The hierarchical tensor format allows for the low-parametric representation of tensors even in high dimensions d. The efficiency of this representation strongly relies on an appropriate hierarchical splitting of the different directions 1,. .. , d such that the associated ranks remain sufficiently small. This splitting can be represented by a binary tree which is usually assumed to be given. In...

The Hierarchical Sub-Sentential Alignment (HSSA) method is a method to obtain aligned binary tree structures for two aligned sentences in translation correspondence. We propose to use the binary aligned tree structures delivered by this method as training data for preordering prior to machine translation. For that, we learn a Bracketing Transduction Grammar (BTG) from these binary aligned tree ...

In this paper we describe a method for recommending news on a news portal based on our novel representation by a similarity tree. Our method for recommending articles is based on their content. The recommendation employs a hierarchical incremental clustering which is used to discover additional information for effective recommending. The important and novel part of our method is an approach to ...

Hierarchical structure is ubiquitous in data across many domains. There are many hierarchical clustering methods, frequently used by domain experts, which strive to discover this structure. However, most of these methods limit discoverable hierarchies to those with binary branching structure. This limitation, while computationally convenient, is often undesirable. In this paper we explore a Bay...

Relation extraction by universal schema avoids mapping to a brittle, incomplete traditional schema by instead making predictions in the union of all input schemas, including textual patterns. Modeling these predictions by matrix competition with matrix factorization has yielded state-of-the-art accuracies. One difficulty with prior work in matrix factorization, however, is that there is no nega...

ProtoNet is an agglomerative binary clustering procedure that provides a hierarchical tree of over 1,000,000 proteins. In this paper we show that the ProtoNet tree is composed of a large number of biologically valid clusters and that the tree expresses functional information. We confirm that several aspects of the tree highly correspond to various external sources, some of which are manually va...

Emotion state tracking is an important aspect of humancomputer and human-robot interaction. It is important to design task specific emotion recognition systems for real-world applications. In this work, we propose a hierarchical structure loosely motivated by Appraisal Theory for emotion recognition. The levels in the hierarchical structure are carefully designed to place the easier classificat...

We present new links between some remarkable martingales found in the study of the Binary Search Tree or of the bisection problem, looking at them on the probability space of a continuous time binary branching process.

Neural probabilistic language models (NPLMs) have been shown to be competitive with and occasionally superior to the widely-used n-gram language models. The main drawback of NPLMs is their extremely long training and testing times. Morin and Bengio have proposed a hierarchical language model built around a binary tree of words, which was two orders of magnitude faster than the nonhierarchical m...

In this paper a new method of rule generation for hierarchical fuzzy systems (Hierarchical Fuzzy Associative Memory, HIFAM) is described. A HIFAM is structured as a binary tree and overcomes the exponential growth of the rulebases when the number of inputs increases. The training algorithm for HIFAM is suited for approximation and classification problems. Several benchmarks demonstrate that the...