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This paper is concerned with a continuous-time mean-variance portfolio selection model that is formulated as a bicriteria optimization problem. The objective is to maximize the expected terminal return and minimize the variance of the terminal wealth. By putting weights on the two criteria one obtains a single objective stochastic control problem which is however not in the standard form due to...

A fundamental theory of deterministic linear-quadratic (LQ) control is the equivalent relationship between problems, two-point boundary value and Riccati equations. In this paper, we extend equivalence to a general time-inconsistent LQ problem, where inconsistency arises from nonexponential discount functions. By studying solvability equation, show existence uniqueness linear equilibrium for pr...

Quantified Boolean formula (QBF) evaluation has a broad range of applications in computer science and is gaining increasing attention. Recent progress has shown that for a certain family of formulas, Qresolution, which forms the foundation of learning in modern search-based QBF solvers, is exponentially inferior in proof size to two of its extensions: Q-resolution with resolution over universal...

The pseudo-dimension of a real-valued function class is an extension of the VC dimension for set-indicator function classes. A classH of finite pseudo-dimension possesses a useful statistical smoothness property. In [10] we introduced a nonlinear approximation width ρn(F , Lq ) = infHn dist(F ,Hn, Lq ) which measures the worstcase approximation error over all functions f ∈ F by the best manifol...

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This paper describes lq-text, an inverted index text retrieval package written by the author. Inverted index text retrieval provides a fast and effective way of searching large amounts of text. This is implemented by making an index to all of the natural-language words that occur in the text. The actual text remains unaltered in place, or, if desired, can be compressed or archived; the index al...

We introduce a maximum Lq-likelihood estimation (MLqE) of mixture models using our proposed expectation maximization (EM) algorithm, namely the EM algorithm with Lq-likelihood (EM-Lq). Properties of the MLqE obtained from the proposed EMLq are studied through simulated mixture model data. Compared with the maximum likelihood estimation (MLE) which is obtained from the EM algorithm, the MLqE pro...