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15th Conference of the Spanish-Association-for-Artificial-Intelligence (CAEPIA)

作者： Cabanas, Rafael Cano, Andres Gomez-Olmedo, Manuel Madsen, Anders L. Univ Granada CITIC Dept Comp Sci & Artificial Intelligence E-18071 Granada Spain HUGIN EXPERT Aalborg Denmark Aalborg Univ Dept Comp Sci Aalborg Denmark

ISBN: (纸本)9783642406423;9783642406430

Influence Diagrams are a tool used to represent and solve decision problems under uncertainty. One of the most efficient exact methods used to evaluate Influence Diagrams is Lazy Evaluation. This paper proposes the use of trees for representing potentials involved in an Influence Diagram in order to obtain an approximate Lazy Evaluation of decision problems. This method will allow to evaluate complex decision problems that are not evaluable with exact methods due to their computational cost. The experimental work compares the efficiency and goodness of the approximate solutions obtained using different kind of trees.

关键词： Influence Diagram Approximate computation Lazy Evaluation deterministic algorithms Context-specific independencies

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Separations in Query Complexity Based on Pointer Functions 16

Separations in Query Complexity Based on Pointer Functions

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48th Annual ACM SIGACT Symposium on Theory of Computing (STOC)

作者： Ambainis, Andris Balodis, Kaspars Belovs, Aleksandrs Lee, Troy Santha, Miklos Smotrovs, Juris Univ Latvia Fac Comp Riga Latvia Univ Latvia IMCS Riga Latvia CWI Amsterdam Netherlands Nanyang Technol Univ SPMS Singapore Singapore NUS CQT Singapore Singapore NUS MajuLab Singapore Singapore CNRS IRIF Paris France

ISBN: (纸本)9781450341325

In 1986, Saks and Wigderson conjectured that the largest separation between deterministic and zero-error randomized query complexity for a total boolean function is given by the function f on n = 2(k) bits defined by a complete binary tree of NAND gates of depth k, which achieves R-0(f) = O(D(f)(0.7537...)). We show this is false by giving an example of a total boolean function f on n bits whose deterministic query complexity is Omega(n/log(n)) while its zero-error randomized query complexity is (O) over tilde(root n). We further show that the quantum query complexity of the same function is (O) over tilde (n(1/4)), giving the first example of a total function with a super-quadratic gap between its quantum and deterministic query complexities. We also construct a total boolean function g on n variables that has zero-error randomized query complexity Omega(n/log(n)) and bounded-error randomized query complexity R(g) = (O) over tilde(root n). This is the first super-linear separation between these two complexity measures. The exact quantum query complexity of the same function is Q(E)(g) = (O) over tilde(root n). These functions show that the relations D(f) = O(R-1(f)(2)) and R-0(f) = (O) over tilde (R(f)(2)) are optimal, up to poly-logarithmic factors. Further variations of these functions give additional separations between other query complexity measures: a cubic separation between Q and R-0, a 3/2-power separation between Q(E) and R, and a 4th power separation between approximate degree and bounded-error randomized query complexity. All of these examples are variants of a function recently introduced by Goos, Pitassi, and Watson which they used to separate the unambiguous 1-certificate complexity from deterministic query complexity and to resolve the famous Clique versus Independent Set problem in communication complexity.

关键词： deterministic algorithms Randomized algorithms Quantum algorithms Monte Carlo Las Vegas

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Feature selection in deterministic policy gradient

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JOURNAL OF ENGINEERING-JOE 2020年第13期2020卷 403-406页

作者： Li, Luntong Li, Dazi Song, Tianheng Beijing Univ Chem Technol Inst Automat Beijing 100029 Peoples R China

The authors consider the task of learning control problem in reinforcement learning (RL) with continuous action space. Policy gradient, and in particular the determinist policy gradient (DPG) algorithm, provides a method for solving learning control problem with continuous action space. However, when the RL task is complex enough so that tuning of the function approximation is necessary, hand-tuning for the features is infeasible. In order to solve this problem, the authors extend DPG algorithm by adding an approximate-linear-dependency-based sparsification procedure, which makes DPG algorithm to automatically select the useful and sparse features. As far as the authors know, this is the first time to consider the feature selection problem in DPG. Simulation results illustrate that (i) the proposed algorithm can find the optimal solution of the continuous version of mountain car problem;(ii) the proposed algorithm achieves good performance over a large range of the approximate linear dependency threshold parameter settings.

关键词： learning (artificial intelligence) function approximation learning systems feature selection deterministic algorithms continuous action space learning control problem RL task function approximation hand-tuning DPG algorithm approximate-linear-dependency-based sparsification procedure useful features sparse features feature selection problem mountain car problem approximate linear dependency threshold parameter settings deterministic policy gradient reinforcement learning determinist policy gradient algorithm

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Evolution with size in a locally periodic system: scattering and deterministic maps

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JOURNAL OF PHYSICS A-MATHEMATICAL AND THEORETICAL 2013年第23期46卷 235101-235101页

作者： Dominguez-Rocha, V. Martinez-Mares, M. Univ Autonoma Metropolitana Iztapalapa Dept Fis Mexico City 09340 DF Mexico

In this paper, we study the evolution of the wavefunction with the system size in a locally periodic structure. In particular, we analyse the dependence of the wavefunction with the number of unit cells, which also reflects information about its spatial behaviour in the system. We reduce the problem to a nonlinear map and find an equivalence of its energy regions of single periodicity and weak chaos, with the forbidden and allowed bands of the fully periodic system, respectively. At finite size the wavefunction decays exponentially with the system size, as well as in space, when the energy lies inside a region of single periodicity, while for energies in the weak chaotic region it never decays. At the transition between those regions the wavefunction still decays but in a q-exponential form;we find that the decay length is a half of the mean free path, which is larger than the lattice constant.

关键词： SCATTERING (Mathematics) deterministic algorithms UNIT cell LATTICE constants CYCLES

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Two-Source Extractors for Leaky Sources

Two-Source Extractors for Leaky Sources

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IEEE Information Theory Workshop (ITW)

作者： Yu, Yu Li, Xiangxue Qian, Haifeng East China Normal Univ Dept Comp Sci & Technol Shanghai 200062 Peoples R China Tsinghua Univ Inst Interdisciplinary Informat Sci Beijing 100084 Peoples R China

ISBN: (纸本)9781467302234;9781467302241

A (worst-case) 2-source extractor is a deterministic algorithm that transforms pairwise independent weak random sources into almost uniform random strings. Despite non-constructive proofs that such objects exist with almost optimal parameters, it has been a longstanding open problem to construct 'explicit' (aka efficient) functions for sources of 'small' constant entropy rate. In particular, best known constructions either require entropy rate of at least 0.4999 (due to Bourgain), or one source must remain with constant entropy rate above half (due to Raz). Motivated by cryptographic applications, we observe that if one source is a leaky source (or it contains a few deterministically extractable entropy), then we will be able to efficiently extract almost all entropy from both sources with nearly optimal entropy loss. Further, our extractor (for leaky sources) does not suffer from the half entropy rate barrier, and it works for all linear (and even sub-linear) entropy sources. The extractor is constructed using the technique of alternating extraction by Dziembowski and Pietrzak (FOCS 2007). Finally, we show that the extractor is almost a worse-case extractor (for the same parameters) in the sense that it only fails for a negligible fraction of sources.

关键词： extraction device entropy deterministic algorithms optimal parameter Transform

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Generation of Diverse Paths in 3D Environments

Generation of Diverse Paths in 3D Environments

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Quispe, Ana Huaman Kunz, Tobias Stilman, Mike Georgia Inst Technol Ctr Robot & Intelligent Machines Atlanta GA 30332 USA

ISBN: (纸本)9781467363587

In this paper we propose a deterministic algorithm to produce a set of diverse paths between a given start and goal configuration in 3D environments. These diverse paths have the following properties: 1) They are bounded in length and 2) They are non-visibility-deformable into one another. Maintaining multiple path alternatives is important in practical applications such as planning in dynamic environments, in which a path may unexpectedly become infeasible due to unforeseen environmental changes. We present our approach, the distance cost considered ( based on the path deformability concept previously introduced in [11]) and finally show results of simulated experiments that exemplify the effectiveness of our algorithm.

关键词： deterministic algorithms path planning robots

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Peeling Algorithm for Custom Instruction Identification

Peeling Algorithm for Custom Instruction Identification

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IEEE Asia Pacific Conference on Circuit and System (APCCAS)

作者： Zhao, Kang Bian, Jinian Tsinghua Univ EDA Lab Dept Comp Sci & Technol Beijing 100084 Peoples R China

ISBN: (纸本)9781424474561

To speedup the custom instruction identification for the application specific instruction-set processor (ASIP), this paper proposes a peeling algorithm. It starts with the maximal valid pattern, and then gets a set of valid sub-patterns through deleting the source and sink respectively. Furthermore, a local priority is proposed for the exhaustive pruning. The final experiment indicates a distinct speedup compared to the fastest deterministic algorithm.

关键词： instruction Customs Customization Speeding deterministic algorithms algorithms Valid

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Optimal Monte Carlo algorithms

Optimal Monte Carlo algorithms

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IEEE John Vincent Atanasoff International Symposium on Modern Computing

作者： Dimov, Ivan T. Bulgarian Acad Sci Dept Parallel Algorithms Inst Parallel Proc Sofia 1113 Bulgaria

ISBN: (纸本)0769526438

The question "what Monte Carlo can do and cannot do efficiently " is discussed for some functional spaces that define the regularity of the input data. Important for practical computations data classes are considered: classes of functions with bounded derivatives and Holder type conditions. Theoretical performance analysis of some algorithms with unimprovable rate of convergence is given. Estimates of complexity of two classes of algorithms - deterministic and randomized for the solution of a class of integral equations are presented.

关键词： Monte Carlo algorithms deterministic algorithms integral equations unimprovable rate of convergence

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Fast variable selection for gas sensing applications

Fast variable selection for gas sensing applications

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Electronics, Robotics and Automotive Mechanics Conference

作者： Gualdron, O. Torres, I. Departamento de Ingeniería Electrónica Universidad de Pamplona Km 1 via Bucaramanga Colombia

ISBN: (纸本)9780769529745

We introduce a new variable selection approach, which converges much faster to the optimal set of variables for a given application. The new procedure runs in two steps. First, a coarse and very fast variable selection procedure, is applied: A figure of merit is defined and computed for every variable, a threshold value set and only the variables whose figure of merit is higher than the threshold are retained for further selection. Then, a fine-tuning selection based either on deterministic or stochastic methods is conducted on the variable subset that resulted from the first step. The method is demonstrated using a database consisting of vapors of acetone, ammonia and o-xylene and their binary mixtures (120 variables/measurement). Vapors can be simultaneously identified and quantified with a 92.7% success rate and the time needed for variable selection is reduced at least by a factor of 4

关键词： deterministic algorithms gas sensors sensor fusion stochastic processes deterministic method fine-tuning selection gas sensing application stochastic method threshold value set vapor database variable selection variable subset Input variables deterministic algorithms deterministic approach Sensor fusion Markov chain Gas sensors remote sensing application Stochastic Processes

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Methods for Large Scale Hydraulic Fracture Monitoring

Methods for Large Scale Hydraulic Fracture Monitoring

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5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)

作者： Ely, Gregory Aeron, Shuchin Tufts Univ Dept ECE Medford MA 02155 USA

ISBN: (纸本)9781467331463;9781467331449

In this paper we propose computationally efficient and robust methods for estimating the moment tensor and location of microseismic event(s) for large search volumes. Our contribution is two-fold. First, we propose a novel joint-complexity measure, namely the sum of nuclear norms which while imposing sparsity on the number of fractures (locations) over a large spatial volume, also captures the rank-1 nature of the induced wavefield pattern. This wavefield pattern is modeled as the outer-product of the source signature with the amplitude pattern across the receivers from a seismic source. A rank-1 factorization of the estimated wavefield pattern at each location can therefore be used to estimate the seismic moment tensor using the knowledge of the array geometry. In contrast to existing work this approach allows us to drop any other assumption on the source signature. Second, we exploit the recently proposed first-order incremental projection algorithms for a fast and efficient implementation of the resulting optimization problem and develop a hybrid stochastic & deterministic algorithm which results in significant computational savings.

关键词： moment tensors Hydraulic Fracking Projection algorithms Earthquakes Tensor Receivers deterministic algorithms

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