Titlebook: ;

pulse-pressure

An Improved Artificial Bee Colony Algorithm with Multiple Search Strategy. To solve the problem that ABC algorithm is easy to fall into local optimum, this paper proposes an Improved Artificial Bee Colony (IABC) algorithm with multiple search strategy. An opposition-based learning technique is integrated in initialization phase. Then, in order to speed up convergence rat

跑過

An Efficient Data Prefetch Strategy for Deep Learning Based on Non-volatile Memoryisk to DRAM is still limited by disk performance. The emerging . (NVRAM) provides a novel solution for this problem, while few existing researches have considered it. We propose a novel efficient data prefetch strategy for DL based on a heterogeneous memory system combining NVRAM with DRAM. Benefitt

frugal

半導(dǎo)體

Dictation

APEX

Echo State Network Based on L0 Norm Regularization for Chaotic Time Series Predictione the gradient-based problem of most recurrent neural networks in the training process. However, there may be an ill-posed problem when the least square method is used to calculate the output weight. In this paper, we proposed an echo state network based on L. norm regularization. The main idea is t

jeopardize

cornucopia

MGCN4REC: Multi-graph Convolutional Network for Next Basket Recommendation with Instant Interestt item-level preferences. The existing works often combine the long-and short-term patterns to capture user’s preferences. But the short-term preferences modeled by the recent behavior patterns cannot clearly indicate the users’ instant interest. In this paper, we propose a sequential recommendation

galley

Using Deep Active Learning to Save Sensing Cost When Estimating Overall Air Quality the stations are actuated at partial time. Therefore, it is necessary to study how to actively collect a subset of air quality data to maximize the estimation accuracy of air quality at other locations and time. In order to solve this challenge, we propose the active variational adversarial model (

dialect