
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Cited by 5 (2 self)
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challenging as compared to their on-line counterparts. In this paper, we propose an effective method to perform off-line signature verification based on intelligent techniques. Structural features are extracted from the signature's contour using the Modified Direction Feature (MDF) and its extended
German wineries on the web: A survey of web sites of Mosel-Saar-Ruwer and Pfalz wineries.
"... In this paper we report results of a survey of web sites by wineries from the Mosel-Saar-Ruwer and Pfalz regions in Germany. The wine industries in both regions are characterized by many small wine growers who process their own grapes and who market some or all of their wine directly to consumers. A ..."
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Cited by 1 (0 self)
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. A surprisingly large share of the wineries ’ web sites surveyed provide information and also allow the wineries to sell wine through the site. The wineries present on the web are on average larger than their offline counterparts, but there is evidence that, small wineries will also participate as e
Certainty-based Prototype Insertion/Deletion for Classification with Metric Adaptation
"... Abstract. We propose an extension of prototype-based classification models to automatically adjust model complexity, thus offering a powerful technique for online, incremental learning tasks. The incremental technique is based on the notion of the certainty of an observed classification. Unlike prev ..."
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Cited by 1 (1 self)
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to offline counterparts and an incremental support vector machine, while enabling a better control of the required memory. 1
Diamond in the Rough: Finding Hierarchical Heavy Hitters in Multi-Dimensional Data
- In Proceedings of the 23rd ACM SIGMOD International Conference on Management of Data
, 2004
"... Data items archived in data warehouses or those that arrive online as streams typically have attributes which take values from multiple hierarchies (e.g., time and geographic location; source and destination IP addresses). Providing an aggregate view of such data is important to summarize, visualize ..."
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Cited by 44 (2 self)
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experimentally, using real and synthetic data, that our proposed online algorithms yield outputs which are very similar (virtually identical, in many cases) to their offline counterparts. The lattice property of the product of hierarchical dimensions (“diamond”) is crucially exploited in our online algorithms
World With Web A compiler from world applications to JavaScript
"... Our methods for interacting with computers have changed drastically over the last 10 years. As web based technologies improve, online applications are starting to replace their offline counterparts. In the world of online interaction, our educational tools also need to be adapted for this environmen ..."
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Our methods for interacting with computers have changed drastically over the last 10 years. As web based technologies improve, online applications are starting to replace their offline counterparts. In the world of online interaction, our educational tools also need to be adapted
Efficient On-Line Call Control Algorithms
, 1993
"... We study the problem of on-line call control, i.e., the problem of accepting or rejecting an incoming call without knowledge of future calls. The problem is a part of the more general problem of bandwidth allocation and management. Intuition suggests that knowledge of future call arrivals can be ..."
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Cited by 67 (2 self)
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be crucial to the performance of the system. In this paper, however, we present preemptive deterministic on-line call control algorithms. We use competitive analysis to measure their performance--- i.e., we compare our algorithms to their off-line, clairvoyant counterparts---and prove optimality for some
Prominent Features of Rumor Propagation in Online Social Media
"... Abstract—The problem of identifying rumors is of practical importance especially in online social networks, since infor-mation can diffuse more rapidly and widely than the offline counterpart. In this paper, we identify characteristics of rumors by examining the following three aspects of diffusion: ..."
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Cited by 7 (0 self)
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Abstract—The problem of identifying rumors is of practical importance especially in online social networks, since infor-mation can diffuse more rapidly and widely than the offline counterpart. In this paper, we identify characteristics of rumors by examining the following three aspects of diffusion
Online least-squares policy iteration for reinforcement learning control
- In Proceedings of the 2010 American Control Conference (ACC
, 2010
"... Abstract-Reinforcement learning is a promising paradigm for learning optimal control. We consider policy iteration (PI) algorithms for reinforcement learning, which iteratively evaluate and improve control policies. State-of-the-art, least-squares techniques for policy evaluation are sample-efficie ..."
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Cited by 12 (3 self)
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-functions (LSTD-Q). The crucial difference between this online least-squares policy iteration (LSPI) algorithm and its offline counterpart is that, in the online case, policy improvements must be performed once every few state transitions, using only an incomplete evaluation of the current policy. In an extensive
The Effect of Risk Perceptions on Online Political Participatory Decisions
"... ABSTRACT. Since the emergence of the Internet as an outlet for mass political participation, there has been considerable disagreement over whether political activities can be performed reliably and securely online. In this paper, we consider one aspect of this debate, assessing whether the general p ..."
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Cited by 2 (0 self)
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consequences than do their offline counterparts. We then demonstrate that risk perceptions are a significant factor in decisions to participate in a variety of online political activities. We conclude by discussing the implications of these findings. doi:10.1300/J516v04n01_02 [Article copies available
Theoretical analysis of heuristic search methods for online pomdps
, 2007
"... Planning in partially observable environments remains a challenging problem, despite significant recent advances in offline approximation techniques. A few online methods have also been proposed recently, and proven to be remarkably scalable, but without the theoretical guarantees of their offline c ..."
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Cited by 3 (1 self)
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counterparts. Thus it seems natural to try to unify offline and online techniques, preserving the theoretical properties of the former, and exploiting the scalability of the latter. In this paper, we provide theoretical guarantees on an anytime algorithm for POMDPs which aims to reduce the error made
Results 11 - 20
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106
