This paper presents two results concerning uniform confidence intervals for the tail index and the extreme quantile. First, we show that there exists a lower bound of the length for confidence intervals that satisfy t...
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The transformer models have been extensively used with good results in a wide area of machine learning applications including Large Language Models and image generation. Here, we inquire on the applicability of this a...
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We revisit the problem of online portfolio allocation first introduced by Cover. We propose factor weighing of the dirichlet sampling to construct universal portfolios that out-perform those using uniform dirichlet sa...
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The analysis of screening experiments is often done in two stages, starting with factor selection via an analysis under a main effects model. The success of this first stage is influenced by three components: (1) main...
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We address the problem of sequential prediction with expert advice in a nonstationary environment with long-term memory guarantees in the sense of Bousquet and Warmuth [4]. We give a linear-time algorithm that improve...
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ISBN:
(纸本)9781713845393
We address the problem of sequential prediction with expert advice in a nonstationary environment with long-term memory guarantees in the sense of Bousquet and Warmuth [4]. We give a linear-time algorithm that improves on the best known regret bounds [27]. This algorithm incorporates a relative entropy projection step. This projection is advantageous over previous weight-sharing approaches in that weight updates may come with implicit costs as in for example portfolio optimization. We give an algorithm to compute this projection step in linear time, which may be of independent interest.
The paper aims: - This paper aims to provide a comprehensive systematic literature review on portfolio optimization by analyzing their keywords, top journals, most cited authors, leading organizations, and most cited ...
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In this paper, we study the portfolio optimization problem formulated by Lacker and Soret [1]. They formulate a finite time horizon model that allows agents to be competitive, measuring their utility not only by their...
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Blockchain as a distributed ledger technology can be very effective in providing access control and big data management in health-care systems. Because implementing or migrating to a pure blockchain solution is an ext...
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Blockchain as a distributed ledger technology can be very effective in providing access control and big data management in health-care systems. Because implementing or migrating to a pure blockchain solution is an extremely challenging task, several design and implementation dynamics should be considered.
The neural distributed ledger so lution presented here adopts a ledger-of-ledgers approach to perform the interconnection of multiple ledgers. Beyond interledger operability, it also enables the development of custom ...
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The neural distributed ledger so lution presented here adopts a ledger-of-ledgers approach to perform the interconnection of multiple ledgers. Beyond interledger operability, it also enables the development of custom blockchain-based solutions, providing controlled costs and scalability while retaining decentralization and security.
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