Shu Yao

Assistant Professor @ AI Thrust, HKUST (GZ)

[Shu Yao @ZCODE0]

Hi guys! I am extremely honored to join the AI Thrust at HKUST (GZ) as an Assistant Professor in April 2025. I am recruiting Ph.D. and MPhil students for Fall 2025. Visit my personal website https://t.co/uy8J0HqSU9 for more info and feel free to email for the application.

[Shu Yao @ZCODE0]

LLMs struggling with prompt variations? 🤔 PAFT (Prompt-Agnostic Fine-Tuning) to the rescue! 🚀 We fine-tune for robustness, achieving state-of-the-art performance. Read the paper: https://t.co/w80HmQ9PyL
#AI #NLP #LLMs #Prompt #Robustness

[Shu Yao @ZCODE0]

@ray_qiaorui Haha, thanks!

[Shu Yao @ZCODE0]

Hi guys! I am extremely honored to join the AI Thrust at HKUST (GZ) as an Assistant Professor in April 2025. I am recruiting Ph.D. and MPhil students for Fall 2025. Visit my personal website https://t.co/uy8J0HqSU9 for more info and feel free to email for the application.

[Bryan Kian Hsiang Low @bryanklow]

The #EMNLP2024 @emnlpmeeting (findings) position paper of @michael_xinyi @WuZhaoxuan @ray_qiaorui @arun_v3rma @PangWeiKoh et al. proposes a data-centric viewpoint of AI research, focusing on #LLM #LLMs.

Check it out @ https://t.co/IEtyi0dGLS

[Bryan Kian Hsiang Low @bryanklow]

Visit the poster of @ZCODE0 @xiaoqiang_98 @Dai_Zh et al. on Federated #ZerothOrderOptimization at @icmlconf #ICML2024 Workshop on Differentiable Almost Everything (26 Jul, https://t.co/ogwPZwOaFe)!

Paper: https://t.co/rwMyXC9dk7
#FederatedLearning

[Bryan Kian Hsiang Low @bryanklow]

The #ICLR2024 @iclr_conf work of @he_zhenfeng @Dai_Zh @ZCODE introduces RoBoT🤖 to robustify and boost training-free #NeuralArchitectureSearch.

Join us @ Poster Session 6 May 9 Thu 4:30PM Halle B #250
Paper: https://t.co/wsvUvM5oXi
Code: https://t.co/nxk1q8w5IJ

[Bryan Kian Hsiang Low @bryanklow]

Our research group & collaborators have put together 4 chapters in the #FederatedLearning: Theory and Practice book: fairness (ch.8), #DataValuation (ch.15) & incentives (ch.16) in #FederatedLearning, and federated sequential decision making (ch.14).
https://t.co/rFgJNudTKM (1/n)

[Bryan Kian Hsiang Low @bryanklow]

Congrats! @greglau @apivich_h @he_zhenfeng @insebtion @WuZhaoxuan @ray_qiaorui @qphong ruth @Dai_Zh @ZCODE @pjaillet

Accepted @iclr_conf #ICLR2024: #ShapleyValue #DataValuation #FederatedLearning #BayesianOptimization #NeuralArchitectureSearch #NeuralTangentKernel #AI4Science

[Bryan Kian Hsiang Low @bryanklow]

When using #ChatGPT, how do u decide what instruction to give it?

https://t.co/6PNugtiN19

Joint work on Automatic Prompting with @xiaoqiang_98 @WuZhaoxuan @Dai_Zh @_Hu_Wenyang @ZCODE0 see-kiong @pjaillet.

#LLM #LLMs #PromptEngineering #GenerativeAI (1/n)

[Bryan Kian Hsiang Low @bryanklow]

Congrats! to @RachaelSim2 @insebtion @michael_xinyi greg @chi_thanh_lam @arun_v3rma @Dai_Zh @ZCODE0 @qphong @nghiaht87 yehong chuan-sheng @pjaillet

Accepted papers @NeurIPSConf #NeurIPS2023: #ShapleyValue #DataValuation #FederatedLearning #BayesianOptimization #AI4Science

[Bryan Kian Hsiang Low @bryanklow]

Congrats to @ZCODE0 for winning the best Ph.D. thesis award in 2023 @NUSComputing!

His thesis topic is on #NeuralArchitectureSearch.

URL: https://t.co/dFAoU9pylm

[Bryan Kian Hsiang Low @bryanklow]

Postdoc & RA positions in #AutoML #ActiveLearning #BayesianOptimization #NeuralArchitectureSearch #ReinforcementLearning #MultiAgentRL #AutoRL @NUSComputing

See https://t.co/KI2CHrfiyi

#ICLR2023 #AAAI2023 #IJCAI2023 #UAI2023 #AISTATS2023 #NeurIPS2023

Meet me @ #ICML2023

[Bryan Kian Hsiang Low @bryanklow]

The #ICLR2023 work of @ZCODE0 @Dai_Zh weicong @arun_v3rma @pjaillet @bryanklow proposes a query-efficient Zeroth-Order Optimization algo w. trajectory-informed derivative est. #BayesianOptimization #GaussianProcess

Paper: https://t.co/1tqv3N4PSU

Present: https://t.co/z9rvSNBSyS

[Bryan Kian Hsiang Low @bryanklow]

The #ICLR2023 work of @Dai_Zh @ZCODE0 @arun_v3rma @Flint_xf_Fan @bryanklow @pjaillet proposes the first federated neural contextual bandit algorithm (1/N).

#FederatedLearning #BayesianOptimization

Paper: https://t.co/QUcHtB1a2Q

Presentation: https://t.co/gh6aSXTWFk

[Bryan Kian Hsiang Low @bryanklow]

Congrats @chi_thanh_lam @michael_xinyi @insebtion weicong @WuZhaoxuan @Flint_xf_Fan @qphong @Dai_Zh @ZCODE0 @arun_v3rma chuan-sheng @pjaillet. Accepted papers @ #AISTATS2023 #ICLR2023: Zeroth-Order Optimization #BayesianOptimization #ActiveLearning #FederatedLearning #AI4Science

[Shu Yao @ZCODE0]

This is the first unified theoretical study to explain why existing training-free NAS algorithms perform well in practice and how to further improve them. We believe this work can help/inspire existing training-free NAS and also the follow-ups to behave more soundly in practice.

[Bryan Kian Hsiang Low @bryanklow]

To understand and boost gradient-based #TrainingFree #NeuralArchitectureSearch algorithms, the #NeurIPS2022 work of @ZCODE0 @Dai_Zh @WuZhaoxuan @bryanklow provides the first unified theoretical study and principled improvement for them based on theory of #NeuralTangentKernel.

[Bryan Kian Hsiang Low @bryanklow]

The #NeurIPS2022 work of @Dai_Zh @ZCODE0 @bryanklow @pjaillet introduces theoretically grounded batch #BayesianOptimization algorithms using #DeepNeuralNetworks (DNNs) as the surrogate function that can handle categorical, high-dimensional, or image inputs. #NeuralTangentKernel

[Bryan Kian Hsiang Low @bryanklow]

To fairly trade off betw payoff & model rewards in collaborative ML, the #NeurIPS2022 work of @qphong @bryanklow @pjaillet refines #ShapleyValue into a conditional variant representing pairwise payoff flows betw parties. #FederatedLearning #DataValuation

[Bryan Kian Hsiang Low @bryanklow]

Postdoc & RA positions in #DataCentricAI Collaborative ML/#FederatedLearning #DataValuation Incentive-Aware Mechanism Design #MachineUnlearning
@NUSComputing

See https://t.co/37Hq2zWM3O

#ICML2023 #ICLR2023 #AAAI2023 #IJCAI2023 #UAI2023 #AISTATS2023

Meet me @ #NeurIPS2022