Yew-Soon Ong
Professor
Works on computational intelligence, including evolutionary and transfer optimization, Bayesian optimization and statistical machine learning.
Yew-Soon Ong's lab at NTU works on learning theory & optimization, probabilistic & causal inference and genomics & computational biology. 22 papers since 2023, 7 at top venues, mostly TPAMI and ICLR.
At a glance
- papers, 2023–2026
- 6/ year
- at T1 venues
- 32%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom the lab homepage, 2023–2026
- 0 papers2026 · T1 0 · collecting
- 0 papers2025 · T1 0
- 5 papers2024 · T1 1
- 17 papers2023 · T1 6
T1 venuesOtherVenues: TPAMI, ICLR, ICML, IJCAI, SIGIR
Research focuspaper titles that use each topic's words
- Learning theory & optimization16 papers
- Probabilistic & causal inference3 papers
- evolutionary2 papers
- bayesian optimization1 paper
- Genomics & computational biology0 papers
Paper list
From the lab homepage.
20245 papers
- IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR- ), June 17-21, , Seattle, USAAdversarially Robust Few-shot Learning via Parameter Co-distillation of Similarity and Class Concept Learners
- The Annual AAAI Conference on Artificial Intelligence. February 20-27, , Vancouver, Canada Vancouver Convention Centre, West BuildingFedCompetitors: Harmonious Collaboration in Federated Learning with Competing Participants
- The Annual AAAI Conference on Artificial Intelligence. February 20-27, , Vancouver, Canada Vancouver Convention Centre, West BuildingLearning Accurate and Bidirectional Transformation via Dynamic Embedding Transportation for Cross-Domain Recommendation
- ICML (T1)Reducing Item Discrepancy via Differentially Private Robust Embedding Alignment for Privacy-Preserving Cross Domain Recommendation
- IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR- ), June 17-21, , Seattle, USARobust Distillation via Untargeted and Targeted Intermediate Adversarial Samples
202317 papers
- IEEE Computational Intelligence MagazineA Survey on AI Sustainability: Emerging Trends on Learning Algorithms and Research Challenges
- TPAMI (T1)Adaptive Transfer Kernel Learning for Transfer Gaussian Process Regression
- TNNLS (T1)Adversary Agnostic Robust Deep Reinforcement Learning
- IJCAI (T1)Bayesian Federated Learning: A Survey
- IEEE Transactions on CyberneticsChoose Appropriate Subproblems for Collaborative Modeling in Expensive Multiobjective Optimization
- IEEE Transactions on CyberneticsGenerative Multi-Form Bayesian Optimization
- Chaos: An Interdisciplinary Journal of Nonlinear ScienceGranger Causality Using Jacobian in Neural Networks
- IEEE Computational Intelligence MagazineJack and Masters of All Trades: One-pass Learning Sets of Model Sets from Large Pre-trained Models
- IEEE Transactions on Systems, Man, and Cybernetics: SystemsLearning Multi-Task Gaussian Process Over Heterogeneous Input Domains
- ICLR (T1)Masked Frequency Modeling for Self-Supervised Visual Pre-Training
- IEEE Transactions on Artificial IntelligenceMulti-Space Evolutionary Search for Large-Scale Optimization with Applications to Recommender Systems
- IEEE Transactions on CyberneticsMultiparty Dual Learning
Where alumni went
Alumni are not listed on the lab homepage.
Apply to NTUFall 2027
Not announced yet
Computing and Data Science PhD
- Round
- Main
- Opens
- —
- GRE
- not required
- English
- TOEFL/IELTS
- Fee
- See program page
Not yet confirmed for this intake.
Similar labsnearest by research summary
- GBUCL
David Barber
- Probabilistic & causal inference
- USUSC
Angela Zhou
- Probabilistic & causal inference
- GBEdinburgh
Amos Storkey
- Reinforcement learning
- USGeorgia Tech
Thomas Ploetz
- Recognition, detection & segmentation
- USUCLA
Aditya Grover
- Reinforcement learning
- USUW
Kevin Jamieson
- Reinforcement learning
Your notes
Save this lab to keep notes.
Data
Some numbers could not be verified:
- The member list could not be found on the lab site.
- The alumni list could not be found on the lab site.
- Collected
- Verified
- Papers
- The lab homepage
- Members
- Not collected
- Alumni
- Not collected
Tiers are venue classifications, not lab rankings.