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Greedy Function Approximation: A Gradient Boosting Machine
 Annals of Statistics
, 2000
"... Function approximation is viewed from the perspective of numerical optimization in function space, rather than parameter space. A connection is made between stagewise additive expansions and steepest{descent minimization. A general gradient{descent \boosting" paradigm is developed for additi ..."
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Cited by 1000 (13 self)
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Function approximation is viewed from the perspective of numerical optimization in function space, rather than parameter space. A connection is made between stagewise additive expansions and steepest{descent minimization. A general gradient{descent \boosting" paradigm is developed
Energy Conserving Routing in Wireless Adhoc Networks
, 2000
"... An adhoc network of wireless static nodes is considered as it arises in a rapidly deployed, sensor based, monitoring system. Information is generated in certain nodes and needs to reach a set of designated gateway nodes. Each node may adjust its power within a certain range that determines the set ..."
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Cited by 622 (2 self)
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with node capacities and the algorithms converge to the optimal solution. When there are multiple power levels then the achievable lifetime is close to the optimal (that is computed by linear programming) most of the time. It turns out that in order to maximize the lifetime, the traffic should be routed
ABSOLUTELY OPTIMAL CONFIGURATIONS WITH MAXIMUM LIFTTODRAG RATIO AT HIGH SUPERSONIC
"... Abstract. The problem on the configuration with maximum lifttodrag ratio in supersonic gas flow is discussed. It is assumed that pressure on the body surface is defined by a local method and friction coefficient is constant. Corresponding variational problem is stated and solved without isoperimet ..."
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to Zaxis that form the windward surface of the optimal body. If isoperimetric conditions are not prescribed, absolutely optimal body is twodimensional wedge. If base area is given then optimal body base shape is a polygon formed by line segments. Optimal parameters are found for bodies
Autocalibration and the absolute quadric
 in Proc. IEEE Conf. Computer Vision, Pattern Recognition
, 1997
"... We describe a new method for camera autocalibration and scaled Euclidean structure and motion, from three or more views taken by a moving camera with fixed but unknown intrinsic parameters. The motion constancy of these is used to rectify an initial projective reconstruction. Euclidean scene structu ..."
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Cited by 248 (7 self)
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structure is formulated in terms of the absolute quadric — the singular dual 3D quadric ( rank 3 matrix) giving the Euclidean dotproduct between plane normals. This is equivalent to the traditional absolute conic but simpler to use. It encodes both affine and Euclidean structure, and projects very simply
Sparse Reconstruction by Separable Approximation
, 2007
"... Finding sparse approximate solutions to large underdetermined linear systems of equations is a common problem in signal/image processing and statistics. Basis pursuit, the least absolute shrinkage and selection operator (LASSO), waveletbased deconvolution and reconstruction, and compressed sensing ..."
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Cited by 373 (38 self)
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Finding sparse approximate solutions to large underdetermined linear systems of equations is a common problem in signal/image processing and statistics. Basis pursuit, the least absolute shrinkage and selection operator (LASSO), waveletbased deconvolution and reconstruction, and compressed sensing
Mean absolute deviation portfolio optimization model and its application to Tokyo Stock Market
 Management Science
, 1991
"... Abstract We will propose a branch and bound algorithm for solving, a portfolio optimization model under nonconvex transaction costs. It is well known that the unit transaction cost is larger when the amount of transaction is small while it remains stable up to a certain point and then increases due ..."
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Cited by 191 (2 self)
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aside due to its computational difficulty. In fact, there are only a few studies which treated nonconvex costs in a rigorous manner. In this paper, we will propose a branch and bound algorithm for solving a meanabsolute deviation portfolio optimization model assuming that the cost function is concave
ContextDependent Pretrained Deep Neural Networks for Large Vocabulary Speech Recognition
 IEEE TRANSACTIONS ON AUDIO, SPEECH, AND LANGUAGE PROCESSING
, 2012
"... We propose a novel contextdependent (CD) model for large vocabulary speech recognition (LVSR) that leverages recent advances in using deep belief networks for phone recognition. We describe a pretrained deep neural network hidden Markov model (DNNHMM) hybrid architecture that trains the DNN to pr ..."
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Cited by 254 (50 self)
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to produce a distribution over senones (tied triphone states) as its output. The deep belief network pretraining algorithm is a robust and often helpful way to initialize deep neural networks generatively that can aid in optimization and reduce generalization error. We illustrate the key components of our
An asymptotically optimal multiversion Btree
, 1996
"... In a variety of applications, we need to keep track of the development of a data set over time. For maintaining and querying these multiversion data efficiently, external storage structures are an absolute necessity. We propose a multiversion Btree that supports insertions and deletions of data ite ..."
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Cited by 184 (9 self)
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In a variety of applications, we need to keep track of the development of a data set over time. For maintaining and querying these multiversion data efficiently, external storage structures are an absolute necessity. We propose a multiversion Btree that supports insertions and deletions of data
Query Optimization
, 1996
"... Imagine yourself standing in front of an exquisite buffet filled with numerous delicacies. Your goal is to try them all out, but you need to decide in what order. What exchange of tastes will maximize the overall pleasure of your palate? Although much less pleasurable and subjective, that is the typ ..."
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Cited by 147 (5 self)
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that they need to run. What is the plan that needs the least amount of time? Such query optimization is absolutely necessary in a DBMS. The cost difference between two alternatives can be enormous. For example, consider the following database schema, which will be...
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