We introduce a greedy local search procedure called GSAT for solving propositional satisfiability problems. Our experiments show that this procedure can be used to solve hard, randomly generated problems that are an order of magnitude larger than those that can be handled by more traditional

) which simply linearises all nonlinear models so that the traditional linear Kalman filter can be applied. Although the EKF (in its many forms) is a widely used filtering strategy, over thirty years of experience with it has led to a general consensus within the tracking and control community

are characteristic of normal human thought. Moreover, these illusions appear to promote other criteria of mental health, including the ability to care about others, the ability to be happy or contented, and the ability to engage in productive and creative work. These strategies may succeed, in large part, because

-ordering heuristic, the min-conflicts heuristic, that attempts to minimize the number of constraint violations after each step. The heuristic can be used with a variety of different search strategies. We demonstrate empirically that on the n-queens problem, a technique based on this approach performs orders

The traditional SPM approach based on bag-of-features (BoF) requires nonlinear classifiers to achieve good image classification performance. This paper presents a simple but effective coding scheme called Locality-constrained Linear Coding (LLC) in place of the VQ coding in traditional SPM. LLC

circumstances of risk and uncertainty. It is also a tool vital to forming corporate strategies needed for effective competition. Nearly all of us, in one way or another, have been brought up to believe that clearheaded logical thinking is our only sure way to face and solve problems. We also believe that our

New developments in the world economy have triggered research designed to better understand the changes in trade and investment patterns, and the reorganization of production across national borders. Although traditional trade theory has much to offer in explaining parts of this puzzle, other parts

-labeling strategies of increasing complexity, and show several main results. (i) Repeated-labeling can improve label quality and model quality, but not always. (ii) When labels are noisy, repeated labeling can be preferable to single labeling even in the traditional setting where labels are not particularly cheap

utilizing MS and a host of stable isotope-labeling chemistries have emerged (reviewed in Refs. 1 and 2), offering a departure from traditional techniques employing comparative two-dimensional gel electrophoresis. The ICAT quantitative labeling strategy (3, 4) is perhaps the best-characterized method

rates and the market risk premium. RECENT EMPIRICAL RESEARCH IN FINANCE has focused on regularities in the cross section of expected returns that appear anomalous relative to traditional models. Stock returns are related to book-to-market, and market value. 1 Past returns have also been shown to predict