OCP optimization results for iteration 1 and iteration 6
2th iteration th iteration
... Summarizing, the original AdaBoost algorithm is useful for low noise cases, where the classes are easily separable (as shown for OCR cf. Schwenk & Bengio, 1997; Le- Cun et al., 1995). L/QP Reg -AdaBoost can improve the ...
Higher Order Iteration Schemes for Unconstrained Optimization
... Received August 3, 2011; revised August 20, 2011; accepted September 19, 2011 Abstract Using a predictor-corrector tactic, this paper derives new iteration schemes for unconstrained optimization. It yields ...
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Pipeline Iteration
... the results of performing this com- bined precision/recall optimization on three separate n-best lists: the 50-best list of base-phrase trees ex- tracted from the full-parse output of the Charniak and ...
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Low-Order Optimization Algorithms: Iteration Complexity and Applications
... of optimization method, Bayesian optimization [63] also provides a powerful tool for black-box ...Bayesian optimization constructs a prior probabilistic distribution over the functional ...Bayesian ...
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Iteration Complexity of Feasible Descent Methods for Convex Optimization
... Although this work focuses on deterministic algorithms, we briefly review past studies on stochastic (randomized) methods. An interesting fact is that there are more studies on the complexity of randomized rather than ...
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The equivalence of Mann iteration and Ishikawa iteration for non Lipschitzian operators
... The existence of the solution for Sx = f when S is a continuous and strongly accretive operator results from [8]. This argument and Remark 2.2(ii) lead us to the following corollary. Corollary 3.1. Let X be a real ...
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On policy iteration as a Newton’s method and polynomial policy iteration algorithms
... Fig. 1 shows the MDP problems in ...Our results apply to the enclosed prob- ...Each iteration takes O(m) time or O(m + n 2 ) time depend- ing on the edges (Section ...
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Value-Iteration Based Fitted Policy Iteration: Learning with a Single Trajectory
... presented results for sample- based approximate value iteration where a generative model of the MDP was assumed to be available, in this paper we dealt with the significantly more complicated problem of ...
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Value-iteration based fitted policy iteration: learning with a single trajectory
... presented results for sample- based approximate value iteration where a generative model of the MDP was assumed to be available, in this paper we dealt with the significantly more complicated problem of ...
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Iteration in Asynchronous System
... that the algorithm is asynchronous if these times can vary widely in two different executions of the algorithm with an attendant effect on the results of the computation [4]. The most extreme type of asynchronous ...
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Stable Iteration Procedures in Metric Spaces which Generalize a Picard-Type Iteration
... of iteration procedures defined by continuous functions acting on self-maps in continuous metric ...obtained results extend the contraction principle to the use of altering-distance functions and extended ...
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Adventures in applying iteration lemmas
... and results and define automata that take inputs over an arbitrary monoid M, but that making that exposition explicit would be “an exercise that is not very produc- ...
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Iteration functions re visited
... All of the formulae have been checked using Mathematica, version 10. The Mat- lab code and the Mathematica code can be provided by the authors on request. The software was tested intensively on a database of 215 ...
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Computing a eigenvector with inverse iteration
... main results and to set out his ...inverse iteration from nite precision ...inverse iteration is presented for the computation of a complete set of eigenvectors of a real, symmetric ...
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The embedding problem in iteration theory
... Iteration groups (5), (7) and (9), where the functions ϕ, ψ and γ are given respectively by the formulas (6), (8) and (10) are said to be the principal iteration groups of f . Several authors ...
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An inertial S-iteration process
... various iteration schemes for several classes of nonexpansive mappings to solve some mathematical problems such as convex optimization problems, convex feasibility problems, and variational inequalities ...
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Policy Iteration for Factored MDPs
... ral structural parameters of the MDP and the value functions. When approximately solving an MDP, it is impor tant to evaluate how far our proposed solution is from the optimal. There are known results that allow ...
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Approximate Modified Policy Iteration
... policy iteration (MPI), that despite its generality that contains the celebrated policy and value itera- tion methods, has not been thoroughly investigated in the ...fitted-value iteration, fitted- Q ...
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Least-Squares Policy Iteration
... the results of LSTDQ to form an approximate policy-iteration ...policy iteration with the data efficiency of ...each iteration of LSPI to evaluate the generated ...policy iteration and ...
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Algorithmic iteration for computational intelligence
... In the formal logic literature, self-knowledge is usually identified as knowledge about beliefs, intentions and desires. Formalization of self-knowledge in first-order logic is known to lead to trivialising ...
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