Transfer learning aims at improving the performance of target learners on domains by transferring knowledge contained in different but related source domains. In this way, dependence a large number target-domain data can be reduced for constructing learners. Due to wide application prospects, transfer has become popular and promising area machine learning. Although there are already some valuable impressive surveys learning, these introduce approaches relatively isolated way lack recent...

Transfer learning aims at improving the performance of target learners on domains by transferring knowledge contained in different but related source domains. In this way, dependence a large number domain data can be reduced for constructing learners. Due to wide application prospects, transfer has become popular and promising area machine learning. Although there are already some valuable impressive surveys learning, these introduce approaches relatively isolated way lack recent advances...

Knowledge Graph (KG) alignment is to discover the mappings (i.e., equivalent entities, relations, and others) between two KGs. The existing methods can be divided into embedding-based models, conventional reasoning lexical matching based systems. former compute similarity of entities via their cross-KG embeddings, but they usually rely on an ideal supervised learning setting for good performance lack appropriate avoid logically wrong mappings; while latter address issue are poor at utilizing...

Zeroing neural dynamics (ZND), a special class of dynamics, is powerful methodology for time-varying problems solving. On the basis this methodology, different continuous-time ZND models are obtained various Continuous-time supposed to be discretized sake prevalent digital-equipment applications, and discretization formula needed transform model into discrete-time model. In article, models, new formulas presented. The minimization problem, which representative issue, also discussed as an...

Deep learning enabled semantic communications are attracting extensive attention. However, most works normally ignore the data acquisition process and suffer from robustness issues under dynamic channel environment. In this paper, we propose an adaptive joint sampling-semantic-channel coding (Adaptive-JSSCC) framework. Specifically, a semantic-aware sampling reconstruction method to optimize number of samples dynamically for each region images. According significance, matrices individually...

Time-variant problems, which can be classified into future and non-future are often encountered in academia industry. In a problem, we only know the information on current past time instants, have to acquire next-time-instant solution before next instant arrives. Zeroing neural dynamics (ZND) Zhang et al. discretization (ZeaD) formula group two essential tools build discrete-time ZND (DT-ZND) models for problems solving. The former uses systematical design continuous-time (CT-ZND) model,...

This paper presents our wining contribution to SemEval 2021 Task 8: MeasEval. The purpose of this task is identifying the counts and measurements from clinical scientific discourse, including quantities, entities, properties, qualifiers, units, modifiers, their mutual relations. can be induced a joint entity relation extraction problem. Accordingly, we propose CONNER, cascade count measurement tool that identify entities corresponding relations in two-step pipeline model. We provide detailed...

In this paper, Taylor expansion and Vandermonde determinant are used to derive the coefficients of group extrapolation formulas. derivation coefficients, we first use expand formulas, then is transformed into matrix. The general formula obtained by using characteristics Cramer's rule. After careful observation, find that rule similar Pascal's triangle. Three functions in numerical experiments. We evaluate effect different step size values on error order-3 formula, order formulas with some...

In this paper, the derivations and some concepts of physical equivalency Zhang dynamics (ZD) formulas systems are proposed investigated. Based on four low-order ZD formulas, general form formula is obtained by mathematical induction. addition, coefficients these link Pascal triangle, expressions have kind law in form. Therefore, between triangle provide a quick easy way to construct any order, as part equivalency. Furthermore, examples application integrator solve tracking control problems...

Two classes of time-dependent matrices are proposed and investigated in this paper terms their pseudoinverses solving. On one hand, the pseudoinverse Getz-Masden matrix can be solved by dynamic system (GMDS) effectively accurately. other GMDS not solve for Zhang matrix, as found shown paper. Besides, purpose obtaining discrete-time illustrating phenomena, Euler forward formula four-point ZeaD (Zhang et al discretization) adopted to discretize continuous-time GMDS. After getting two models,...

The transfer of science and technology center is great importance to many countries in the world because are primary productive forces also important embodiment comprehensive national strength. In this paper, according Yuasa phenomenon, we use ASF (addition-and-subtraction frequency) method, which based on commensurability predict possibility scientific future, as well time its possible impact.

The transfer learning toolkit wraps the codes of 17 models and provides integrated interfaces, allowing users to use those by calling a simple function. It is easy for primary researchers this choose proper real-world applications. written in Python distributed under MIT open source license. In paper, current state described necessary environment setting usage are introduced.

Knowledge Graph (KG) alignment aims at finding equivalent entities and relations (i.e., mappings) between two KGs. The existing approaches utilize either reasoning-based or semantic embedding-based techniques, but few studies explore their combination. In this demonstration, we present PRASEMap, an unsupervised KG system that iteratively computes the Mappings with both Probabilistic Reasoning (PR) And Semantic Embedding (SE) techniques. PRASEMap can support various as SE module, enables easy...

Future minimization, i.e., discrete time-varying is a difficult and meaningful problem. It has been successfully solved by Zhang et al using zeroing dynamics (ZD) discretization formulas. In this paper, type of discrete-time ZD (DT-ZD) model, which obtained via utilizing ZeaD (Zhang Discretization) formula 4IgS_Y, analyzed investigated to ensure its stability. Specifically, theoretical guarantees, we propose the step-length domain, or say, effective domain step-length, makes model stable....

In this study, the hyper-chaotic 4th-order Lu system stabilization (or say, stabilizing) problem is solved based on Zhang neural dynamics (ZND) method as well four-instant et al discretization (ZeaD) formulas. Firstly, controller for single-input stabilizing developed by using ZND method. Then, discretizing continuous controller, discrete-time models are obtained, and ZeaD formulas adopted during process. Finally, computer experiments performed to check accuracy effectiveness of our stabilizing.

In this paper, a new discrete-time zeroing-dynamics (or termed, Zhang-dynamics, ZD) model is proposed, analyzed and investigated for solving generalized-Sylvester-type future linear matrix inequality (GS-type FLMI). First of all, based on ZD design formula, continuous-time (CTZD) model, i.e., CTZD-I proposed CTLMI). Secondly, five-node Zhang et al discretization formula (ZeaD also termed time-discretization or [ZTD] formula) presented the first-order derivative approximation with higher...

Zhang neural network (ZNN, also called zeroing network) is considered as an effective method to solve time-dependent problems (i.e., time-varying problems). Different continuous-time ZNN models of various solving are obtained by exploiting the design formula. Before applying on digital equipment, acquired generally discretized using time discretization (ZTD) To provide readers with choice and different ZTD formulas for solving, this paper summarizes formulas, presents them in tables....

Knowledge Graph (KG) alignment is to discover the mappings (i.e., equivalent entities, relations, and others) between two KGs. The existing methods can be divided into embedding-based models, conventional reasoning lexical matching based systems. former compute similarity of entities via their cross-KG embeddings, but they usually rely on an ideal supervised learning setting for good performance lack appropriate avoid logically wrong mappings; while latter address issue are poor at utilizing...