Academic literature on the topic 'Estimateurs explicites'

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Journal articles on the topic "Estimateurs explicites"

1

Ramaré, Olivier. "From explicit estimates for primes to explicit estimates for the Möbius function." Acta Arithmetica 157, no. 4 (2013): 365–79. http://dx.doi.org/10.4064/aa157-4-4.

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2

Piau, Didier. "Quasi-renewal estimates." Journal of Applied Probability 37, no. 1 (2000): 269–75. http://dx.doi.org/10.1239/jap/1014842284.

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We show that the solution of a quasi-renewal equation with an exponential distribution of the renewals converges at infinity and we compute explicitly the limit, hence generalizing the classical renewal theorem. We apply this result to a stochastic model of DNA replication introduced by Cowan and Chiu (1994).
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3

Piau, Didier. "Quasi-renewal estimates." Journal of Applied Probability 37, no. 01 (2000): 269–75. http://dx.doi.org/10.1017/s0021900200015412.

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We show that the solution of a quasi-renewal equation with an exponential distribution of the renewals converges at infinity and we compute explicitly the limit, hence generalizing the classical renewal theorem. We apply this result to a stochastic model of DNA replication introduced by Cowan and Chiu (1994).
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4

Sanghvi, Navyata, Shinnosuke Usami, Mohit Sharma, Joachim Groeger, and Kris Kitani. "Inverse Reinforcement Learning with Explicit Policy Estimates." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 11 (2021): 9472–80. http://dx.doi.org/10.1609/aaai.v35i11.17141.

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Various methods for solving the inverse reinforcement learning (IRL) problem have been developed independently in machine learning and economics. In particular, the method of Maximum Causal Entropy IRL is based on the perspective of entropy maximization, while related advances in the field of economics instead assume the existence of unobserved action shocks to explain expert behavior (Nested Fixed Point Algorithm, Conditional Choice Probability method, Nested Pseudo-Likelihood Algorithm). In this work, we make previously unknown connections between these related methods from both fields. We achieve this by showing that they all belong to a class of optimization problems, characterized by a common form of the objective, the associated policy and the objective gradient. We demonstrate key computational and algorithmic differences which arise between the methods due to an approximation of the optimal soft value function, and describe how this leads to more efficient algorithms. Using insights which emerge from our study of this class of optimization problems, we identify various problem scenarios and investigate each method's suitability for these problems.
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5

Romero, José Luis. "Explicit Localization Estimates for Spline-Type Spaces." Sampling Theory in Signal and Image Processing 8, no. 3 (2009): 249–59. http://dx.doi.org/10.1007/bf03549518.

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6

C, Gallesco, Gallo S, and Takahashi D. Y. "Explicit estimates in the Bramson–Kalikow model." Nonlinearity 27, no. 9 (2014): 2281–96. http://dx.doi.org/10.1088/0951-7715/27/9/2281.

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7

Cheng, Yuanyou F., and Sidney W. Graham. "Explicit Estimates for the Riemann Zeta Function." Rocky Mountain Journal of Mathematics 34, no. 4 (2004): 1261–80. http://dx.doi.org/10.1216/rmjm/1181069799.

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8

Dusart, Pierre. "Explicit estimates of some functions over primes." Ramanujan Journal 45, no. 1 (2016): 227–51. http://dx.doi.org/10.1007/s11139-016-9839-4.

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9

Juricevic, Robert. "Explicit estimates of solutions of some Diophantine equations." Functiones et Approximatio Commentarii Mathematici 38, no. 2 (2008): 171–94. http://dx.doi.org/10.7169/facm/1229696538.

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10

Consiglieri, Luisa. "Explicit Estimates for Solutions of Mixed Elliptic Problems." International Journal of Partial Differential Equations 2014 (March 31, 2014): 1–16. http://dx.doi.org/10.1155/2014/845760.

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We deal with the existence of quantitative estimates for solutions of mixed problems to an elliptic second-order equation in divergence form with discontinuous coefficients. Our concern is to estimate the solutions with explicit constants, for domains in ℝn (n≥2) of class C0,1. The existence of L∞ and W1,q estimates is assured for q=2 and any q<n/(n-1) (depending on the data), whenever the coefficient is only measurable and bounded. The proof method of the quantitative L∞ estimates is based on the De Giorgi technique developed by Stampacchia. By using the potential theory, we derive W1,p estimates for different ranges of the exponent p depending on the fact that the coefficient is either Dini-continuous or only measurable and bounded. In this process, we establish new existences of Green functions on such domains. The last but not least concern is to unify (whenever possible) the proofs of the estimates to the extreme Dirichlet and Neumann cases of the mixed problem.
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