scholarly journals Improving Welfare in One-Sided Matchings using Simple Threshold Queries

2021 ◽  
Author(s):  
Thomas Ma ◽  
Vijay Menon ◽  
Kate Larson
Keyword(s):  
Pareto Optimality ◽  
Welfare Loss ◽  
Desirable Property ◽  
Matching Problems ◽  
Extra Information ◽  
Classic Problem ◽  
Ordinal Preferences ◽  
Design Algorithms

We study one-sided matching problems where each agent must be assigned at most one object. In this classic problem it is often assumed that agents specify only ordinal preferences over objects and the goal is to return a matching that satisfies some desirable property such as Pareto optimality or rank-maximality. However, agents may have cardinal utilities describing their preference intensities and ignoring this can result in welfare loss. We investigate how to elicit additional cardinal information from agents using simple threshold queries and use it in turn to design algorithms that return a matching satisfying a desirable matching property, while also achieving a good approximation to the optimal welfare among all matchings satisfying that property. Overall, our results show how one can improve welfare by even non-adaptively asking agents for just one bit of extra information per object.

SANTM: Efficient Self-attention-driven Network for Text Matching

2022 ◽  
Vol 22 (3) ◽  
pp. 1-21
Author(s):  
Prayag Tiwari ◽  
Amit Kumar Jaiswal ◽  
Sahil Garg ◽  
Ilsun You
Keyword(s):  
Natural Language ◽  
State Of The Art ◽  
The State ◽  
Attention Mechanism ◽  
Matching Problems ◽  
Attention Model ◽  
Extra Information ◽  
Textual Entailment ◽  
Benchmark Datasets ◽  
Text Matching

Self-attention mechanisms have recently been embraced for a broad range of text-matching applications. Self-attention model takes only one sentence as an input with no extra information, i.e., one can utilize the final hidden state or pooling. However, text-matching problems can be interpreted either in symmetrical or asymmetrical scopes. For instance, paraphrase detection is an asymmetrical task, while textual entailment classification and question-answer matching are considered asymmetrical tasks. In this article, we leverage attractive properties of self-attention mechanism and proposes an attention-based network that incorporates three key components for inter-sequence attention: global pointwise features, preceding attentive features, and contextual features while updating the rest of the components. Our model follows evaluation on two benchmark datasets cover tasks of textual entailment and question-answer matching. The proposed efficient Self-attention-driven Network for Text Matching outperforms the state of the art on the Stanford Natural Language Inference and WikiQA datasets with much fewer parameters.

scholarly journals Pareto optimality in many-to-many matching problems

2014 ◽  
Vol 14 ◽  
pp. 160-169 ◽  
Author(s):  
Katarína Cechlárová ◽  
Pavlos Eirinakis ◽  
Tamás Fleiner ◽  
Dimitrios Magos ◽  
Ioannis Mourtos ◽  
...  
Keyword(s):  
Pareto Optimality ◽  
Matching Problems

Non-Blind Image Deconvolution Based on “Ringing” Removal Using Convolutional Neural Network

2020 ◽  
Vol 2020 (10) ◽  
pp. 181-1-181-7
Author(s):  
Takahiro Kudo ◽  
Takanori Fujisawa ◽  
Takuro Yamaguchi ◽  
Masaaki Ikehara
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Network Architecture ◽  
Large Scale ◽  
Blind Deconvolution ◽  
Training Dataset ◽  
Image Deconvolution ◽  
Classic Problem ◽  
Key Points ◽  
Blind Image

Image deconvolution has been an important issue recently. It has two kinds of approaches: non-blind and blind. Non-blind deconvolution is a classic problem of image deblurring, which assumes that the PSF is known and does not change universally in space. Recently, Convolutional Neural Network (CNN) has been used for non-blind deconvolution. Though CNNs can deal with complex changes for unknown images, some CNN-based conventional methods can only handle small PSFs and does not consider the use of large PSFs in the real world. In this paper we propose a non-blind deconvolution framework based on a CNN that can remove large scale ringing in a deblurred image. Our method has three key points. The first is that our network architecture is able to preserve both large and small features in the image. The second is that the training dataset is created to preserve the details. The third is that we extend the images to minimize the effects of large ringing on the image borders. In our experiments, we used three kinds of large PSFs and were able to observe high-precision results from our method both quantitatively and qualitatively.

UNSUR MANAJEMEN DALAM PENGELOLAAN LEMBAGA PENDIDIKAN ISLAM DI INDONESIA

2018 ◽  
Vol 6 (1) ◽  
pp. 675-695
Author(s):  
FAJRI DWIYAMA
Keyword(s):  
Staff Development ◽  
Management Education ◽  
Poor Quality ◽  
Islamic Education ◽  
Educational Institutions ◽  
Education Management ◽  
Classic Problem ◽  
The World ◽  
Education Personnel

Abstract: Islamic education institutions in Indonesia face two challenges, namely; internal and external. Internally, Islamic education is faced with the classic problem of the low quality of human resources in education management. The causes include poor quality and education staff development and selectivity of education personnel. Furthermore externally, Islamic education institutions faced three major issues; globalization, democratization, and liberalization. The issue of globalization that is identical with market orientation and mechanism also affects the world of education. That way in education also includes awareness about how to attract and convince the community of the type and model of education. From here, the education world is ready or not ready to be involved in competition to gain public trust. To face these challenges Islamic Education institutions must maximally manage and empower all elements of management in the management of educational institutions. A good understanding of the elements of management can have an impact on the readiness of educational institutions to manage their institutions well in any condition to be the best and foremost. Keywords: Elements of Management, Management, Education, Islam

Rhetoric and argumentation: the unity of the field

2017 ◽  
Author(s):  
Michel Meyer
Keyword(s):  
The Other ◽  
Classic Problem ◽  
False Dilemma ◽  
The Difference ◽  
As If

Rhetoric has always been torn between the rhetoric of figures and the rhetoric of conflicts or arguments, as if rhetoric were exclusively one or the other. This is a false dilemma. Both types of rhetoric hinge on the same structure. A common formula is provided in Chapter 3 which unifies rhetoric stricto sensu and rhetoric as argumentation as two distinct but related strategies adopted according to the level of problematicity of the questions at stake, thereby giving unity to the field called “Rhetoric.” Highly problematic questions require arguments to justify their answers; non-divisive ones can be treated rhetorically through their answers as if they were self-evident. Another classic problem is how to understand the difference between logic and rhetoric. The difference between the two is due to the presence of questions explicitly answered in the premises in logic and only suggested (or remaining indeterminate) in rhetoric.

scholarly journals Impact of alternative regional trade arrangements on the Ethiopian economy

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Habtamu Shiferaw Amogne ◽  
Taiji Hagiwara
Keyword(s):  
Transition Period ◽  
Terms Of Trade ◽  
Endowment Effect ◽  
Welfare Loss ◽  
Customs Union ◽  
Regional Trade ◽  
Partnership Agreement ◽  
Saving Effect ◽  
The Impact ◽  
Trade And Investment

AbstractThe Common Market for Eastern and Southern Africa (COMESA) is a Free Trade Area (FTA) regional trade agreement in Africa. Currently, Ethiopia is negotiating to join COMESA FTA. This study assesses the impact of three regional trade arrangements, COMESA FTA, customs unions, and the European Partnership Agreement (EPA) on the economy of Ethiopia. The analysis is based on a static Global Trade Analysis Project (GTAP) model, version 9 database. Unlike previous studies, the customs union scenarios are designed at the detailed Harmonized System (HS) level. COMESA FTA (scenario 1) with standard GTAP model results in a welfare loss for Ethiopia due to negative terms of trade and investment-saving effect, but with unemployment closure (scenario 2); Ethiopia enjoys a welfare gain mainly due to endowment effect. In scenario 3 (COMESA customs union) and scenario 4 (European Partnership Agreement), Ethiopia loses due to negative terms of trade and investment-saving effect. There is a large increase in demand for unskilled labor force in Ethiopia by around US$23 million, US$112 million, and US$43 million for scenario 2, 3, and 4 respectively. Moreover, there is a positive output effect for oilseeds, leather, and basic metals across all scenarios. The world, as a whole, enjoys welfare gains with COMESA FTA (scenario 1 and 2). However, with scenario 3 and 4, there is an overall welfare loss. There is no strong reason for Ethiopia to move to the customs union, and the EPA in the short run. Therefore, a transition period is necessary, but it is recommended for Ethiopia to join COMESA FTA.

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