scholarly journals SAT-Based Combinational and Sequential Dependency Computation

2016 ◽  
pp. 1-17 ◽  
Author(s):  
Mathias Soeken ◽  
Pascal Raiola ◽  
Baruch Sterin ◽  
Bernd Becker ◽  
Giovanni De Micheli ◽  
...  
Keyword(s):  
Sequential Dependency

Sequential Dependency Enhanced Graph Neural Networks for Session-based Recommendations

2021 ◽  
Author(s):  
Wei Guo ◽  
Shoujin Wang ◽  
Wenpeng Lu ◽  
Hao Wu ◽  
Qian Zhang ◽  
...  
Keyword(s):  
Neural Networks ◽  
Sequential Dependency ◽  
Graph Neural Networks

scholarly journals Chord-aware automatic music transcription based on hierarchical Bayesian integration of acoustic and language models

2018 ◽  
Vol 7 ◽  
Author(s):  
Yuta Ojima ◽  
Eita Nakamura ◽  
Katsutoshi Itoyama ◽  
Kazuyoshi Yoshii
Keyword(s):  
Latent Variables ◽  
Language Model ◽  
Language Models ◽  
Sequential Dependency ◽  
Acoustic Model ◽  
Hierarchical Bayesian ◽  
Generative Process ◽  
Music Transcription ◽  
Automatic Music Transcription ◽  
Music Audio

This paper describes automatic music transcription with chord estimation for music audio signals. We focus on the fact that concurrent structures of musical notes such as chords form the basis of harmony and are considered for music composition. Since chords and musical notes are deeply linked with each other, we propose joint pitch and chord estimation based on a Bayesian hierarchical model that consists of an acoustic model representing the generative process of a spectrogram and a language model representing the generative process of a piano roll. The acoustic model is formulated as a variant of non-negative matrix factorization that has binary variables indicating a piano roll. The language model is formulated as a hidden Markov model that has chord labels as the latent variables and emits a piano roll. The sequential dependency of a piano roll can be represented in the language model. Both models are integrated through a piano roll in a hierarchical Bayesian manner. All the latent variables and parameters are estimated using Gibbs sampling. The experimental results showed the great potential of the proposed method for unified music transcription and grammar induction.

scholarly journals Sequential dependency computation via geometric data structures

2014 ◽  
Vol 47 (2) ◽  
pp. 141-148 ◽  
Author(s):  
Gruia Calinescu ◽  
Howard Karloff
Keyword(s):  
Data Structures ◽  
Sequential Dependency ◽  
Geometric Data Structures ◽  
Geometric Data

scholarly journals Positive sequential dependency for face attractiveness perception

2019 ◽  
Vol 19 (12) ◽  
pp. 6 ◽  
Author(s):  
Erik Van der Burg ◽  
Gillian Rhodes ◽  
David Alais
Keyword(s):  
Sequential Dependency

Correlations within polyprotein forced unfolding dwell-times introduce sequential dependency

2020 ◽  
Vol 210 (3) ◽  
pp. 107495 ◽  
Author(s):  
Einat Chetrit ◽  
Yasmine Meroz ◽  
Ziv Klausner ◽  
Ronen Berkovich
Keyword(s):  
Sequential Dependency

scholarly journals Non-Autoregressive Machine Translation with Auxiliary Regularization

2019 ◽  
Vol 33 ◽  
pp. 5377-5384 ◽  
Author(s):  
Yiren Wang ◽  
Fei Tian ◽  
Di He ◽  
Tao Qin ◽  
ChengXiang Zhai ◽  
...  
Keyword(s):  
Machine Translation ◽  
High Efficiency ◽  
Side Information ◽  
Reconstruction Error ◽  
Sequential Dependency ◽  
Dual Nature ◽  
Benchmark Datasets ◽  
Source Sentence ◽  
Hidden States ◽  
The Cost

As a new neural machine translation approach, NonAutoregressive machine Translation (NAT) has attracted attention recently due to its high efficiency in inference. However, the high efficiency has come at the cost of not capturing the sequential dependency on the target side of translation, which causes NAT to suffer from two kinds of translation errors: 1) repeated translations (due to indistinguishable adjacent decoder hidden states), and 2) incomplete translations (due to incomplete transfer of source side information via the decoder hidden states). In this paper, we propose to address these two problems by improving the quality of decoder hidden representations via two auxiliary regularization terms in the training process of an NAT model. First, to make the hidden states more distinguishable, we regularize the similarity between consecutive hidden states based on the corresponding target tokens. Second, to force the hidden states to contain all the information in the source sentence, we leverage the dual nature of translation tasks (e.g., English to German and German to English) and minimize a backward reconstruction error to ensure that the hidden states of the NAT decoder are able to recover the source side sentence. Extensive experiments conducted on several benchmark datasets show that both regularization strategies are effective and can alleviate the issues of repeated translations and incomplete translations in NAT models. The accuracy of NAT models is therefore improved significantly over the state-of-the-art NAT models with even better efficiency for inference.

THE DEVELOPMENT OF LARVAL BEHAVIOURS IN THE MESOPHRAGMATICA GROUP OF SPECIES OF DROSOPHILA

Behaviour ◽  
1999 ◽  
Vol 136 (4) ◽  
pp. 391-409 ◽  
Author(s):  
Francisco Del Pino ◽  
Raul Godoy-Herrera
Keyword(s):  
Larval Development ◽  
Phylogenetic Relationships ◽  
Regular Sequence ◽  
Larval Period ◽  
Genetic Differences ◽  
Sequential Dependency ◽  
Marker Studies ◽  
Development And Evolution

AbstractThe development of behaviours in larvae of six species of the mesophragmatica group of Drosophila was investigated. The goals were: (i) to uncover patterns of development and evolution of behaviours, and (ii) to establish behavioural phenograms in order to compare them with the phylogenetic relationships based on chromosomal and isoenzymatic marker studies. In the presence of food, feeding, locomotion, turning, rearing, retreat and bending were recorded. During the whole larval period (24-28 to 192-196 h of age) D. mesophragmatica and D. viracochi show clear, regular but contrasting patterns of development for these behaviours. Fluctuations across larval age were observed for the behaviours exhibited by D. pavani, D. gaucha, D. gasici and D. brncici. As larval development progressed the behaviour of the six species became more differentiated. Larvae of the six species also differed in behavioural organization. The preadults of the species showed high recurrence of feeding and locomotion. In D. mesophragmatica, D. viracochi and D. gasici some elements of behaviour tended to occur in triplets of regular sequence, whereas sequences of two elements were observed in larvae of D. pavani and D. brncici. D. gaucha larvae do not show sequential dependency of behavioural elements. Behavioural similarity among the six species tends to follow the phylogenetic relationships established by chromosomal and isoenzymatic studies. The findings suggest that genetic differences among the six species are expressed in the development of larval behaviours.

scholarly journals REFACTORING WITH ORDERED COLLECTIONS OF FINE-GRAIN TRANSFORMATIONS

2013 ◽  
Vol 23 (03) ◽  
pp. 309-339
Author(s):  
EMMAD SAADEH ◽  
DERRICK G. KOURIE
Keyword(s):  
Building Blocks ◽  
Sequential Dependency ◽  
Level System ◽  
New Approach ◽  
System Description ◽  
Fine Grain ◽  
Prototype Tool ◽  
Different Levels

The objective of this paper is to explain the notion of fine-grain transformations (FGTs), showing how they can be used as prototypical building blocks for constructing refactorings of a design-level system description. FGT semantics are specified in terms of pre- and postconditions which, in turn, also determines the sequential dependency relationships between them. An algorithm is provided which uses sequential dependency relationships to convert an FGT-list to a set of so-called FGT-DAGs. It is shown how to compute the precondition of such ordered collections of FGTs. The paper introduces a new approach to deal with refactoring pre- and postconditions by defining them at two different levels. To give these concepts syntactical form, we rely on the Prolog formats used by an FGT-based refactoring prototype tool. An example is provided to illustrate the various concepts and to demonstrate that, because of their simplicity, well-defined pre-post semantics and their intuitive nature, FGTs provide a pragmatic basis for building refactorings.

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