Computational statisticsComputational statistics, or statistical computing, is the bond between statistics and computer science. It means statistical methods that are enabled by using computational methods. It is the area of computational science (or scientific computing) specific to the mathematical science of statistics. This area is also developing rapidly, leading to calls that a broader concept of computing should be taught as part of general statistical education.
Shor's algorithmShor's algorithm is a quantum algorithm for finding the prime factors of an integer. It was developed in 1994 by the American mathematician Peter Shor. It is one of the few known quantum algorithms with compelling potential applications and strong evidence of superpolynomial speedup compared to best known classical (that is, non-quantum) algorithms. On the other hand, factoring numbers of practical significance requires far more qubits than available in the near future.
Foreign policyA state's foreign policy or external policy (as opposed to internal or domestic policy) is its objectives and activities in relation to its interactions with other states, unions, and other political entities, whether bilaterally or through multilateral platforms. The Encyclopedia Britannica notes that a government's foreign policy may be influenced by "domestic considerations, the policies or behaviour of other states, or plans to advance specific geopolitical designs.
Lifelong learningLifelong learning is the "ongoing, voluntary, and self-motivated" pursuit of knowledge for either personal or professional reasons. It is important for an individual's competitiveness and employability, but also enhances social inclusion, active citizenship, and personal development. In some contexts, the term "lifelong learning" evolved from the term "life-long learners", created by Leslie Watkins and used by Clint Taylor, professor at CSULA and Superintendent for the Temple City Unified School District, in the district's mission statement in 1993, the term recognizes that learning is not confined to childhood or the classroom but takes place throughout life and in a range of situations.
Computational anatomyComputational anatomy is an interdisciplinary field of biology focused on quantitative investigation and modelling of anatomical shapes variability. It involves the development and application of mathematical, statistical and data-analytical methods for modelling and simulation of biological structures. The field is broadly defined and includes foundations in anatomy, applied mathematics and pure mathematics, machine learning, computational mechanics, computational science, biological imaging, neuroscience, physics, probability, and statistics; it also has strong connections with fluid mechanics and geometric mechanics.
Computational complexityIn computer science, the computational complexity or simply complexity of an algorithm is the amount of resources required to run it. Particular focus is given to computation time (generally measured by the number of needed elementary operations) and memory storage requirements. The complexity of a problem is the complexity of the best algorithms that allow solving the problem. The study of the complexity of explicitly given algorithms is called analysis of algorithms, while the study of the complexity of problems is called computational complexity theory.
Learning to rankLearning to rank or machine-learned ranking (MLR) is the application of machine learning, typically supervised, semi-supervised or reinforcement learning, in the construction of ranking models for information retrieval systems. Training data consists of lists of items with some partial order specified between items in each list. This order is typically induced by giving a numerical or ordinal score or a binary judgment (e.g. "relevant" or "not relevant") for each item.
Sample-return missionA sample-return mission is a spacecraft mission to collect and return samples from an extraterrestrial location to Earth for analysis. Sample-return missions may bring back merely atoms and molecules or a deposit of complex compounds such as loose material and rocks. These samples may be obtained in a number of ways, such as soil and rock excavation or a collector array used for capturing particles of solar wind or cometary debris. Nonetheless, concerns have been raised that the return of such samples to planet Earth may endanger Earth itself.
Mars sample-return missionA Mars sample-return (MSR) mission is a proposed mission to collect rock and dust samples on Mars and return them to Earth. Such a mission would allow more extensive analysis than that allowed by onboard sensors. The three most recent concepts are a NASA-ESA proposal, a CNSA proposal, Tianwen-3, and a Roscosmos proposal, Mars-Grunt. Although NASA and ESA's plans to return the samples to Earth are still in the design stage as of 2022, samples have been gathered on Mars by the Perseverance rover.
