Titlebook: Advances in Artificial Intelligence; Selected Papers from Katsutoshi Yada,Daisuke Katagami,Hisashi Kashima Conference proceedings 2021 The

Anticlimax

https://doi.org/10.1007/978-3-319-55524-9end, this paper proposes an approach that performs node classification which is the first step towards extracting the structure of online discussions. In this regard, the proposed approach employs a graph attention network (GAT) in order to directly learn the discussion structure. In specific, the G

損壞

人類

Xiangyu Li,Gongning Luo,Kuanquan Wang legal reasoning systems, works based on the literal interpretation of legal rules. However, in some exceptional cases, the literal interpretation of legal rules may create unexpected consequences. In this paper, we introduce the idea of . for tracing back the intended precedents by lawmakers. Based

搖晃

Po-Yu Kao,Jeffereson W. Chen,B. S. Manjunathre are cases when a single fixed viewpoint does not provide sufficient information to perform a designated robot task. Environments with high occlusion, or cases where objects have fragile components, it is difficult for robots to identify the task relevant viewpoint to achieve a task or goal. Herei

LITHE

Xiangyu Li,Gongning Luo,Kuanquan Wangs a low-effort, easy-to-adopt, and cost-effective mechanism for crowd data collection and analysis. In crowd replication, the quality of data collection is particularly important, which depends on the representativeness of the target population-based sampling. The main two target selection strategie

transdermal

合同

G. Anthony Reina,Ravi Panchumarthylance (SMB) of Antarctica. To accomplish this, we attempted to identify the snowfall cloud at Syowa Station, Antarctica. We constructed a new convolutional neural network (CNN) architecture with multinomial and binary classifications for National Oceanic and Atmospheric Administration (NOAA) Advance

隼鷹

https://doi.org/10.1007/978-3-030-11723-8ones, some researchers set off to focus on dialogue generation models in which causal relation is also taken into consideration. However, it is hard to distinguish whether there is causal relation between speaker’s and responder’s utterances from dialogue automatically, which makes collecting such u

藝術(shù)

G. Anthony Reina,Ravi Panchumarthyof the demonstrator. We thus propose the use two algorithms for inverse reinforcement learning, Bayesian Neural Network and Maximum Entropy to deal with this issue. The primary objective of this work is to determine if varying qualities of domain knowledge, in the form of a demonstrator, would have

騙子