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Decomposed intrinsic mode functions and deep learning algorithms for water quality index forecasting
The water quality index (WQI) serves as a global representation of river water quality (WQ). Existing studies related to the WQI have mainly focused...
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Assimilating human feedback from autonomous vehicle interaction in reinforcement learning models
A significant challenge for real-world automated vehicles (AVs) is their interaction with human pedestrians. This paper develops a methodology to...
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Decomposed Prompting to Answer Questions on a Course Discussion Board
We propose and evaluate a question-answering system that uses decomposed prompting to classify and answer student questions on a course discussion...
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Rethinking AI code generation: a one-shot correction approach based on user feedback
Code generation has become an integral feature of modern IDEs, gathering significant attention. Notable approaches like GitHub Copilot and TabNine...
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Accurate and fast congestion feedback in MEC-enabled RDMA datacenters
Mobile edge computing (MEC) is a novel computing paradigm that pushes computation and storage resources to the edge of the network. The...
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Improving GP-UCB Algorithm by Harnessing Decomposed Feedback
Gaussian processes (GPs) have been widely applied to machine learning and nonparametric approximation. Given existing observations, a GP allows the...
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Specifying requirements for collection and analysis of online user feedback
According to data-driven Requirements Engineering (RE), explicit and implicit user feedback can be considered a relevant source of requirements, thus...
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SRFFNet: Self-refine, Fusion and Feedback for Salient Object Detection
Many existing salient object detection models have achieved excellent results by fusing the progressive multi-layer features extracted by the...
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Optimal clustering from noisy binary feedback
We study the problem of clustering a set of items from binary user feedback. Such a problem arises in crowdsourcing platforms solving large-scale...
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Multi-scale error feedback network for low-light image enhancement
Low-light image enhancement is a challenging task because brightness, contrast, noise and other factors must be considered simultaneously. However,...
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A graph-based collaborative filtering algorithm combining implicit user preference and explicit time-related feedback
Collaborative filtering is one of the most extensively utilized recommendation algorithms in the e-commerce industry. It typically relies either on...
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Impact of combining human and analytics feedback on students’ engagement with, and performance in, reflective writing tasks
Reflective writing is part of many higher education courses across the globe. It is often considered a challenging task for students as it requires...
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A variable memory state feedback and its application to robust control of uncertain singular time-delay systems
This paper is focused on the robust control of uncertain singular time-delay systems. The systems are firstly decomposed to differential-algebraic...
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Joint feedback and recurrent deraining network with ensemble learning
Rainy images typically contain heterogeneous rain distributions; however, many existing methods perform well in simple homogeneous rain and fail to...
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Computing a Feedback Arc Set Using PageRank
We present a new heuristic algorithm for computing a minimum Feedback Arc Set in directed graphs. The new technique produces solutions that are...
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Composite Emotion Recognition and Feedback of Social Assistive Robot for Elderly People
As the world’s population ages, the issue of medical care and daily care for the elderly population is becoming more and more critical. While there...
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Modulation of Beta Power as a Function of Attachment Style and Feedback Valence
Attachment theory is concerned with the basic level of social connection associated with approach and withdrawal mechanisms. Consistent patterns of...
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A zeroing feedback gradient-based neural dynamics model for solving dynamic quadratic programming problems with linear equation constraints in finite time
Gradient-based neural dynamics (GND) models are a classical algorithm for solving optimization problems, but it has non-negligible flaws in solving...
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Dynamic vehicle pose estimation and tracking based on motion feedback for LiDARs
This paper presents a novel dynamic vehicle tracking framework, achieving accurate pose estimation and tracking in urban environments. For vehicle...
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Variational learning from implicit bandit feedback
Recommendations are prevalent in Web applications (e.g., search ranking, item recommendation, advertisement placement). Learning from bandit feedback...
