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Recommender systems exploit interaction history to estimate user preference, having been heavily used in a wide range of industry applications. However, static recommendation models are difficult to answer two important questions well due…

Information Retrieval · Computer Science 2021-09-27 Chongming Gao , Wenqiang Lei , Xiangnan He , Maarten de Rijke , Tat-Seng Chua

Recommender systems are present in many web applications to guide our choices. They increase sales and benefit sellers, but whether they benefit customers by providing relevant products is questionable. Here we introduce a model to examine…

Computers and Society · Computer Science 2017-01-27 Chi Ho Yeung

In contemporary training for industrial manufacturing, reconciling theoretical knowledge with practical experience continues to be a significant difficulty. As companies transition to more intricate and technology-oriented settings,…

Human-Computer Interaction · Computer Science 2025-07-30 Vladislav Li , Ilias Siniosoglou , Panagiotis Sarigiannidis , Vasileios Argyriou

The use of relevant metrics of software systems could improve various software engineering tasks, but identifying relationships among metrics is not simple and can be very time consuming. Recommender systems can help with this…

Software Engineering · Computer Science 2018-01-23 Maral Azizi , Hyunsook Do

User simulators are essential for training reinforcement learning (RL) based dialog models. The performance of the simulator directly impacts the RL policy. However, building a good user simulator that models real user behaviors is…

Computation and Language · Computer Science 2019-09-05 Weiyan Shi , Kun Qian , Xuewei Wang , Zhou Yu

Complex system simulation has been playing an irreplaceable role in understanding, predicting, and controlling diverse complex systems. In the past few decades, the multi-scale simulation technique has drawn increasing attention for its…

Systems and Control · Electrical Eng. & Systems 2024-07-25 Huandong Wang , Huan Yan , Can Rong , Yuan Yuan , Fenyu Jiang , Zhenyu Han , Hongjie Sui , Depeng Jin , Yong Li

Repeated Sampling (RS) is a simple inference-time algorithm that has been shown to improve model performance on complex tasks. Although it is an effective way of scaling inference time, it often struggles to generate diverse solution…

Artificial Intelligence · Computer Science 2026-02-17 Divij Handa , Mihir Parmar , Aswin RRV , Md Nayem Uddin , Hamid Palangi , Chitta Baral

In the context of the evacuation of populations, some citizens/volunteers may want and be able to participate in the evacuation of populations in difficulty by coming to lend a hand to emergency/evacuation vehicles with their own vehicles.…

Information Retrieval · Computer Science 2023-06-05 Ngoc Luyen Le , Jinfeng Zhong , Elsa Negre , Marie-Hélène Abel

We present RecoWorld, a blueprint for building simulated environments tailored to agentic recommender systems. Such environments give agents a proper training space where they can learn from errors without impacting real users. RecoWorld…

Recommender systems are crucial tools to overcome the information overload brought about by the Internet. Rigorous tests are needed to establish to what extent sophisticated methods can improve the quality of the predictions. Here we…

Information Retrieval · Computer Science 2007-09-19 Marcel Blattner , Alexander Hunziker , Paolo Laureti

The design and analysis of systems that combine computational behaviour with physical processes' continuous dynamics - such as movement, velocity, and voltage - is a famous, challenging task. Several theoretical results from programming…

Systems and Control · Electrical Eng. & Systems 2024-11-22 Pedro Mendes , Ricardo Correia , Renato Neves , José Proença

In today's data-driven world, recommender systems (RS) play a crucial role to support the decision-making process. As users become continuously connected to the internet, they become less patient and less tolerant to obsolete…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-04-12 Heidy Hazem , Ahmed Awad , Ahmed Hassan

The information that mobiles can access becomes very wide nowadays, and the user is faced with a dilemma: there is an unlimited pool of information available to him but he is unable to find the exact information he is looking for. This is…

Information Retrieval · Computer Science 2013-05-09 Djallel Bouneffouf

Background: Requirement engineering is often considered a critical activity in system development projects. The increasing complexity of software, as well as number and heterogeneity of stakeholders, motivate the development of methods and…

In this paper, an attempt is made to systematically discuss the development of simulation systems for manufacturing system design. General requirements on manufacturing simulators are formulated and a framework to address the requirements…

Computational Engineering, Finance, and Science · Computer Science 2007-05-23 V. V. Kryssanov , V. A. Abramov , H. Hibino , Y. Fukuda

The globalization of markets and world-wide competition forces manufacturing enterprises to enter into alliances leading to the creation of distributed manufacturing enterprises. Before forming a partnership it is essential to evaluate…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-03-14 Sameh M. Saad , Terrence Perera , Ruwan Wickramarachchi

Existing Conversational Recommender Systems (CRS) predominantly utilize user simulators for training and evaluating recommendation policies. These simulators often oversimplify the complexity of user interactions by focusing solely on…

Information Retrieval · Computer Science 2024-09-10 Gangyi Zhang , Chongming Gao , Hang Pan , Runzhe Teng , Ruizhe Li

Currently, various hardware and software companies are developing augmented reality devices, most prominently Microsoft with its Hololens. Besides gaming, such devices can be used for serious pervasive applications, like interactive mobile…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-02-15 Christoph Dibak , Bernard Haasdonk , Andreas Schmidt , Frank Dürr , Kurt Rothermel

Due to decelerating gains in single-core CPU performance, computationally expensive simulations are increasingly executed on highly parallel hardware platforms. Agent-based simulations, where simulated entities act with a certain degree of…

Multiagent Systems · Computer Science 2018-07-04 Jiajian Xiao , Philipp Andelfinger , David Eckhoff , Wentong Cai , Alois Knoll

Simulation is a useful tool in situations where training data for machine learning models is costly to annotate or even hard to acquire. In this work, we propose a reinforcement learning-based method for automatically adjusting the…

Machine Learning · Computer Science 2019-05-15 Nataniel Ruiz , Samuel Schulter , Manmohan Chandraker
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