Meta-cognitive learning algorithm for neuro-fuzzy inference systems by Kartick Subramanian

“…The learning algorithms employed in these systems are inspired from the physiology and functioning of human brain. As the study on neuroscience and cognitive psychology is an ongoing process, it is essential that these machine learning algorithms be extended with developments from the findings in human learning psychology. …”
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Deep Reinforcement Learning in complex environments by Nardelli, N

HyDRA: hypergradient data relevance analysis for interpreting deep neural networks. by Chen, Yuanyuan, Li, Boyang, Yu, Han, Wu, Pengcheng, Miao, Chunyan

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Mastering Voice Interfaces : Creating Great Voice Apps for Real Users / by Thymé-Gobbel, Ann, author 642940, Jankowski, Charles, author 642941

Source language effect on translating Korean honorifics by Paik, Kyonghee., Ohtake, Kiyonori., Bond, Francis., Yamamoto, Kazuhide.

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Improving contextual coherence in variational personalized and empathetic dialogue agents by Lee, Jing Yang, Lee, Kong Aik, Gan, Woon Seng

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Detecting adversarial samples for deep neural networks through mutation testing by Tan, Kye Yen

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16.412J / 6.834J Cognitive Robotics, Spring 2005 by Williams, Brian Charles

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TraceTogether : pandemic response, democracy, and technology by Stevens, Hallam, Haines, Monamie Bhadra

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Transfer learning application on snake classification by Tananda, Hans

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Stealthy and robust glitch injection attack on deep learning accelerator for target with variational viewpoint by Liu, Wenye, Chang, Chip-Hong, Zhang, Fan

“…The advocacy of 'model once, run optimized anywhere' paradigm introduces potential new security threat to edge intelligence that is methodologically different from the well-known adversarial examples. …”
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An agent-based framework for problem solving in symbiotic simulation systems by Aydt, Heiko

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RES.TLL-008 Social and Ethical Responsibilities of Computing (SERC), Fall 2022 by Shah, Julie, Kaiser, David

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16.412J / 6.834J Cognitive Robotics, Spring 2004 by Williams, Brian C., Roy, Nicholas

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Multimodal fusion for navigation of autonomous mobile robots using a deep learning method by Lee, Anthony Wen Hao

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Cognizant multitasking in multiobjective multifactorial evolution : MO-MFEA-II by Bali, Kavitesh Kumar, Gupta, Abhishek, Ong, Yew-Soon, Tan, Puay Siew

“…Humans have the ability to identify recurring patterns in diverse situations encountered over a lifetime, constantly understanding relationships between tasks and efficiently solving them through knowledge reuse. …”
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Security Orchestration, Automation, and Response for Security Analysts : Learn the secrets of SOAR to improve MTTA and MTTR and strengthen your organization's security posture / by Kovacevic, Benjamin, author 656337, Packt Publishing (Online service) 656336

“…Next, you'll learn how SOAR works and what its benefits are, including optimized threat intelligence, incident response, and utilizing threat hunting in investigations. …”
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The political-economic risks of AI by Carvalho, J-P

“…It is possible that AI creates a superabundant world with unprecedented human freedom. In this essay, however, I will explore a tail risk in which human-level artificial general intelligence (AGI) radically concentrates the global economy, breaks democratic and egalitarian institutions, and tears the social fabric, collapsing human productivity. …”

HCI for Cybersecurity, Privacy and Trust : Third International Conference, HCI-CPT 2021, Held as Part of the 23rd HCI International Conference, HCII 2021, Virtual Event, July 24-29... by HCI for Cybersecurity, Privacy and Trust (Conference) (3rd : 2021 : Online) 643239, Moallem, Abbas, editor 630807

AI and big data applications by May Thu Naing

“…AI is the concept of machines carrying out work requiring the completion of human intelligence. AI covers the research area generally; machine learning and deep learning are being sub-segments of AI. …”
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