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In computational complexity theory, P and NP are two classes of problems. P is the class of decision problems that a deterministic Turing machine can solve in polynomial time. In useful terms, any ...

SFI Complexity Postdoctoral Fellow Kaleda Denton was among roughly 30 early-career researchers selected to participate in the ...

The computational complexity of voting systems examines the algorithmic effort required to determine outcomes, resist strategic interventions and safeguard democratic processes. Central to this field ...

The historical pursuit of creating intelligent machines has culminated in the modern era of artificial intelligence. However, the efficacy of AI applications is contingent upon a nuanced understanding ...

A major advance reveals deep connections between the classes of problems that computers can — and can’t — possibly do. At first glance, the big news coming out of this summer’s conference on the ...

Our research area encompasses the study of computation, computational models, computational complexity, algorithm design, algorithm verification, combinatorial optimization, computational biology and ...

Computational neuroscientists taught an artificial neural network to imitate a biological neuron. The result offers a new way to think about the complexity of single brain cells. Our mushy brains seem ...

A new study proves individual human cortical neurons have the computational complexity of an entire deep artificial neural ...