Constraint satisfaction inference is presented as a generic, theory-neutral inference engine for machine translation. The approach enables the integration of many different solutions to aspects of the output space, including classification-based translation models that take source-side context into account, as well as stochastic components such as target language models. The approach is contras...

We present a novel Undirected Machine Translation model of Hierarchical MT that is not constrained to the standard bottomup inference order. Removing the ordering constraint makes it possible to condition on top-down structure and surrounding context. This allows the introduction of a new class of contextual features that are not constrained to condition only on the bottom-up context. The model...

We propose an unsupervised word segmentation model, in which for each unlabelled sentence sample, the learning objective is to maximize generation probability of given its all possible segmentations. Such a can be factorized into likelihood segment context recursive way. To capture both long- and short-term dependencies, we use bi-directional neural language model better extract features segmen...

Using methods originating in numerical analysis, we will develop a uni ed framework for derivation of eÆcient algorithms for decoding several classes of algebraic codes. We will demonstrate our method by accelerating Sudan's list decoding algorithm for Reed-Solomon codes [22], its generalization to algebraic-geometric codes by Shokrollahi and Wasserman [21], and the improvement of Guruswami and...

Encoding of sensory events in internal states of the brain requires that this information can be decoded by other neural structures. The encoding of sensory events can involve both the spatial organization of neuronal activity and its temporal dynamics. Here we investigate the issue of decoding in the context of a recently proposed encoding scheme: the temporal population code. In this code, th...

Up to now, many studies have been done to show the origin of attitudes and their relationships with behaviors or actions. Some of those works have focused on students' attitudes and some have introduced the various contexts of language teaching and learning. These studies were enough to give a new impetus for conducting the present investigation. This paper investigated the teachers' attitudes ...

Abstract We study finite-time bit erasure in the context of majority-logic decoding. In particular, we calculate minimum amount work needed to erase a when one has full control over system dynamics. show that although single unit is easier slow-driving limit, general outperforms fast-erasure limit. Our results also suggest optimal design principles for bits under limited control.

Using the method of displacement we shall develop a unified framework for derivation of efficient list decoding algorithms for algebraic-geometric codes. We will demonstrate our method by accelerating Sudan’s list decoding algorithm for Reed-Solomon codes [22], its generalization to algebraicgeometric codes by Shokrollahi and Wasserman [21], and the recent improvement of Guruswami and Sudan [8]...

Tandem coding and decoding has been demonstrated to yield arbitrarily low error rates provided a sufficiently large block length is used. When applied to practical systems that are inherently limited to a finite complexity and therefore to finite block lengths, such a strategy may be largely suboptimal. Indeed, a tandem decoding strategy ignores two types of information: the source memory and t...

We generalize Sudan’s list decoding algorithm without multiplicity to evaluation codes coming from arbitrary order domains. The number of correctable errors by the proposed method is larger than the original list decoding without multiplicity.