Chuan Sheng Foo
19 papers · 2007–2024 · 7 conferences · across top CS/AI conferences
Achievements
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π Academic Marathon (17) π Interdisciplinary Bridge π§ Keyword Pioneer π Conference Polyglot (7) π Cross-Pollinator (14)
πΊοΈ
Taxonomy Completionist
(55)
π
Interdisciplinary Bridge
π§
Keyword Pioneer
π€
Dynamic Duo
(10)
β‘
Prolific Year
(6)
π
Trend Setter
π
Century Club
(19)
ποΈ
Keyword Collector
(106)
Conferences
NIPS (7)
CVPR (4)
AAAI (3)
AISTATS (2)
EACL (1)
ECCV (1)
ICML (1)
Top co-authors
Keywords
data valuation
(4)
3d reconstruction
(3)
bayesian optimization
(3)
gaussian process
(2)
fairness guarantee
(2)
maximum mean discrepancy
(2)
active learning
(2)
shapley value
(2)
sample efficiency
(2)
no-regret algorithm
(2)
convex optimization
(1)
object detection
(1)
unsupervised domain adaptation
(1)
gradient-based optimization
(1)
model selection
(1)
hyperparameter optimization
(1)
parallel computing
(1)
hyperparameter learning
(1)
nash equilibrium
(1)
structured prediction
(1)
Papers
REACTO: Reconstructing Articulated Objects from a Single Video
CVPR 2024
R-Cyclic Diffuser: Reductive and Cyclic Latent Diffusion for 3D Clothed Human Digitalization
CVPR 2024
Data Distribution Valuation
NIPS 2024
Towards Reliable Model Selection for Unsupervised Domain Adaptation: An Empirical Study and A Certified Baseline
NIPS 2024
3DFG-PIFu: 3D Feature Grids for Human Digitization from Sparse Views
ECCV 2024
Fine Structure-Aware Sampling: A New Sampling Training Scheme for Pixel-Aligned Implicit Models in Single-View Human Reconstruction
AAAI 2024
FAIR: Fair Collaborative Active Learning with Individual Rationality for Scientific Discovery
AISTATS 2023
No-regret Sample-efficient Bayesian Optimization for Finding Nash Equilibria with Unknown Utilities
AISTATS 2023
Using Punctuation as an Adversarial Attack on Deep Learning-Based NLP Systems: An Empirical Study
EACL 2023
Bayesian Optimization with Cost-varying Variable Subsets
NIPS 2023
Model Shapley: Equitable Model Valuation with Black-box Access
NIPS 2023
Probably Approximate Shapley Fairness with Applications in Machine Learning
AAAI 2023
Efficient Distributionally Robust Bayesian Optimization with Worst-case Sensitivity
ICML 2022
Incentivizing Collaboration in Machine Learning via Synthetic Data Rewards
AAAI 2022
Revisiting Superpixels for Active Learning in Semantic Segmentation With Realistic Annotation Costs
CVPR 2021
Gradient Driven Rewards to Guarantee Fairness in Collaborative Machine Learning
NIPS 2021
Validation Free and Replication Robust Volume-based Data Valuation
NIPS 2021
MaxpoolNMS: Getting Rid of NMS Bottlenecks in Two-Stage Object Detectors
CVPR 2019
Efficient multiple hyperparameter learning for log-linear models
NIPS 2007