Mu (em-power-you) : a jewelry brand inspired by the stories of different communities by Cho, Cecilia Hyunjae

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The city you'll never meet by Lim, Ying Quan

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Soulvurn by Tan, Sherneese

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Ig.n.is. by Ong, Jian'an.

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Singapore premiere. by Ong, Shannon.

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Plateau by Png, Hui Min, Goh Timothy Wei Wen

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Towards optimal scheduling of deep learning training jobs in GPU clusters by Gao, Wei

“…Second, it reuses the fine-tuning runtime of FMF workloads to reduce the significant context switch overhead. …”
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Examples out of Thin Air: AI-Generated Dynamic Context to Assist Program Comprehension by Example by Mattis, Toni, Krebs, Eva, Rinard, Martin C., Hirschfeld, Robert

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A cup of coffee by Yong, Kai Ting

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Supercreative : unleashing creative potential. by Chee, Edison.

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Umbrella by Khoo, Siew May

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One more minute by Liew, Ming Jia

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Image retrieval with deep learning by Tan, Joe Chin Yong

“…Actions can be done to fine-tune the feature extractor with distorted images to see whether it will be more resilient to these distortion methods. …”
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Astray by Tan, Ken Wei Hao

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A book is a body by Goh, Su-Lynn

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Mental-LLM: Leveraging Large Language Models for Mental Health Prediction via Online Text Data by Xu, Xuhai, Yao, Bingsheng, Dong, Yuanzhe, Gabriel, Saadia, Yu, Hong, Hendler, James, Ghassemi, Marzyeh, Dey, Anind K., Wang, Dakuo

“…We conduct a broad range of experiments, covering zero-shot prompting, few-shot prompting, and instruction fine-tuning. The results indicate a promising yet limited performance of LLMs with zero-shot and few-shot prompt designs for mental health tasks. …”
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0-1 Knapsack in Nearly Quadratic Time by Jin, Ce

“…Our algorithm combines and extends several recent structural results and algorithmic techniques from the literature on knapsacktype problems: (1) We generalize the “fine-grained proximity” technique of Chen, Lian, Mao, and Zhang (2023) derived from the additivecombinatorial results of Bringmann and Wellnitz (2021) on dense subset sums. …”
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Dominant contribution of oxygenated organic aerosol to haze particles from real-time observation in Singapore during an Indonesian wildfire event in 2015 by Budisulistiorini, Sri Hapsari, Riva, Matthieu, Williams, Michael, Miyakawa, Takuma, Chen, Jing, Itoh, Masayuki, Surratt, Jason D., Kuwata, Mikinori

“…Simultaneously, we characterized carbonaceous components and organic aerosol (OA) tracers from fine PM (PM2.5) samples to support source apportionment of the online measurements. …”
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Employee profiling via aspect-based sentiment and network for insider threats detection by Soh, Charlie, Yu, Sicheng, Narayanan, Annamalai, Duraisamy, Santhiya, Chen, Lihui

“…On the contrary to the traditional sentiment analysis, aspect-based sentiment analysis provides more fine-grained information on the employee. Our framework employs a combination of deep learning techniques such as Gated Recurrent Unit (GRU) and skipgram to build temporal sentiment profiles for the employees. …”
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Efficiency analysis for active rectifier in more electric aircraft (MEA) generator by Lim, Sin Guang

“…In this analysis, further fine tuning will be done to achieve the desired overall performance of the rectifier. …”
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