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关键词： Learning systems   Training   Neural networks   High frequency   Computer science   Time series analysis   Task analysis   Broad learning system (BLS)   Fourier analysis   frequency principle   incremental learning  

摘要： Deep neural networks have achieved breakthrough improvement in various application fields. Nevertheless, they usually suffer from a time-consuming training process because of the complicated structures of neural networks with a huge number of parameters. As an alternative, a fast and efficient discriminative broad learning system (BLS) is proposed, which takes the advantages of flat structure and incremental learning. The BLS has achieved outstanding performance in classification and regression problems. However, the previous studies ignored the reason why the BLS can generalize well. In this article, we focus on the interpretation from the viewpoint of the frequency domain. We discover the existence of the frequency principle in BLS, i.e., the BLS preferentially captures low-frequency components quickly and then fits the high frequencies during the incremental process of adding feature nodes and enhancement nodes. The frequency principle may be of great inspiration for expanding the application of BLS.

关键词： death penalty   Herod Antipas   Herodias   John the Baptist   Julius Jones   Mark 6:14-29  

摘要： The story of John the Baptist's execution in Mark 6:14-29 has intrigued artists and biblical interpreters alike. The daughter's dance, Herodias's grudge, and Herod's impulsive oath have proven to be fertile ground to speculate on internal motivations and private conversations absent from the Markan account. The daughter has been blamed for John's death because her erotic dancing tricked Herod into making his promise. Herodias gets blamed for orchestrating the events of the banquet that lead to John's death. Herod gets blamed for losing control of himself and making an oath without considering the implications. This article reconsiders this scene with attention to the function of the dinner guests who legitimate Herod's authority, thereby implicating them as much as anyone else in John's death. Furthermore, John's execution is compared with the commutation of Julius Jones's death sentence in Oklahoma in 2021 to highlight the role of the public in determining the exertion of power.

关键词： 6 G Mobile Communication   Machine Learning   Mathematics   Learning Systems   Computer Science   Agile   Software Engineering   Machine Learning   ML Enabled Systems   Development Methodology  

摘要： Increased adoption of machine learning (ML) in business has led to a surge in ML-enabled systems in the market giving rise to new challenges. This article provides insights into Agile4MLS, highlighting the challenges we faced and the process we followed.

关键词： 21st century abilities   distance education and online learning   learning communities   social media  

摘要： Live streaming platforms like *** count millions of viewers and performers, pointing to novel practices and interactions. Instructional applications of this phenomenon are rising with thematic channels and shows aimed at teaching and debating a variety of subjects ranging from art to programming. However, few research publications have specifically explored trends in pedagogical strategies and learning behaviours of viewing audiences. This study responded to this need by analysing computer science shows on ***. A total of 40 hours of live streaming were analysed within a Community of Inquiry framework using the concepts of social affordances, computational thinking, and teaching style. Data collected from both expert and novice streamers included streamers' actions, on-screen activity, and online discussions. Results pointed to specific tactics employed by both performers and viewers for exploring computer science issues and dynamics together, with instances of peer-tutoring, construed learning, and significant transparency, even when top-down instruction was staged. Practitioners notes What is already known about this topic Live streaming is a popular media practice all around the world, with *** as the leading hosting platform. A rising number of live streaming shows are focusing on education and learning topics, from STEM to art. What this paper adds A first exploration of instructional streaming focused on computer science education. An analysis of best practices in instructional streaming in terms of community building, teaching style, and computational thinking processes. A better understanding of how communities of inquiry can be hosted on ***. Implications for practice and/or policy Practitioners can harness this study's results for informing better educational streaming. Educators may refer to this article's highlights for selecting and evaluating educational streaming shows. Policy makers will be able to use this article's insights

关键词： Impact prediction   h-index   Gender   Discrimination   Machine learning  

摘要： The advent of large-scale bibliographic databases and powerful prediction algorithms led to calls for data-driven approaches for targeting scarce funds at researchers with high predicted future scientific impact. The potential side-effects and fairness implications of such approaches are unknown, however. Using a large-scale bibliographic data set of N = 111,156 Computer Science researchers active from 1993 to 2016, I build and evaluate a realistic scientific impact prediction model. Given the persistent under-representation of women in Computer Science, the model is audited for disparate impact based on gender. Random forests and Gradient Boosting Machines are used to predict researchers' h-index in 2010 from their bibliographic profiles in 2005. Based on model predictions, it is determined whether the researcher will become a high-performer with an h-index in the top-25% of the discipline-specific h-index distribution. The models predict the future h-index with an accuracy of R-2 = 0.875 and correctly classify 91.0% of researchers as high-performers and low-performers. Overall accuracy does not vary strongly across researcher gender. Nevertheless, there is indication of disparate impact against women. The models underestimate the true h-index of female researchers more strongly than the h-index of male researchers. Further, women are 8.6% less likely to be predicted to become high-performers than men. In practice, hiring, tenure, and funding decisions that are based on model predictions risk to perpetuate the under-representation of women in Computer Science.

摘要： No abstract available.

关键词： Recommender systems   Reinforcement learning   Cybernetics   Computer science   Cats   Training   Research and development   Deep reinforcement learning (DRL)   hierarchy   large action space   recommender system  

摘要： Deep reinforcement learning (DRL)-based recommender systems have recently come into the limelight due to their ability to optimize long-term user engagement. A significant challenge in DRL-based recommender systems is the large action space required to represent a variety of items. The large action space weakens the sampling efficiency and thereby, affects the recommendation accuracy. In this article, we propose a DRL-based method called deep hierarchical category-based recommender system (DHCRS) to handle the large action space problem. In DHCRS, categories of items are used to reconstruct the original flat action space into a two-level category-item hierarchy. DHCRS uses two deep Q-networks (DQNs): 1) a high-level DQN for selecting a category and 2) a low-level DQN to choose an item in this category for the recommendation. Hence, the action space of each DQN is significantly reduced. Furthermore, the categorization of items helps capture the users' preferences more effectively. We also propose a bidirectional category selection (BCS) technique, which explicitly considers the category-item relationships. The experiments show that DHCRS can significantly outperform state-of-the-art methods in terms of hit rate and normalized discounted cumulative gain for long-term recommendations.

关键词： environmental destruction   dreams   collective unconscious   Jewish myth   'borderland' personality   sandplay  

摘要： The author, although an analyst, is an initiate into the topic of environmental destruction. Following Wendell Berry, she enters the dark and begins a journey of dream-like reflection, weaving images from her own dream and drawing on the work of Vaughan, Bernstein, Soloveitchik and Sacks. She asks, 'not if but where does climate change enter the room?'. The second half of the paper focuses on the manifestations of environmental destruction in dreams and sandplay from three patients and one dream group participant. The paper argues that the analyst must see and intuit before our patients can access the objective layer of environmental destruction in dreams and symbolic material. In this way, the climate becomes the wounded patient, and the analyst as wounded healer must first access his/her own relationship to the wounds inside. Finally, using an ancient Jewish mythological story of Rabbi Shimon bar Yochai, the author argues that Jungian analysts must work to find balance between the inner world of depth psychology and the outer world with its challenges and problems that include environmental destruction.

关键词： Resource management   Ash   Interference   Bandwidth   Virtualization   Parallel architectures   Computer science   Multitenant   over-provisioning space (OPS)   solid-state drives (SSDs)   virtualization   workload characteristic  

摘要： Sharing a flash-based solid-state drive (SSD) among multiple tenants has become a common practice to improve storage utilization and cost efficiency. Meanwhile, how to allocate limited storage resources, especially the over-provisioning space (OPS) resources, among competitive tenants has emerged as a critical problem. The OPS refers to additional user-invisible storage space, whose size influences garbage collection (GC) efficiency. Due to unawareness of workload characteristics of different tenants, prior studies on multitenant OPS allocation lead to suboptimal SSD performance. In this article, we propose a novel workload-adaptive OPS allocation scheme for multitenant SSDs, called WA-OPShare. It targets an OPS sharing scheme that dynamically allocates the OPS among tenants to improve overall SSD performance. Two models are developed to identify underutilized storage space and predict the OPS-induced performance benefit of each tenant, respectively. Guided by the models, WA-OPShare regularly releases the underutilized storage space and then reallocates it to the tenant who can benefit the most. Experimental results show that compared to the traditional Partition and Sharing schemes, WA-OPShare improves the performance by up to 40.3% and 31.2%, and reduces the write amplification by up to 37.0% and 17.5%, respectively.

关键词： Neurons   Biological neural networks   Safety   Robustness   Input variables   Computer science   Venus   Abstract analysis   complete verification   input refinement   input splitting   neural network verification  

摘要： Safety and robustness properties are highly required for neural networks deployed in safety-critical applications. Current complete verification techniques of these properties suffer from the lack of efficiency and effectiveness. In this article, we present an efficient complete approach to verify safety and robustness properties of neural networks through incrementally determinizing activation states of neurons. The key idea is to generate constraints via layerwised splitting that make activation states of hidden neurons become deterministic efficiently. These constraints are then utilized for refining inputs systematically so that abstract analysis over the refined input can be more precise. Our approach decomposes a verification problem into a set of subproblems via layerwised input space splitting. The property is then checked on each subproblem, where the activation states of at least one hidden neurons will be determinized. Further checking is accelerated by constraint-guided input refinement. We have implemented a parallel tool called LayerSAR to verify safety and robustness properties of ReLU neural networks in a sound and complete way, and evaluated it extensively on several benchmark sets. Experimental results show that our approach is promising, compared with complete tools, such as Planet, Neurify, Marabou, ERAN, Venus, Venus2, and nnenum in verifying safety and robustness properties on the benchmarks.