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14,041
PolynomialTime Algorithms for Prime Factorization and Discrete Logarithms on a Quantum Computer
 SIAM J. on Computing
, 1997
"... A digital computer is generally believed to be an efficient universal computing device; that is, it is believed able to simulate any physical computing device with an increase in computation time by at most a polynomial factor. This may not be true when quantum mechanics is taken into consideration. ..."
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Cited by 1277 (4 self)
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quantum computer. These algorithms take a number of steps polynomial in the input size, e.g., the number of digits of the integer to be factored.
Algorithms for Quantum Computation: Discrete Logarithms and Factoring
, 1994
"... A computer is generally considered to be a universal computational device; i.e., it is believed able to simulate any physical computational device with a cost in computation time of at most a polynomial factol: It is not clear whether this is still true when quantum mechanics is taken into consider ..."
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Cited by 1111 (5 self)
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of steps which is polynomial in the input size, e.g., the number of digits of the integer to be factored. These two problems are generally considered hard on a classical computer and have been used as the basis of several proposed cryptosystems. (We thus give the first examples of quantum cryptanulysis.)
RealTime Systems
, 2000
"... Collision avoidance is an important topic in multirobot systems. Existing multirobot pathfinding approaches ignore sideswipe collisions among robots (i.e., only consider the collision which two agents try to occupy the same node during the same timestep) [1, 3, 4], and allow diagonal move between ..."
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Cited by 602 (11 self)
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Collision avoidance is an important topic in multirobot systems. Existing multirobot pathfinding approaches ignore sideswipe collisions among robots (i.e., only consider the collision which two agents try to occupy the same node during the same timestep) [1, 3, 4], and allow diagonal move
Shape and motion from image streams under orthography: a factorization method
 INTERNATIONAL JOURNAL OF COMPUTER VISION
, 1992
"... Inferring scene geometry and camera motion from a stream of images is possible in principle, but is an illconditioned problem when the objects are distant with respect to their size. We have developed a factorization method that can overcome this difficulty by recovering shape and motion under orth ..."
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Cited by 1094 (38 self)
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Inferring scene geometry and camera motion from a stream of images is possible in principle, but is an illconditioned problem when the objects are distant with respect to their size. We have developed a factorization method that can overcome this difficulty by recovering shape and motion under
OPTICS: Ordering Points To Identify the Clustering Structure
, 1999
"... Cluster analysis is a primary method for database mining. It is either used as a standalone tool to get insight into the distribution of a data set, e.g. to focus further analysis and data processing, or as a preprocessing step for other algorithms operating on the detected clusters. Almost all of ..."
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Cited by 527 (51 self)
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Cluster analysis is a primary method for database mining. It is either used as a standalone tool to get insight into the distribution of a data set, e.g. to focus further analysis and data processing, or as a preprocessing step for other algorithms operating on the detected clusters. Almost all
Myrinet: A GigabitperSecond Local Area Network
 IEEE Micro
, 1995
"... Abstract. Myrinet is a new type of localarea network (LAN) based on the technology used for packet communication and switching within "massivelyparallel processors " (MPPs). Think of Myrinet as an MPP messagepassing network that can span campus dimensions, rather than as a widea ..."
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Cited by 1011 (0 self)
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area telecommunications network that is operating in close quarters. The technical steps toward making Myrinet a reality included the development of (1) robust, 25m communication channels with flow control, packet framing, and error control; (2) selfinitializing, lowlatency, cutthrough switches; (3) host interfaces
Reconsidering research on learning from media.
 Review of Educational Research,
, 1983
"... ABSTRACT. Recent metaanalyses and other studies of media influence on learning are reviewed. Consistent evidence is found for the generalization that there are no learning benefits to be gained from employing any specific medium to deliver instruction. Research showing performance or timesaving g ..."
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Cited by 462 (6 self)
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differences between treatments. With the benefit of hindsight it is not surprising that most of the studies he selected for review employed media as simple vehicles for instructional methods, such as text organization, size of step in programming, cueing, repeated exposures, and prompting. These studies
A scaled conjugate gradient algorithm for fast supervised learning
 NEURAL NETWORKS
, 1993
"... A supervised learning algorithm (Scaled Conjugate Gradient, SCG) with superlinear convergence rate is introduced. The algorithm is based upon a class of optimization techniques well known in numerical analysis as the Conjugate Gradient Methods. SCG uses second order information from the neural netwo ..."
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Cited by 451 (0 self)
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and avoids a time consuming linesearch, which CGB and BFGS uses in each iteration in order to determine an appropriate step size.
Incorporating problem dependent structural information in the architecture of a neural network often lowers the overall complexity. The smaller the complexity of the neural
Cascades of Dynamical Transitions in an Adaptive Population
, 2006
"... In an adaptive population that models financial markets and distributed control, we consider how the dynamics depends on the diversity of the agents ’ initial preferences of strategies. When the diversity decreases, more agents tend to adapt their strategies together. This change in the environment ..."
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results in dynamical transitions from vanishing to nonvanishing step sizes. When the diversity decreases further, we find a cascade of dynamical transitions for the different signal dimensions, which is supported by good agreement between simulations and theory. Besides, the signal of the largest step
Policy gradient methods for reinforcement learning with function approximation.
 In NIPS,
, 1999
"... Abstract Function approximation is essential to reinforcement learning, but the standard approach of approximating a value function and determining a policy from it has so far proven theoretically intractable. In this paper we explore an alternative approach in which the policy is explicitly repres ..."
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Cited by 439 (20 self)
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proportional to the gradient: where α is a positivedefinite step size. If the above can be achieved, then θ can usually be assured to converge to a locally optimal policy in the performance measure ρ. Unlike the valuefunction approach, here small changes in θ can cause only small changes in the policy
Results 1  10
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14,041