In this paper, we present a discriminative word-character hybrid model for joint Chinese word segmentation and POS tagging. Our word-character hybrid model offers high performance since it can handle both known and unknown words. We describe our strategies that yield good balance for learning the characteristics of known and unknown words and propose an errordriven policy that delivers such bal...

We give an overview of the Theory of Relaxed Unification—a novel theory that extends the classical Theory of Unification. Classical unification requires a perfect agreement between the terms being unified. In practice, data is seldom error-free and can contain inconsistent information. Classical unification fails when the data is imperfect. We propose the Theory of Relaxed Unification as a new ...

For pension-savers, a low payoff is a financial disaster. Such investors will most likely prefer left-skewed payoff distributions over right-skewed payoff distributions. We explore how such distributions can be delivered. Cautious-relaxed utility measures are cautious in ensuring that payoffs don’t fall much below a reference value, but relaxed about exceeding it. We find that the payoff distri...

We consider an optimal control problem described by a second order elliptic boundary value problem, jointly nonlinear in the state and control with high monotone nonlinearity in the state, with control and state constraints, where the state constraints and cost functional involve also the state gradient. Since no convexity assumptions are made, the problem may have no classical solutions, and s...

This paper presents a newmodel of support vector machines (SVMs) that handle data with tolerance and uncertainty. The constraints of the SVM are converted to fuzzy inequality. Giving more relaxation to the constraints allows us to consider an importance degree for each training samples in the constraints of the SVM. The new method is called relaxed constraints support vector machines (RSVMs). A...

In previous work, we have introduced the technique of relaxed power series computations. With this technique, it is possible to solve implicit equations almost as quickly as doing the operations which occur in the implicit equation. Here almost as quickly means that we need to pay a logarithmic overhead. In this paper, we will show how to reduce this logarithmic factor in the case when the cons...

Relaxed balancing means that, in a dictionary stored as a balanced tree, the necessary rebalancing after updates may be delayed. This is in contrast to strict balancing meaning that rebalancing is performed immediately after the update. Relaxed balancing is important for efficiency in highly dynamic applications where updates can occur in bursts. The rebalancing tasks can be performed gradually...