Optimal Allocation Strategies for the Dark Pool Problem
... of volumes V 1 , . . . , V T and allocation limits sti to be distributed in an iid fashion. They propose an algorithm based on Kaplan-Meier estimators. Their algorithm mimics an optimal allocation strategy by estimating the tail probabilities of sti being larger than a given value. They show that th ...
... of volumes V 1 , . . . , V T and allocation limits sti to be distributed in an iid fashion. They propose an algorithm based on Kaplan-Meier estimators. Their algorithm mimics an optimal allocation strategy by estimating the tail probabilities of sti being larger than a given value. They show that th ...
Building Knowledge-Driven DSS and Mining Data
... representation scheme controlled by backward chaining. TAXADVISOR was implemented in EMYCIN. It was developed at the University of Illinois, ChampaignUrbana, as a PhD dissertation and it reached the stage of a research prototype. XCON (eXpert CONfigurer of VAX 11/780 computer systems) was developed ...
... representation scheme controlled by backward chaining. TAXADVISOR was implemented in EMYCIN. It was developed at the University of Illinois, ChampaignUrbana, as a PhD dissertation and it reached the stage of a research prototype. XCON (eXpert CONfigurer of VAX 11/780 computer systems) was developed ...
Solving the 0-1 Knapsack Problem with Genetic Algorithms
... chromosomes encodings are binary, permutation, value, and tree encodings. For the Knapsack problem, we use binary encoding, where every chromosome is a string of bits, 0 or 1. ...
... chromosomes encodings are binary, permutation, value, and tree encodings. For the Knapsack problem, we use binary encoding, where every chromosome is a string of bits, 0 or 1. ...
Identifying Condition-Action Sentences Using a Heuristic
... Abstract. Translating clinical practice guidelines into a computer-interpretable format is a challenging and laborious task. In this project we focus on supporting the early steps of the modeling process by automatically identifying conditional activities in guideline documents in order to model the ...
... Abstract. Translating clinical practice guidelines into a computer-interpretable format is a challenging and laborious task. In this project we focus on supporting the early steps of the modeling process by automatically identifying conditional activities in guideline documents in order to model the ...
Integrating Scheduling and Control Functions in Computer
... information-processing system composed of a large number of interconnected processing elements (See Figure 2).; Each of these processing elements has a number of inputs which are modified by adaptive coefftcients (weights) and generates an output signal that is a function of its weighted in inputs. ...
... information-processing system composed of a large number of interconnected processing elements (See Figure 2).; Each of these processing elements has a number of inputs which are modified by adaptive coefftcients (weights) and generates an output signal that is a function of its weighted in inputs. ...
Locality Preserving Hashing Kang Zhao, Hongtao Lu and Jincheng Mei
... Hashing has recently attracted considerable attention for large scale similarity search. However, learning compact codes with good performance is still a challenge. In many cases, the real-world data lies on a low-dimensional manifold embedded in high-dimensional ambient space. To capture meaningful ...
... Hashing has recently attracted considerable attention for large scale similarity search. However, learning compact codes with good performance is still a challenge. In many cases, the real-world data lies on a low-dimensional manifold embedded in high-dimensional ambient space. To capture meaningful ...
Hierarchical Knowledge for Heuristic Problem Solving — A Case
... observations of human behavior. Tenbrink and Seifert (2011) asked participants to plan a holiday trip and analyzed verbal reports from this task. They found that humans combined spatial knowledge with knowledge about travel modalities, for example the physical effort when riding a bike. This behavio ...
... observations of human behavior. Tenbrink and Seifert (2011) asked participants to plan a holiday trip and analyzed verbal reports from this task. They found that humans combined spatial knowledge with knowledge about travel modalities, for example the physical effort when riding a bike. This behavio ...
SOM
... • Neural networks for unsupervised learning attempt to discover special patterns from available data without using external help (i.e. RISK FUNCTION). – There is no information about the desired class (or output ) d of an example x. So only x is given. – Self Organising Maps (SOM) are neural network ...
... • Neural networks for unsupervised learning attempt to discover special patterns from available data without using external help (i.e. RISK FUNCTION). – There is no information about the desired class (or output ) d of an example x. So only x is given. – Self Organising Maps (SOM) are neural network ...
W. Dean. Algorithms and the mathematical foundations of computer
... methods mentioned thus far are paradigmatically effective, i.e. they are finitely specifiable in terms of operations (e.g. adding or subtracting natural numbers, comparing the order of leading terms of polynomials, etc.) which may be carried out using finite resources by a mechanical computing agent ...
... methods mentioned thus far are paradigmatically effective, i.e. they are finitely specifiable in terms of operations (e.g. adding or subtracting natural numbers, comparing the order of leading terms of polynomials, etc.) which may be carried out using finite resources by a mechanical computing agent ...
Learning Low-Rank Representations with Classwise Block
... problem. Moreover, representations of training images and testing images should be consistent, which is important for the recognition process. Representations of training images and testing images should be learnt in a unified framework. For this purpose, we propose a semi-supervised framework to le ...
... problem. Moreover, representations of training images and testing images should be consistent, which is important for the recognition process. Representations of training images and testing images should be learnt in a unified framework. For this purpose, we propose a semi-supervised framework to le ...
Profiles in Innovation: Artificial Intelligence
... created by the increasingly ubiquitous connected devices, machines, and systems globally. Neural networks become more effective the more data that they have, meaning that as the amount of data increases the number of problems that machine learning can solve using that data increases. Mobile, IoT, an ...
... created by the increasingly ubiquitous connected devices, machines, and systems globally. Neural networks become more effective the more data that they have, meaning that as the amount of data increases the number of problems that machine learning can solve using that data increases. Mobile, IoT, an ...
