Search Results - "Chung, Tae Choong"

Accurate multi-criteria decision making methodology for recommending machine learning algorithm by Ali, Rahman, Lee, Sungyoung, Chung, Tae Choong

“…•A multi-criteria decision making methodology is proposed to select best classifier.•NGT-based method is adapted to choose suitable classifier's evaluation…”
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Univector field method-based multi-agent navigation for pursuit problem in obstacle environments by Tuyen, Le Pham, Viet, Hoang Huu, An, Sang Hyeok, Lee, Seung Gwan, Kim, Dong-Han, Chung, Tae Choong

“…The pursuit problem is a well-known problem in computer science. In this problem, a group of predator agents attempt to capture a prey agent in an environment…”
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Dyna-QUF: Dyna-Q based univector field navigation for autonomous mobile robots in unknown environments by Viet, Hoang-huu, Choi, Seung-yoon, Chung, Tae-choong

“…A novel approach was presented to solve the navigation problem of autonomous mobile robots in unknown environments with dense obstacles based on a univector…”
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On Curating Multimodal Sensory Data for Health and Wellness Platforms by Amin, Muhammad Bilal, Banos, Oresti, Khan, Wajahat Ali, Muhammad Bilal, Hafiz Syed, Gong, Jinhyuk, Bui, Dinh-Mao, Cho, Soung Ho, Hussain, Shujaat, Ali, Taqdir, Akhtar, Usman, Chung, Tae Choong, Lee, Sungyoung

“…In recent years, the focus of healthcare and wellness technologies has shown a significant shift towards personal vital signs devices. The technology has…”
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Privacy-Aware Relevant Data Access with Semantically Enriched Search Queries for Untrusted Cloud Storage Services by Pervez, Zeeshan, Ahmad, Mahmood, Khattak, Asad Masood, Lee, Sungyoung, Chung, Tae Choong

“…Privacy-aware search of outsourced data ensures relevant data access in the untrusted domain of a public cloud service provider. Subscriber of a public cloud…”
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Learning via human feedback in continuous state and action spaces by Vien, Ngo Anh, Ertel, Wolfgang, Chung, Tae Choong

“…This paper considers the problem of extending Training an Agent Manually via Evaluative Reinforcement (TAMER) in continuous state and action spaces…”
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A semantic sequence similarity based approach for extracting medical entities from clinical conversations by Satti, Fahad Ahmed, Hussain, Musarrat, Ali, Syed Imran, Saleem, Misha, Ali, Husnain, Chung, Tae Choong, Lee, Sungyoung

“…Clinical conversations between physicians and patients can provide a rich source of data, information, and knowledge. A plethora of tools and technologies have…”
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Frequency-based Data-driven Surrogate Model for Efficient Prediction of Irregular Structure's Seismic Responses by Dang-Vu, Hoang, Nguyen, Quang Dang, Chung, TaeChoong, Shin, Jiuk, Lee, Kihak

“…This research proposes a surrogate model to predict the seismic response of individual structural elements in structures whose inherent vertical and horizontal…”
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A practical approach towards causality mining in clinical text using active transfer learning by Hussain, Musarrat, Satti, Fahad Ahmed, Hussain, Jamil, Ali, Taqdir, Ali, Syed Imran, Bilal, Hafiz Syed Muhammad, Park, Gwang Hoon, Lee, Sungyoung, Chung, TaeChoong

“…[Display omitted] •Causality mining in clinical text is a difficult and time consuming task.•Traditional ML models are not able to provide acceptable…”
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Intelligent knowledge consolidation: From data to wisdom by Hussain, Musarrat, Satti, Fahad Ahmed, Ali, Syed Imran, Hussain, Jamil, Ali, Taqdir, Kim, Hun-Sung, Yoon, Kun-Ho, Chung, TaeChoong, Lee, Sungyoung

“…Knowledge based systems have accomplished remarkable achievements in assisting evidence based decision making for complex problems. However, machine…”
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Performance Analysis of LTE Smartphones-Based Vehicle-to-Infrastrcuture Communication by Abid, H., Tae Choong Chung, Sungyoung Lee, Qaisar, S.

“…With an increase in number of vehicles on road, applications and services offered by Intelligent Transportation System are growing in demand. However, there…”
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Constrained representation learning for recurrent policy optimisation under uncertainty by Dang, Viet-Hung, Vien, Ngo Anh, Chung, TaeChoong

“…Learning to make decisions in partially observable environments is a notorious problem that requires a complex representation of controllers. In most work, the…”
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A covariance matrix adaptation evolution strategy in reproducing kernel Hilbert space by Dang, Viet-Hung, Vien, Ngo Anh, Chung, TaeChoong

“…The covariance matrix adaptation evolution strategy (CMA-ES) is an efficient derivative-free optimization algorithm. It optimizes a black-box objective…”
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Asynchronous framework with Reptile+ algorithm to meta learn partially observable Markov decision process by Nguyen, Dang Quang, Vien, Ngo Anh, Dang, Viet-Hung, Chung, TaeChoong

“…Meta-learning has recently received much attention in a wide variety of deep reinforcement learning (DRL). In non-meta-learning, we have to train a deep neural…”
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B-Theta: an Efficient Online Coverage Algorithm for Autonomous Cleaning Robots by Choi, SeungYoon, Lee, SeungGwan, Viet, Hoang Huu, Chung, TaeChoong

“…We propose a novel approach to deal with the online complete-coverage task of cleaning robots in unknown workspaces with arbitrarily-shaped obstacles. Our…”
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A max-conflicts based heuristic search for the stable marriage problem with ties and incomplete lists by Viet, Hoang Huu, Uyen, Nguyen Thi, Lee, SeungGwan, Chung, TaeChoong, Trang, Le Hong

“…In this paper, we propose a heuristic search algorithm based on maximum conflicts to find a weakly stable matching of maximum size for the stable marriage…”
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Importance sampling policy gradient algorithms in reproducing kernel Hilbert space by Le, Tuyen Pham, Ngo, Vien Anh, Jaramillo, P. Marlith, Chung, TaeChoong

“…Modeling policies in reproducing kernel Hilbert space (RKHS) offers a very flexible and powerful new family of policy gradient algorithms called RKHS policy…”
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BoB: an online coverage approach for multi-robot systems by Viet, Hoang Huu, Dang, Viet-Hung, Choi, SeungYoon, Chung, Tae Choong

“…Online complete coverage is required in many applications, such as in floor cleaning, lawn mowing, mine hunting, and harvesting, and can be performed by…”
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Bayes-adaptive hierarchical MDPs by Vien, Ngo Anh, Lee, SeungGwan, Chung, TaeChoong

“…Reinforcement learning (RL) is an area of machine learning that is concerned with how an agent learns to make decisions sequentially in order to optimize a…”
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Toward Self-Driving Bicycles Using State-of-the-Art Deep Reinforcement Learning Algorithms by Choi, SeungYoon, Le, Tuyen, Nguyen, Quang, Layek, Md, Lee, SeungGwan, Chung, TaeChoong

“…In this paper, we propose a controller for a bicycle using the DDPG (Deep Deterministic Policy Gradient) algorithm, which is a state-of-the-art deep…”
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