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Novi Quadrianto

24 papers · 2008–2026 · 10 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (13) 🌈 Renaissance Researcher (6) πŸŒ‰ Interdisciplinary Bridge πŸƒ Academic Marathon (16) πŸ—ΊοΈ Taxonomy Completionist (22) 🧭 Keyword Pioneer 🌍 Conference Polyglot (10) 🌟 Keyword Trendsetter Combo (7) πŸ† Keyword Champion 🌱 Topic Pioneer πŸ“ˆ Trend Setter πŸ’Ž Century Club (23) ❓ The Questioner πŸš€ Conference Pioneer πŸ—ƒοΈ Keyword Collector (53)

Conferences

NIPS (8) CVPR (3) ICML (3) AAAI (2) AISTATS (2) ECCV (2) EMNLP (1) ICCV (1) IJCAI (1) JMLR (1)

Top co-authors

Viktoriia Sharmanska (9) Alex J. Smola (5) TibΓ©rio S. Caetano (3) Kristian Kersting (2) Sara Romiti (2) James Petterson (2) Oliver Thomas (2) Myles Bartlett (2) Christoph H. Lampert (2) Ainhize Barrainkua (2)

Research topics

Optimization (1)

Keywords

privileged information (5) gaussian process (3) semi-supervised learning (2) computer vision (2) bayesian inference (2) structured prediction (2) distribution matching (2) control variate (2) semidefinite programming (1) black-box optimization (1) metric learning (1) variational inference (1) representation learning (1) domain adaptation (1) domain generalization (1) probabilistic modeling (1) image segmentation (1) convex optimization (1) algorithmic fairness (1) classification (1)

Papers

Revisiting (Un)Fairness in Recourse by Minimizing Worst-Case Social Burden AAAI 2026
Uncertainty Matters: Stable Conclusions under Unstable Assessment of Fairness Results AISTATS 2024
Are Compressed Language Models Less Subgroup Robust? EMNLP 2023
RealPatch: A Statistical Matching Framework for Model Patching with Real Samples ECCV 2022
Okapi: Generalising Better by Making Statistical Matches Match NIPS 2022
Low-Variance Black-Box Gradient Estimates for the Plackett-Luce Distribution AAAI 2020
Null-sampling for Interpretable and Fair Representations ECCV 2020
Discovering Fair Representations in the Data Domain CVPR 2019
Recycling Privileged Learning and Distribution Matching for Fairness NIPS 2017
Composing Tree Graphical Models with Persistent Homology Features for Clustering Mixed-Type Data ICML 2017
Gray-box Inference for Structured Gaussian Process Models AISTATS 2017
Learning From the Mistakes of Others: Matching Errors in Cross-Dataset Learning CVPR 2016
Ambiguity Helps: Classification With Disagreements in Crowdsourced Annotations CVPR 2016
Clustering High Dimensional Categorical Data via Topographical Features ICML 2016
Learning Using Unselected Features (LUFe) IJCAI 2016
Scalable Gaussian Process Structured Prediction for Grid Factor Graph Applications ICML 2014
Mind the Nuisance: Gaussian Process Classification using Privileged Noise NIPS 2014
Learning to Rank Using Privileged Information ICCV 2013
Multitask Learning without Label Correspondences NIPS 2010
Optimal Web-Scale Tiering as a Flow Problem NIPS 2010
Convex Relaxation of Mixture Regression with Efficient Algorithms NIPS 2009
Distribution Matching for Transduction NIPS 2009
Estimating Labels from Label Proportions JMLR 2009
Kernelized Sorting NIPS 2008