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Improving Search through A3C Reinforcement Learning based Conversational Agent [article]

Milan Aggarwal, Aarushi Arora, Shagun Sodhani, Balaji Krishnamurthy
2018 arXiv   pre-print
We propose a stochastic virtual user which impersonates a real user and can be used to sample user behavior efficiently to train the agent which accelerates the bootstrapping of the agent.  ...  We develop a reinforcement learning based search assistant which can assist users through a set of actions and sequence of interactions to enable them realize their intent.  ...  But US is a subjective metric and is much harder to measure or annotate real data with.  ... 
arXiv:1709.05638v2 fatcat:tnoht3f5yvgcxbsxs5arvg32zy

Improving Search Through A3C Reinforcement Learning Based Conversational Agent [chapter]

Milan Aggarwal, Aarushi Arora, Shagun Sodhani, Balaji Krishnamurthy
2018 Lecture Notes in Computer Science  
We propose a stochastic virtual user which impersonates a real user and can be used to sample user behavior efficiently to train the agent which accelerates the bootstrapping of the agent.  ...  We develop a reinforcement learning based search assistant which can assist users through a set of actions and sequence of interactions to enable them realize their intent.  ...  But US is a subjective metric and is much harder to measure or annotate real data with.  ... 
doi:10.1007/978-3-319-93701-4_21 fatcat:vj3byu4yk5cvfpviv6tztsijsi

Loop 1 of APOBEC3C regulates its antiviral activity against HIV-1 [article]

Ananda Ayyappan Jaguva Vasudevan, Kannan Balakrishnan, Christoph G. W. Gertzen, Fanni Borvetó, Zeli Zhang, Anucha Sangwiman, Ulrike Held, Caroline Küstermann, Sharmistha Banerjee, Gerald G. Schumann, Dieter Häussinger, Ignacio G. Bravo (+2 others)
2020 biorxiv/medrxiv   pre-print
is also the inferred ancestral sequence for the last common ancestor of A3C|D|F in primates.  ...  Overall, our study highlights the possibility of A3C acting as a super restriction factor, however, this was likely evolutionarily selected against to achieve a balance between anti-viral/anti-LINE-1 activity  ...  A small number of studies have addressed the catalytic activity and substrate binding capacity of A3C [61, 70, 74, 85] .  ... 
doi:10.1101/2020.02.05.936021 fatcat:tkvsyphupjfj3de47zp44upkxy

CRSAL

Xuhui Ren, Hongzhi Yin, Tong Chen, Hao Wang, Nguyen Quoc Viet Hung, Zi Huang, Xiangliang Zhang
2020 ACM Transactions on Information Systems (TOIS; Formerly: ACM Transactions on Office Information Systems)  
DS for the general recommendation task has been rarely studied, and it is more complicated.  ...  In contrast, in the offline real-life cases, when a new customer walks into a store, the sales manager would start a conversation with the customer to first identify the demand of the customer (e.g., buying  ...  ACKNOWLEDGMENTS We would like to thank our anonymous reviewers for providing insightful review comments and suggestions.  ... 
doi:10.1145/3394592 fatcat:vwl44xoo6jdm5nlw3bhh7qyzga

Clone-Seeker: Effective Code Clone Search Using Annotations

Muhammad Hammad, Onder Babur, Hamid Abdul Basit, Mark Van Den Brand
2022 IEEE Access  
This keyword list can be extracted from a manually annotated general description of the clone class, or automatically generated from the source code of the entire clone class.  ...  The metadata includes a pre-processed list of identifiers from the code clones augmented with a list of keywords indicating the semantics of the code clone.  ...  ACKNOWLEDGMENT The authors acknowledge SURFsara and TU/e HPC Cluster for providing them computational credits for the experiments.  ... 
doi:10.1109/access.2022.3145686 fatcat:use6c3t2xjbyvgenvs2b3z66eu

Deep Learning in Spatiotemporal Cardiac Imaging: A Review of Methodologies and Clinical Usability

Karen Andrea Lara Hernandez, Theresa Rienmüller, Daniela Baumgartner, Christian Baumgartner
2020 Computers in Biology and Medicine  
Interestingly, not a single one of the reviewed papers was classified as a "clinical level" study.  ...  This review aims to synthesize the most relevant deep learning methods and discuss their clinical usability in dynamic cardiac imaging using for example the complete spatiotemporal image information of  ...  The keywords search resulted in a total of 346 potentially useful articles. Duplicated studies were removed, resulting in 287 papers.  ... 
doi:10.1016/j.compbiomed.2020.104200 pmid:33421825 fatcat:ltxjpt6yhzgvdkifo4wo3ftveq

Embodied AI-Driven Operation of Smart Cities: A Concise Review [article]

Farzan Shenavarmasouleh, Farid Ghareh Mohammadi, M. Hadi Amini, Hamid R. Arabnia
2021 arXiv   pre-print
can be used to make the whole system more efficient.  ...  Robots and physical machines are inseparable parts of a smart city. Embodied AI is the field of study that takes a deeper look into these and explores how they can fit into real-world environments.  ...  The second one was LSTM A3C that used an LSTM model with the Feedforward A3C act as a simple memory.  ... 
arXiv:2108.09823v1 fatcat:xcjyq2ad3jgbborpldopgcd3vm

Reinforcement Learning in Medical Image Analysis: Concepts, Applications, Challenges, and Future Directions [article]

Mingzhe Hu, Jiahan Zhang, Luke Matkovic, Tian Liu, Xiaofeng Yang
2022 arXiv   pre-print
This review article could serve as the stepping-stone for related research.  ...  Compared to the enormous deployments of supervised and unsupervised learning models, attempts to use reinforcement learning in medical image analysis are scarce.  ...  Disclosure The authors are not aware of any affiliations, memberships, funding, or financial holds that might be perceived as affecting the objectivity of this review.  ... 
arXiv:2206.14302v1 fatcat:45moxmomlbcexjnsjepkidgwr4

AID/APOBEC-network reconstruction identifies pathways associated with survival in ovarian cancer

Martin Svoboda, Anastasia Meshcheryakova, Georg Heinze, Markus Jaritz, Dietmar Pils, Dan Cacsire Castillo-Tong, Gudrun Hager, Theresia Thalhammer, Erika Jensen-Jarolim, Peter Birner, Ioana Braicu, Jalid Sehouli (+6 others)
2016 BMC Genomics  
Results: We structured the study by three consecutive analytical modules, which include the multigene-based expression profiling in a cohort of patients with primary serous ovarian cancer using a self-created  ...  , and systems biologybased reconstruction of the AID/APOBEC-driven disease-relevant mechanisms using transcriptomics data from ovarian cancer samples.  ...  Mechtcheriakova); the Sixth Framework Programme (FP6) Project of the European Union (EU) called 'Ovarian Cancer: Diagnosis of a silent killer -OVCAD', no. 018698.  ... 
doi:10.1186/s12864-016-3001-y pmid:27527602 pmcid:PMC4986275 fatcat:jalzl2z2vnfgnfuctuq2jn4k3m

A general overview and bibliometric analysis of seven ACM hypertext and web conferences

Swati Agarwal, Nitish Mittal, Ashish Sureka
2017 International Journal of Web Engineering and Technology  
Bibliometric analysis of published scientific papers is a widely used practice to conduct quantitative evaluations and assessments of conferences.  ...  In this study, we performed an in-depth bibliometric, scientometric and exploratory analysis of ACM SIGWEB sponsored conferences by visually analysing the DBLP database.  ...  To avoid the noise in tags (repetitive keywords with different names or abbreviations), we used the ACM concepts to study the topics and themes of SIGWEB conferences.  ... 
doi:10.1504/ijwet.2017.088376 fatcat:x52guzmov5ejzaznn3zow25an4

Standard Echocardiographic View Recognition in Diagnosis of Congenital Heart Defects in Children Using Deep Learning Based on Knowledge Distillation

Lanping Wu, Bin Dong, Xiaoqing Liu, Wenjing Hong, Lijun Chen, Kunlun Gao, Qiuyang Sheng, Yizhou Yu, Liebin Zhao, Yuqi Zhang
2022 Frontiers in Pediatrics  
This study provides a solid foundation for the subsequent use of artificial intelligence (AI) to identify CHDs in children.  ...  This study aims to evaluate the feasibility and accuracy of standard echocardiographic view recognition in the diagnosis of CHDs in children using convolutional neural networks (CNNs).  ...  This study provides a solid foundation for the subsequent use of artificial intelligence (AI) to identify CHDs in children.  ... 
doi:10.3389/fped.2021.770182 pmid:35118028 pmcid:PMC8805220 fatcat:kupcxiuxijev3ho3s4innytfru

Deep Reinforcement Learning for Autonomous Driving: A Survey [article]

B Ravi Kiran, Ibrahim Sobh, Victor Talpaert, Patrick Mannion, Ahmad A. Al Sallab, Senthil Yogamani, Patrick Pérez
2021 arXiv   pre-print
With the development of deep representation learning, the domain of reinforcement learning (RL) has become a powerful learning framework now capable of learning complex policies in high dimensional environments  ...  The role of simulators in training agents, methods to validate, test and robustify existing solutions in RL are discussed.  ...  Instead, the more general stochastic game (SG) may be used in the case of a Multi-Agent System (MAS) [56] .  ... 
arXiv:2002.00444v2 fatcat:axj3ohhjwzdrxp6dgpfqvctv2i

Towards a Standardised Performance Evaluation Protocol for Cooperative MARL [article]

Rihab Gorsane, Omayma Mahjoub, Ruan de Kock, Roland Dubb, Siddarth Singh, Arnu Pretorius
2022 arXiv   pre-print
By conducting a detailed meta-analysis of prior work, spanning 75 papers accepted for publication from 2016 to 2022, we bring to light worrying trends that put into question the true rate of progress.  ...  Multi-agent reinforcement learning (MARL) has emerged as a useful approach to solving decentralised decision-making problems at scale.  ...  Acknowledgments and Disclosure of Funding The authors would like to kindly thank the following people for useful discussions and feedback on this work: Jonathan Shock, Matthew Morris, Claude Formanek,  ... 
arXiv:2209.10485v1 fatcat:ryldhay5zzc2tcg2igpysybgwa

Deep Reinforcement Learning: An Overview [article]

Yuxi Li
2018 arXiv   pre-print
Please see Deep Reinforcement Learning, arXiv:1810.06339, for a significant update.  ...  We mention topics not reviewed yet, and list a collection of RL resources. After presenting a brief summary, we close with discussions.  ...  See Serban et al. (2015) for a survey of corpora for building dialogue systems.  ... 
arXiv:1701.07274v6 fatcat:x2es3yf3crhqblbbskhxelxf2q

Deep Reinforcement Learning [article]

Yuxi Li
2018 arXiv   pre-print
We start with background of artificial intelligence, machine learning, deep learning, and reinforcement learning (RL), with resources.  ...  Then we discuss important mechanisms for RL, including attention and memory, unsupervised learning, hierarchical RL, multi-agent RL, relational RL, and learning to learn.  ...  The authors propose policy-space response oracle (PSRO), and its approximation, deep cognitive hierarchies (DCH), to compute best responses to a mixture of policies using deep RL, and to compute new meta-strategy  ... 
arXiv:1810.06339v1 fatcat:kp7atz5pdbeqta352e6b3nmuhy
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