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91.
92.
k-best MIRA和动态k-best MIRA 总被引:1,自引:0,他引:1
MIRA(Margin Infused Relaxed Algorithm)是一种超保守算法,在分类、排序、回归等应用领域都取得不错成绩.文中在传统MIRA算法基础上进行改进,提出k-best MIRA(K-MIRA)与动态k-best MIRA(DK-MIRA)算法.这两种算法能够根据学习进程自动调整优化约束条件,从而提高算法的收敛速度与性能.将K-MIRA与DK-MIRA用于定义类问题回答中的句子排序任务,取得较为满意的实验结果. 相似文献
93.
94.
基于量子粒子群优化的在线航迹规划 总被引:1,自引:0,他引:1
现代战场中,环境信息是变化的,飞行器很难预先获得精确的全局环境信息,因此要求无人飞行器具有实时的航迹规划能力,采用量子粒子群优化算法,将约束条件和搜索算法相结合,有效解决了简单粒子群算法在高维空间中易陷入局部最优点的问题;同时,根据地形障碍、敌方防御雷达、防空火力等威胁以及禁飞区的分布情况,引入最小威胁面的概念,利用B-Spline插值逼近最小威胁面中的三维航迹在二维水平面内的投影,从而将三维曲线的规划问题简化为二维平面中控制点的寻优问题,简化了问题复杂度,提高了计算效率.仿真结果表明该方法可以满足在线航迹规划的要求. 相似文献
95.
网上银行支持在网络上进行交易的虚拟银行。只要能够上网,无论身在何处,都能够安全便捷地管理自己的资产和享受银行提供的服务。然而网上银行存在诸多的安全问题。本文就针对这些安全问题提出相应的解决办法。 相似文献
96.
This paper investigates an online gradient method with penalty for training feedforward neural networks with linear output.
A usual penalty is considered, which is a term proportional to the norm of the weights. The main contribution of this paper
is to theoretically prove the boundedness of the weights in the network training process. This boundedness is then used to
prove an almost sure convergence of the algorithm to the zero set of the gradient of the error function. 相似文献
97.
This work considers non-terminating scheduling problems in which a system of multiple resources serves clients having variable
needs. The system has m identical resources and n clients; in each time slot each resource may serve at most one client; in each such slot t each client γ has a rate, a real number ρ
γ
(t), that specifies his needs in this slot. The rates satisfy the restriction ∑
γ
ρ
γ
(t)≤m for any slot t. Except of this restriction, the rates can vary in arbitrary fashion. (This contrasts most prior works in this area in which
the rates of the clients are constant.) The schedule is required to be smooth as follows: a schedule is Δ
-smooth if for all time intervals I the absolute difference between the amount of service received by each client γ to his nominal needs of ∑
t∈I
ρ
γ
(t) is less than Δ. Our objective are online schedulers that produce Δ-smooth schedules where Δ is a small constant which is independent of m and n. Our paper constructs such schedulers; these are the first online Δ-smooth schedulers, with a constant Δ, for clients with arbitrarily variable rates in a single or multiple resource system. Furthermore, the paper also considers
a non-concurrent environment in which there is an additional restriction that each client is served at most once in each time slot; it presents
the first online smooth schedulers for variable rates under this restriction.
The above non-concurrent restriction is crucial in some applications (e.g., CPU scheduling). It has been pointed out that
this restriction “adds a surprising amount of difficulty” to the scheduling problem. However, this observation was never formalized
and, of course, was never proved. Our paper formalizes and proves some aspects of this observation.
Another contribution of this paper is the introduction of a complete information, two player game called the analog-digital confinement game. In such a game pebbles are located on the real line; the two players, the analog player and the digital player, take alternating turns and each one, in his turn, moves some of the pebbles; the digital player moves the pebbles backwards
by discrete distances while the analog player moves the pebbles forward by analog distances; the aim of the analog player
is to cause one pebble (or more) to escape a pre-defined real interval while the aim of the digital player is to confine the
pebbles into the interval. We demonstrate that this game is a convenient framework to study the general question of how to
approximate an analog process by a digital one. All the above scheduling results are established via this game. In this derivation,
the pebbles represent the clients, the analog player generates the needs of the clients and the digital player generates the
schedule.
Dedicated to the memory of Professor Shimon Even for his inspiration and encouragement 相似文献
98.
A Randomized Algorithm for Online Unit Clustering 总被引:1,自引:0,他引:1
In this paper, we consider the online version of the following problem: partition a set of input points into subsets, each enclosable by a unit ball, so as to minimize the number of subsets used. In the one-dimensional case, we show that surprisingly the naïve upper bound of 2 on the competitive ratio can be beaten: we present a new randomized 15/8-competitive online algorithm. We also provide some lower bounds and an extension to higher dimensions. 相似文献
99.
100.