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关键词： Computational neuroscience   Computer science   Learning and memory   Olfactory system  

摘要： Keeping track of the number of times different stimuli have been experienced is a critical computation for behavior. Here, we propose a theoretical two-layer neural circuit that stores counts of stimulus occurrence frequencies. This circuit implements a data structure, called a count sketch, that is commonly used in computer science to maintain item frequencies in streaming data. Our first model implements a count sketch using Hebbian synapses and outputs stimulus-specific frequencies. Our second model uses anti-Hebbian plasticity and only tracks frequencies within four count categories ("1-2-3-many"), which trades-off the number of categories that need to be distinguished with the potential ethological value of those categories. We show how both models can robustly track stimulus occurrence frequencies, thus expanding the traditional novelty-familiarity memory axis from binary to discrete with more than two possible values. Finally, we show that an implementation of the "1-2-3-many" count sketch exists in the insect mushroom body.

关键词： Applied mathematics   Computer science  

摘要： Improving the efficiency of algorithms for fundamental computations can have a widespread impact, as it can affect the overall speed of a large amount of computations. Matrix multiplication is one such primitive task, occurring in many systems-from neural networks to scientific computing routines. The automatic discovery of algorithms using machine learning offers the prospect of reaching beyond human intuition and outperforming the current best human-designed algorithms. However, automating the algorithm discovery procedure is intricate, as the space of possible algorithms is enormous. Here we report a deep reinforcement learning approach based on AlphaZero(1) for discovering efficient and provably correct algorithms for the multiplication of arbitrary matrices. Our agent, AlphaTensor, is trained to play a single-player game where the objective is finding tensor decompositions within a finite factor space. AlphaTensor discovered algorithms that outperform the state-of-the-art complexity for many matrix sizes. Particularly relevant is the case of 4 x 4 matrices in a finite field, where AlphaTensor's algorithm improves on Strassen's two-level algorithm for the first time, to our knowledge, since its discovery 50 years ago(2). We further showcase the flexibility of AlphaTensor through different use-cases: algorithms with state-of-the-art complexity for structured matrix multiplication and improved practical efficiency by optimizing matrix multiplication for runtime on specific hardware. Our results highlight AlphaTensor's ability to accelerate the process of algorithmic discovery on a range of problems, and to optimize for different criteria.

关键词： Complex networks   Computer science   Information theory and computation   Optoelectronic devices and components  

摘要： Ising machines are a promising non-von-Neumann computational concept for neural network training and combinatorial optimization. However, while various neural networks can be implemented with Ising machines, their inability to perform fast statistical sampling makes them inefficient for training neural networks compared to digital computers. Here, we introduce a universal concept to achieve ultrafast statistical sampling with analog Isingmachines by injecting noise. With an opto-electronic Ising machine, we experimentally demonstrate that this can be used for accurate sampling of Boltzmann distributions and for unsupervised training of neural networks, with equal accuracy as software-based training. Through simulations, we find that Ising machines can perform statistical sampling orders-of-magnitudes faster than software-based methods. This enables the use of Ising machines beyond combinatorial optimization and makes them into efficient tools for machine learning and other applications.

摘要： An existing undergraduate computer science curriculum was augmented with activities that address diversity, equity, and inclusion (DEI) in the discipline and associated professions. The effort was part of a larger project (Partnership for Equity:STEM) that seeks to cultivate inclusive professional identities in engineering and computer science students through curricular design. The development and implementation of such a curricular activity, used successfully in introductory computer science courses, is described along with qualitative analyses of student responses. The experience also revealed that inherent differences among institutions and across disciplines represent significant impediments to the transferability of curricular activities and the conduct of research in broader contexts.

关键词： 共青团   科技创新   创新创业   人才培养   实践基地   基层团建  

摘要： 创新是一个民族进步的灵魂,是国家持续发展的不竭动力。高校是科技创新的重要源头,是科技创新人才培养的主要力量。该文在分析大学生科技创新人才培养的意义、原则的基础上,提出了“科技创新+”的创新人才培养途径,将“专业”“社团”“赛事”“基地”四大元素与创新人才培养相融合,对创新人才培养体系赋能,并提出了思想引领、团建帮扶、以理想信念筑牢基地育人成效等创新点。

关键词： Ecosystems   Guidelines   Semantics   Runtime   Tools   Computer science   Computer bugs   Dependency smells   software ecosystems   dependency management   npm  

摘要： Dependency management in modern software development poses many challenges for developers who wish to stay up to date with the latest features and fixes whilst ensuring backwards compatibility. Project maintainers have opted for varied, and sometimes conflicting, approaches for maintaining their dependencies. Opting for unsuitable approaches can introduce bugs and vulnerabilities into the project, introduce breaking changes, cause extraneous installations, and reduce dependency understandability, making it harder for others to contribute effectively. In this paper, we empirically examine evidence of recurring dependency management issues (dependency smells). We look at the commit data for a dataset of 1,146 active JavaScript repositories to catalog, quantify and understand dependency smells. Through a series of surveys with practitioners, we identify and quantify seven dependency smells with varying degrees of popularity and investigate why they are introduced throughout project history. Our findings indicate that dependency smells are prevalent in JavaScript projects with two or more distinct smells appearing in 80 percent of the projects, but they generally infect a minority of a project's dependencies. Our observations show that the number of dependency smells tend to increase over time. Practitioners agree that dependency smells bring about many problems including security threats, bugs, dependency breakage, runtime errors, and other maintenance issues. These smells are generally introduced as developers react to dependency misbehaviour and the shortcomings of the npm ecosystem.

关键词： 科学-技术交叉   专利分析   学科发展   行业高校   文献计量学  

摘要： 本文基于科学-技术交叉视角对国内四所电子特色高校的计算机科学学科发展情况展开研究。通过对四所高校ESI论文与专利文献的年度产出、成果学科分布、基金支持、影响力、国际与校企合作、研究热点与趋势进行文献计量分析并开展学科发展情况的比较分析。研究发现,作为学校的特色学科,从高水平成果数量和比重、成果被引率、基金资助率、国际合作率等各项指标看,各校计算机学科均达到了较高的研究水准。各校基于实际办学情况,在深度学习、云计算、无线网络等基础理论研究领域以及数字信息传输等技术研发方向,基础科学研究和应用技术创新方面各具所长,走出了跨界交融、专精特色的发展道路。