We propose ConVEx (Conversational Value Extractor), an efficient pretraining and fine-tuning neural approach for slot-labeling dialog tasks. Instead of relying on more general pretraining objectives from prior work (e.g., language modeling, response
selection), ConVEx's pretraining objective, a novel pairwise cloze task using Reddit data, is well aligned with its intended usage on sequence labeling tasks. This enables learning domain-specific slot labelers by simply fine-tuning decoding layers of the pretrained general-purpose sequence labeling model, while the majority of the pretrained model's parameters are kept frozen. We report state-of-the-art performance of ConVEx across a range of diverse domains and data sets for dialog slot-labeling, with the largest gains in the most challenging, few-shot setups. We believe that ConVEx's reduced pretraining times (i.e., only 18 hours on 12 GPUs) and cost, along with its efficient fine-tuning and strong performance, promise wider portability and scalability for data-efficient sequence-labeling tasks in general.
It is often useful to replace a function with a sequence of smooth functions
approximating the given function to resolve minimizing optimization problems.
The most famous one is the Moreau envelope. Recently the function was organized
using the Br
egman distance h D . It is worth noting that Bregman distance h D is
not a distance in the usual sense of the term. In general, it is not symmetric and it
does not satisfy the triangle inequality
The purpose of the research is to study the convergence of the Moreau envelope
function and the related proximal mapping depends on Bregman Distance for a
function on Banach space. Proved equivalence between Mosco-epi-convergence of
sequence functions and pointwise convergence of Moreau-Bregman envelope We
also studied the strong and weak convergence of resolvent operators According to
the concept of Bregman distance.
Let denote the class of functions that are analytic and univalent in the unit disk such that:
Using De Brange Theorem it has been shown for the functinos of this class that the the following estimations are true:
For the Subclass ( e.i. The Class of Convex functionswhdch in analytic and univalent in unit disk) the following estimations are true.
In this paper we study some basic properties of the Moreau-Yosida function with two variables , and generalize the results of related to study of the convergence for sequence of convex-concave functions and the sequence of Moreau-Yosida function corr
esponding , and the basic theorem that we proved is : for any sequence of convex-concave functions , if they are convergent of the Moreau-Yosida distance then the sequence of Moreau-Yosida function corresponding will be convergent to the concept of Mosco-epi/hypo graph convergence .
Let A be a set in R3. A is called a Convex set in accordance with the coordinate planes ,if and only if ,any parallel plane to any coordinate planes was intersected with A is convex set . In this research we introduced a new style in the convexity is
convexity in accordance with the coordinate planes ,and got a some of results and theorems, the most important : proving that every convex set in accordance with the coordinate planes is convex set, and we have offered many examples that illustrate the relationship between starshaped set, compact set , simply connected set , coordinate convex set and convex set in accordance with the coordinate planes .
The supporting functions are powerful tools for studying several problems in mathematics and engineering sciences, since they have useful advantages.
In this paper, we prove that the following conditions and statements are equivalent:
1. is convex.
2. is supporting
3. is subadditive on the unit sphere.
The aim of the study was to evaluate The relation between frontonasal complex and cases with class I, II, III Malooclousion. Material and methods: True lateral cephalometric radiograph of the sample that comprises 61 patienta of 34 females and 27 ma
les aged 18-25 years.The data were analyzed using independent sample Student t-test, Anova analysis and Pearson correlation analysis. The results showed that significant differences between the value of front complsx and frontonasal angle and different malooclusion classes, but there were no significant differences between male and female according to frontal convex and frontonasal angle, However, the differences between classes according to frontal convex and frontonasal angle were found in females.
This paper presents a certain method to determine the range of variability ( or the set of values) of some functionals defined in the Class (i.e the class of analytic functions in the unit disk
It have been shown in this class that the range of variability of the functional is the closed disk
The estimations of modulus of function and some other estimations related were also obtaind
The purpose of the research is to study Bergman distance to generalize Lasry – Lions regularization which play important role of theory optimization.
To do that we replace the quardatic additive terms in Lasry – Lions regularization by more gene
ral Bergman distance (non metric distance), and study properties generalized approximation and proof its continuous as we give a relationship between the solution minimization sets of function and Lions – Lasry Regularization and others properties.
In this research we will find a law of the large numbers for random convex – concave closed functions, and generalize some results related to lower semi- continuous functions to similar results concerning the convex– concave functions, and that will
be done with using the parent convex functions and the Mosco-epi \ hypo-convergence.
