Computer Sciences

HAMLET: A platform to simplify AI research and development

Machine learning (ML) algorithms have proved to be highly valuable computational tools for tackling a variety of real-world problems, including image, audio and text classification tasks. Computer scientists worldwide are ...

Software

New tool detects unsafe security practices in Android apps

Computer scientists at Columbia Engineering have shown for the first time that it is possible to analyze how thousands of Android apps use cryptography without needing to have the apps' actual codes. The team's new tool, ...

Computer Sciences

When algorithms compete, who wins?

Over time, prediction algorithms become specialized for an increasingly narrow slice of the population, and the average quality of their predictions declines.

Computer Sciences

A machine leaning model that incorporates immunological knowledge

The complex network of interconnected cellular signals produced in response to changes in the human body offers a vast amount of interesting and valuable insight that could inform the development of more effective medical ...

Robotics

Researchers improve autonomous boat design

The feverish race to produce the shiniest, safest, speediest self-driving car has spilled over into our wheelchairs, scooters, and even golf carts. Recently, there's been movement from land to sea, as marine autonomy stands ...

Robotics

AI improves control of robot arms

More than one million American adults use wheelchairs fitted with robot arms to help them perform everyday tasks such as dressing, brushing their teeth, and eating. But the robotic devices now on the market can be hard to ...

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Algorithm

In mathematics, computing, linguistics, and related subjects, an algorithm is a finite sequence of instructions, an explicit, step-by-step procedure for solving a problem, often used for calculation and data processing. It is formally a type of effective method in which a list of well-defined instructions for completing a task, will when given an initial state, proceed through a well-defined series of successive states, eventually terminating in an end-state. The transition from one state to the next is not necessarily deterministic; some algorithms, known as probabilistic algorithms, incorporate randomness.

A partial formalization of the concept began with attempts to solve the Entscheidungsproblem (the "decision problem") posed by David Hilbert in 1928. Subsequent formalizations were framed as attempts to define "effective calculability" (Kleene 1943:274) or "effective method" (Rosser 1939:225); those formalizations included the Gödel-Herbrand-Kleene recursive functions of 1930, 1934 and 1935, Alonzo Church's lambda calculus of 1936, Emil Post's "Formulation 1" of 1936, and Alan Turing's Turing machines of 1936–7 and 1939.

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