Novi Quadrianto

Publication Activity (10 Years)

Years Active: 2008-2024
Publications (10 Years): 39

Top Topics

Gaussian Process

Structured Prediction

Candidate Matches

Top Venues

Publications

Thomas Kehrenberg, Myles Bartlett, Viktoriia Sharmanska, Novi Quadrianto
Addressing Attribute Bias with Adversarial Support-Matching. Trans. Mach. Learn. Res. 2024 (2024)
Leonidas Gee, Andrea Zugarini, Novi Quadrianto
Are Compressed Language Models Less Subgroup Robust? CoRR (2024)
Ainhize Barrainkua, Paula Gordaliza, José Antonio Lozano, Novi Quadrianto
Dancing in the Shadows: Harnessing Ambiguity for Fairer Classifiers. CoRR (2024)
Ainhize Barrainkua, Paula Gordaliza, José Antonio Lozano, Novi Quadrianto
Uncertainty Matters: Stable Conclusions under Unstable Assessment of Fairness Results. AISTATS (2024)
Ainhize Barrainkua, Paula Gordaliza, José Antonio Lozano, Novi Quadrianto
Uncertainty in Fairness Assessment: Maintaining Stable Conclusions Despite Fluctuations. CoRR (2023)
Leonidas Gee, Andrea Zugarini, Novi Quadrianto
Are Compressed Language Models Less Subgroup Robust? EMNLP (2023)
Georgios Voulgaris, Andy Philippides, Jonathan Dolley, Jeremy Reffin, Fiona Marshall, Novi Quadrianto
Seasonal Domain Shift in the Global South: Dataset and Deep Features Analysis. CVPR Workshops (2023)
Georgios Voulgaris, Andrew Philippides, Novi Quadrianto
Water Physics Aware Semantic Segmentation through Texture-Biased U-Net Architectures. IGARSS (2023)
Gergely Dániel Németh, Miguel Angel Lozano, Novi Quadrianto, Nuria Oliver
Addressing Membership Inference Attack in Federated Learning with Model Compression. CoRR (2023)
Ainhize Barrainkua, Paula Gordaliza, José Antonio Lozano, Novi Quadrianto
A Survey on Preserving Fairness Guarantees in Changing Environments. CoRR (2022)
Sara Romiti, Christopher Inskip, Viktoriia Sharmanska, Novi Quadrianto
RealPatch: A Statistical Matching Framework for Model Patching with Real Samples. ECCV (25) (2022)
Myles Bartlett, Sara Romiti, Viktoriia Sharmanska, Novi Quadrianto
Okapi: Generalising Better by Making Statistical Matches Match. CoRR (2022)
Georgios Voulgaris, Andrew Philippides, Novi Quadrianto
Deep Learning Robustness to Domain Shifts During Seasonal Variations. IGARSS (2022)
Gergely Dániel Németh, Miguel Angel Lozano, Novi Quadrianto, Nuria Oliver Ramirez
A Snapshot of the Frontiers of Client Selection in Federated Learning. Trans. Mach. Learn. Res. 2022 (2022)
Sara Romiti, Christopher Inskip, Viktoriia Sharmanska, Novi Quadrianto
RealPatch: A Statistical Matching Framework for Model Patching with Real Samples. CoRR (2022)
Thomas Kehrenberg, Myles Bartlett, Viktoriia Sharmanska, Novi Quadrianto
Addressing Missing Sources with Adversarial Support-Matching. CoRR (2022)
Gergely Dániel Németh, Miguel Angel Lozano, Novi Quadrianto, Nuria Oliver
A Snapshot of the Frontiers of Client Selection in Federated Learning. CoRR (2022)
Myles Bartlett, Sara Romiti, Viktoriia Sharmanska, Novi Quadrianto
Okapi: Generalising Better by Making Statistical Matches Match. NeurIPS (2022)
Oliver Thomas, Miri Zilka, Adrian Weller, Novi Quadrianto
An Algorithmic Framework for Positive Action. EAAMO (2021)
Bradley Butcher, Vincent S. Huang, Christopher Robinson, Jeremy Reffin, Sema K. Sgaier, Grace Charles, Novi Quadrianto
Causal Datasheet for Datasets: An Evaluation Guide for Real-World Data Analysis and Data Collection Design Using Bayesian Networks. Frontiers Artif. Intell. 4 (2021)
Novi Quadrianto, Björn W. Schuller, Finnian Rachel Lattimore
Editorial: Ethical Machine Learning and Artificial Intelligence. Frontiers Big Data 4 (2021)
Viktoriia Sharmanska, Lisa Anne Hendricks, Trevor Darrell, Novi Quadrianto
Contrastive Examples for Addressing the Tyranny of the Majority. CoRR (2020)
Artyom Gadetsky, Kirill Struminsky, Christopher Robinson, Novi Quadrianto, Dmitry P. Vetrov
Low-Variance Black-Box Gradient Estimates for the Plackett-Luce Distribution. AAAI (2020)
Bradley Butcher, Vincent S. Huang, Jeremy Reffin, Sema K. Sgaier, Grace Charles, Novi Quadrianto
Causal datasheet: An approximate guide to practically assess Bayesian networks in the real world. CoRR (2020)
Thomas Kehrenberg, Zexun Chen, Novi Quadrianto
Tuning Fairness by Balancing Target Labels. Frontiers Artif. Intell. 3 (2020)
Thomas Kehrenberg, Myles Bartlett, Oliver Thomas, Novi Quadrianto
Null-sampling for Interpretable and Fair Representations. CoRR (2020)
Thomas Kehrenberg, Myles Bartlett, Oliver Thomas, Novi Quadrianto
Null-Sampling for Interpretable and Fair Representations. ECCV (26) (2020)
Novi Quadrianto, Viktoriia Sharmanska, Oliver Thomas
Discovering Fair Representations in the Data Domain. CVPR (2019)
David Spence, Christopher Inskip, Novi Quadrianto, David Weir
Quantification under class-conditional dataset shift. ASONAM (2019)
Artyom Gadetsky, Kirill Struminsky, Christopher Robinson, Novi Quadrianto, Dmitry P. Vetrov
Low-variance Black-box Gradient Estimates for the Plackett-Luce Distribution. CoRR (2019)
Novi Quadrianto, Viktoriia Sharmanska, Oliver Thomas
Neural Styling for Interpretable Fair Representations. CoRR (2018)
Thomas Kehrenberg, Zexun Chen, Novi Quadrianto
Interpretable Fairness via Target Labels in Gaussian Process Models. CoRR (2018)
Pietro Galliani, Amir Dezfouli, Edwin V. Bonilla, Novi Quadrianto
Gray-box Inference for Structured Gaussian Process Models. AISTATS (2017)
Novi Quadrianto, Viktoriia Sharmanska
Recycling Privileged Learning and Distribution Matching for Fairness. NIPS (2017)
Xiuyan Ni, Novi Quadrianto, Yusu Wang, Chao Chen
Composing Tree Graphical Models with Persistent Homology Features for Clustering Mixed-Type Data. ICML (2017)
Viktoriia Sharmanska, Novi Quadrianto
Learning from the Mistakes of Others: Matching Errors in Cross-Dataset Learning. CVPR (2016)
Viktoriia Sharmanska, Daniel Hernández-Lobato, José Miguel Hernández-Lobato, Novi Quadrianto
Ambiguity Helps: Classification with Disagreements in Crowdsourced Annotations. CVPR (2016)
Joseph G. Taylor, Viktoriia Sharmanska, Kristian Kersting, David Weir, Novi Quadrianto
Learning Using Unselected Features (LUFe). IJCAI (2016)
Chao Chen, Novi Quadrianto
Clustering High Dimensional Categorical Data via Topographical Features. ICML (2016)
Novi Quadrianto, Zoubin Ghahramani
A Very Simple Safe-Bayesian Random Forest. IEEE Trans. Pattern Anal. Mach. Intell. 37 (6) (2015)
Sébastien Bratières, Novi Quadrianto, Zoubin Ghahramani
GPstruct: Bayesian Structured Prediction Using Gaussian Processes. IEEE Trans. Pattern Anal. Mach. Intell. 37 (7) (2015)
Viktoriia Sharmanska, Novi Quadrianto, Christoph H. Lampert
Learning to Transfer Privileged Information. CoRR (2014)
Sébastien Bratières, Novi Quadrianto, Sebastian Nowozin, Zoubin Ghahramani
Scalable Gaussian Process Structured Prediction for Grid Factor Graph Applications. ICML (2014)
Daniel Hernández-Lobato, Viktoriia Sharmanska, Kristian Kersting, Christoph H. Lampert, Novi Quadrianto
Mind the Nuisance: Gaussian Process Classification using Privileged Noise. NIPS (2014)
Daniel Hernández-Lobato, Viktoriia Sharmanska, Kristian Kersting, Christoph H. Lampert, Novi Quadrianto
Mind the Nuisance: Gaussian Process Classification using Privileged Noise. CoRR (2014)
Sébastien Bratières, Novi Quadrianto, Zoubin Ghahramani
Bayesian Structured Prediction Using Gaussian Processes. CoRR (2013)
Viktoriia Sharmanska, Novi Quadrianto, Christoph H. Lampert
Learning to Rank Using Privileged Information. ICCV (2013)
Novi Quadrianto, Viktoriia Sharmanska, David A. Knowles, Zoubin Ghahramani
The Supervised IBP: Neighbourhood Preserving Infinite Latent Feature Models. CoRR (2013)
Novi Quadrianto, Viktoriia Sharmanska, David A. Knowles, Zoubin Ghahramani
The Supervised IBP: Neighbourhood Preserving Infinite Latent Feature Models. UAI (2013)
Novi Quadrianto, Chao Chen, Christoph H. Lampert
The Most Persistent Soft-Clique in a Set of Sampled Graphs CoRR (2012)
Novi Quadrianto, Chao Chen, Christoph H. Lampert
The Most Persistent Soft-Clique in a Set of Sampled Graphs. ICML (2012)
Tatiana Tommasi, Novi Quadrianto, Barbara Caputo, Christoph H. Lampert
Beyond Dataset Bias: Multi-task Unaligned Shared Knowledge Transfer. ACCV (1) (2012)
Viktoriia Sharmanska, Novi Quadrianto, Christoph H. Lampert
Augmented Attribute Representations. ECCV (5) (2012)
Novi Quadrianto, Christoph H. Lampert
Learning Multi-View Neighborhood Preserving Projections. ICML (2011)
Novi Quadrianto, Kristian Kersting, Tinne Tuytelaars, Wray L. Buntine
Beyond 2D-grids: a dependence maximization view on image browsing. Multimedia Information Retrieval (2010)
Gilbert Leung, Novi Quadrianto, Alexander J. Smola, Kostas Tsioutsiouliklis
Optimal Web-Scale Tiering as a Flow Problem. NIPS (2010)
Novi Quadrianto, Alexander J. Smola, Le Song, Tinne Tuytelaars
Kernelized Sorting. IEEE Trans. Pattern Anal. Mach. Intell. 32 (10) (2010)
Novi Quadrianto, Dale Schuurmans, Alexander J. Smola
Distributed Flow Algorithms for Scalable Similarity Visualization. ICDM Workshops (2010)
Novi Quadrianto, Alexander J. Smola, Tibério S. Caetano, S. V. N. Vishwanathan, James Petterson
Multitask Learning without Label Correspondences. NIPS (2010)
Akshay Asthana, Roland Goecke, Novi Quadrianto, Tom Gedeon
Learning based automatic face annotation for arbitrary poses and expressions from frontal images only. CVPR (2009)
Novi Quadrianto, Tibério S. Caetano, John Lim, Dale Schuurmans
Convex Relaxation of Mixture Regression with Efficient Algorithms. NIPS (2009)
Novi Quadrianto, Kristian Kersting, Mark D. Reid, Tibério S. Caetano, Wray L. Buntine
Kernel Conditional Quantile Estimation via Reduction Revisited. ICDM (2009)
Novi Quadrianto, Alexander J. Smola, Tibério S. Caetano, Quoc V. Le
Estimating Labels from Label Proportions. J. Mach. Learn. Res. 10 (2009)
Novi Quadrianto, James Petterson, Alexander J. Smola
Distribution Matching for Transduction. NIPS (2009)
Novi Quadrianto, Alexander J. Smola, Tibério S. Caetano, Quoc V. Le
Estimating labels from label proportions. ICML (2008)
Novi Quadrianto, Le Song, Alexander J. Smola
Kernelized Sorting. NIPS (2008)