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281
Double‐shelled nanostructure of SnO2@C tube‐in‐SnO2@C tube boosts lithium‐ion storage
Published 2021Get full text
Journal Article -
282
Learning on heterogeneous graphs using high-order relations
Published 2021Get full text
Conference Paper -
283
A data-driven bottom-up approach for spatial and temporal electric load forecasting
Published 2021Get full text
Journal Article -
284
Robust pricing and production with information partitioning and adaptation
Published 2022Get full text
Journal Article -
285
Robust semi-supervised nonnegative matrix factorization for image clustering
Published 2022Get full text
Journal Article -
286
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287
Initial public offering : voluntary disclosure and its effect on United States IPOs.
Published 2011Get full text
Final Year Project (FYP) -
288
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289
Mental accounting and its impact on outbound leisure traveler’s overspending Behavior.
Published 2013Get full text
Final Year Project (FYP) -
290
Banking behaviour of expatriate lecturers in Singapore.
Published 2013Get full text
Final Year Project (FYP) -
291
Factors influencing market entry modes for outward Hong Kong foreign direct investments.
Published 2008Get full text
Final Year Project (FYP) -
292
Investigation of nonlinear ultrasonic guided waves in open waveguides based on perfectly matched layers
Published 2018Get full text
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Journal Article -
293
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294
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295
Solution of dusty flow past a vertical plate /
Published 2015“…Project Paper (Sarjana Muda Sains serta Pendidikan (Matematik)) - Universiti Teknologi Malaysia, 2015…”
text -
296
The structural and optical properties of neodymium doped lithium niobate and yttrium aluminum garnet single crystals [electronic resource] /
Published 2015“…Thesis (Sarjana Sains (Fizik))…”
text -
297
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298
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299
Cross-Modal Deep Variational Hashing
Published 2017“…Unlike most existing cross-modal hashing methods which learn a single pair of projections to map each example into a binary vector, we design a deep fusion neural network to learn non-linear transformations from image-text input pairs, such that a unified binary code is achieved in a discrete and discriminative manner using a classification-based hinge-loss criterion. We then design modality-specific neural networks in a probabilistic manner such that we model a latent variable to be close as possible from the inferred binary codes, at the same time approximated by a posterior distribution regularized by a known prior, which is suitable for out-of-sample extension. …”
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Conference Paper -
300