Circuit complexity and neural networks: By Ian Parberry
نویسندگان
چکیده
منابع مشابه
Circuit Complexity and Feedforward Neural Networks
Circuit complexity, a subfield of computational complexity theory, can be used to analyze how the resource usage of neural networks scales with problem size. The computational complexity of discrete feedforward neural networks is surveyed, with a comparison of classical circuits to circuits constructed from gates that compute weighted majority functions.
متن کاملOn the Circuit Complexity of Neural Networks
K. Y. Sill Information Systems Laboratory Stanford University Stanford, CA, 94305 T. Kailath Informat.ion Systems Laboratory Stanford U ni versity Stanford, CA, 94305 '~le introduce a geometric approach for investigating the power of threshold circuits. Viewing n-variable boolean functions as vectors in 'R'2", we invoke tools from linear algebra and linear programming to derive new results on t...
متن کاملClasses of feedforward neural networks and their circuit complexity
-Th& paper aims to p&ce neural networks in the conte.\t ol'booh'an citz'ldt complexit.l: 1,1~, de/itte aplm~priate classes qlfeedybrward neural networks with specified fan-in, accm'ac)' olcomputation and depth and ttsing techniques" o./commzmication comph:¥ity proceed to show t/tat the classes.fit into a well-studied hieralz'h)' q/boolean circuits. Results cover both classes of sigmoid activati...
متن کاملPlacing Feedforward Neural Networks Among Several Circuit Complexity Classes
This paper examines the circuit complexity of feedforward neural networks having sigmoid activation function. The starting point is the complexity class NN defined in [18]. First two additional complexity classes NN∆ k and NN∆,ε k having less restrictive conditions (than NN) concerning fan-in and accuracy are defined. We then prove several relations among these three classes and well establishe...
متن کاملNeural Networks and Complexity Theory
We survey some of the central results in the complexity theory of discrete neural networks, with pointers to the literature.
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Complexity
سال: 1998
ISSN: 1076-2787,1099-0526
DOI: 10.1002/(sici)1099-0526(199803/04)3:4<59::aid-cplx11>3.0.co;2-o