A Comparison between Fixed-Basis and Variable-Basis Schemes for Function Approximation and Functional Optimization [PDF]
, 2012 Fixed-basis and variable-basis approximation schemes are compared for the problems of function approximation and functional optimization (also known as infinite programming).
Gnecco, Giorgio
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Constrained Monotone Function Maximization and the Supermodular Degree [PDF]
, 2014 The problem of maximizing a constrained monotone set function has many practical applications and generalizes many combinatorial problems. Unfortunately, it is generally not possible to maximize a monotone set function up to an acceptable approximation ...
Feldman, Moran, Izsak, Rani
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Strategy-Proof Facility Location for Concave Cost Functions [PDF]
, 2013 We consider k-Facility Location games, where n strategic agents report their locations on the real line, and a mechanism maps them to k facilities.
Fotakis, Dimitris, Tzamos, Christos
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Comparing policy gradient and value function based reinforcement learning methods in simulated electrical power trade [PDF]
, 2012 In electrical power engineering, reinforcement learning algorithms can be used to model the strategies of electricity market participants. However, traditional value function based reinforcement learning algorithms suffer from convergence issues when ...
Burt, Graeme +3 more
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Pseudorehearsal in value function approximation
, 2017 Catastrophic forgetting is of special importance in reinforcement learning, as the data distribution is generally non-stationary over time. We study and compare several pseudorehearsal approaches for Q-learning with function approximation in a pole ...
A Robins +16 more
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Weak approximation over function fields
, 2004 We prove that rationally connected varieties over the function field of a complex curve satisfy weak approximation for places of good reduction.Comment: 22 ...
Artin +9 more
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Pair Fluctuations in Ultra-small Fermi Systems within Self-Consistent RPA at Finite Temperature [PDF]
, 2003 A self-consistent version of the Thermal Random Phase Approximation (TSCRPA) is developed within the Matsubara Green's Function (GF) formalism. The TSCRPA is applied to the many level pairing model. The normal phase of the system is considered.
A. Storozhenko +42 more
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Intra-Landau level polarization effect for a striped Hall gas
, 2004 We calculate the polarization function including only intra-Landau level correlation effects of striped Hall gas. Using the polarization function, the dielectric function, the dispersion of the plasmon and the correlation energy are computed in a random ...
A. L. Fetter +8 more
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Loop Calculus for Non-Binary Alphabets using Concepts from Information Geometry [PDF]
, 2014 The Bethe approximation is a well-known approximation of the partition function used in statistical physics. Recently, an equality relating the partition function and its Bethe approximation was obtained for graphical models with binary variables by ...
Mori, Ryuhei
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Shrinkage Function And Its Applications In Matrix Approximation
, 2017 The shrinkage function is widely used in matrix low-rank approximation, compressive sensing, and statistical estimation. In this article, an elementary derivation of the shrinkage function is given. In addition, applications of the shrinkage function are
Boas, Toby +4 more
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