Titlebook: Innovation Networks; Concepts and Challen Knut Koschatzky,Marianne Kulicke,Andrea Zenker Conference proceedings 2001 Springer-Verlag Berlin

Highbrow

Günter H. Walter constraint contrastive learning (Inter-CCL) objective to effectively enlarge the discrepancy among different classes as much as possible, enforcing the strong separability for different classes in the intent embedding space. Besides, to further enhance the discriminative representation capability o

Consequence

Knut Koschatzky,Ulrike Brossreduce training time through adaptive parameters update algorithm which dynamically changes learning time for various objects. (4) We speed up the computation and enhance scalability by fast Fourier transform (FFT). Extensive experiments show that CirE outperforms state-of-the-art baselines in link

BLUSH

Slavo Radosevic) Events are detected accurately on category-level word time series, due to richer semantics and less noise. (4) Experiment verifies the quality of category-level topics extracted from knowledge base, and the further study on the benchmark . validates the effectiveness of our proposed transfer learn

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未開(kāi)化

Marianne Kulickewhich can provide a good load balancing for query processing by using . to capture data distribution. Analysis of theoretical and experimental results on standard benchmark illustrate the efficacy of the proposed methods in a distributed environment.

CURB

which can provide a good load balancing for query processing by using . to capture data distribution. Analysis of theoretical and experimental results on standard benchmark illustrate the efficacy of the proposed methods in a distributed environment.

escalate

Herbert Berteitions, thus improving the accuracy of the location estimation models. A confidence iteration method is further introduced to improve estimation accuracy and overcome the problem of scarce location information. We evaluate our methods on two different datasets, Twitter and Gowalla. The results show th

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