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& Oja, E. A fast fixed-point algorithm for independent component analysis. Neural Comput. 9, 1483–1492 (1997). Article Google Scholar Hyvärinen, A. & Oja, E. Independent component analysis: Algorithms and applications. Neural Net. 13, 411–430 (2000). Article Google Scholar Foldiak,...
Many real-world engineering problems need to balance different objectives and can be formatted as multi-objective optimization problem. An effective multi-objective algorithm can achieve a set of optimal solutions that can make a tradeoff between differe
We introduce a novel multivariate approach for solving weighted parameterized problems. Our framework yields fast algorithms whose running times are of the form O⁎(cs). We demonstrate its usefulness for the following problems. • WVC: We give an algorithm that uses O⁎(1.381s) time and po...
The most popular federated algorithm is Federated Averaging (FedAvg) [11]. There are some key components in standard federated settings. The parameters w∈W of the model are initialized on the server, so that every participant i∈{1,…,n}=N starts the training stage at a common point. ...
A fast, multi-language, multi-precision fixed-point library! Key Features Deterministic: Operations produce bit-identical results across languages and compilers Fast: All operations use efficient algorithms and are highly optimized Multi-Language: Supports C#, Java, and C++ Multiple Types: Supports sign...
What if there were a consensus algorithm we could actually understand? Paxos approaches independent decisions when what we want is state machines Maintains a replicated log of state machine transitions instead Also builds in cluster membership transitions, which is key for real systems Very new, ...
the most objectionable artifacts due to depth discontinuities are only really solved by avoiding those cases in which they occur (that is, when the focal plane is far into the scene), which limits the utility of the algorithm for general purposes but is good enough for many real-ti...
Fast and robust fixed-point algorithms for independent component analysis. IEEE Trans. Neural Netw. 1999, 10, 626–634. [Google Scholar] [CrossRef] [PubMed] [Green Version] Immanuvel, A.; Suganthi, M. Performance Analysis of Low Power Channel Estimator for Multi User MIMO-OFDM System. ...
surface at every iteration of the surface particle simulation. Therefore, for each particle, the GPU randomly selects a comparison particle in the pool everytseconds, by using a texture with random values generated on the CPU. The value oftcan be chosen arbitrarily. Here is the alg...