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2020 – today
- 2024
[j9]Thomas Kehrenberg, Myles Bartlett, Viktoriia Sharmanska, Novi Quadrianto:
Addressing Attribute Bias with Adversarial Support-Matching. Trans. Mach. Learn. Res. 2024 (2024)- [c37]Ainhize Barrainkua, Paula Gordaliza, José Antonio Lozano, Novi Quadrianto:
Uncertainty Matters: Stable Conclusions under Unstable Assessment of Fairness Results. AISTATS 2024: 1198-1206 - [i20]Leonidas Gee, Andrea Zugarini, Novi Quadrianto:
Are Compressed Language Models Less Subgroup Robust? CoRR abs/2403.17811 (2024) - [i19]Ainhize Barrainkua, Paula Gordaliza, José Antonio Lozano, Novi Quadrianto:
Dancing in the Shadows: Harnessing Ambiguity for Fairer Classifiers. CoRR abs/2406.19066 (2024) - 2023
- [c36]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: 2116-2124 - [c35]Leonidas Gee, Andrea Zugarini, Novi Quadrianto:
Are Compressed Language Models Less Subgroup Robust? EMNLP 2023: 15859-15868 - [c34]Georgios Voulgaris, Andrew Philippides, Novi Quadrianto:
Water Physics Aware Semantic Segmentation through Texture-Biased U-Net Architectures. IGARSS 2023: 5435-5438 - [i18]Ainhize Barrainkua, Paula Gordaliza, José Antonio Lozano, Novi Quadrianto:
Uncertainty in Fairness Assessment: Maintaining Stable Conclusions Despite Fluctuations. CoRR abs/2302.01079 (2023) - [i17]Gergely Dániel Németh, Miguel Angel Lozano, Novi Quadrianto, Nuria Oliver:
Addressing Membership Inference Attack in Federated Learning with Model Compression. CoRR abs/2311.17750 (2023) - 2022
- [j8]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) - [c33]Sara Romiti, Christopher Inskip, Viktoriia Sharmanska, Novi Quadrianto:
RealPatch: A Statistical Matching Framework for Model Patching with Real Samples. ECCV (25) 2022: 146-162 - [c32]Georgios Voulgaris, Andrew Philippides, Novi Quadrianto:
Deep Learning Robustness to Domain Shifts During Seasonal Variations. IGARSS 2022: 417-420 - [c31]Myles Bartlett, Sara Romiti, Viktoriia Sharmanska, Novi Quadrianto:
Okapi: Generalising Better by Making Statistical Matches Match. NeurIPS 2022 - [i16]Thomas Kehrenberg, Myles Bartlett, Viktoriia Sharmanska, Novi Quadrianto:
Addressing Missing Sources with Adversarial Support-Matching. CoRR abs/2203.13154 (2022) - [i15]Sara Romiti, Christopher Inskip, Viktoriia Sharmanska, Novi Quadrianto:
RealPatch: A Statistical Matching Framework for Model Patching with Real Samples. CoRR abs/2208.02192 (2022) - [i14]Gergely Dániel Németh, Miguel Angel Lozano, Novi Quadrianto, Nuria Oliver:
A Snapshot of the Frontiers of Client Selection in Federated Learning. CoRR abs/2210.04607 (2022) - [i13]Myles Bartlett, Sara Romiti, Viktoriia Sharmanska, Novi Quadrianto:
Okapi: Generalising Better by Making Statistical Matches Match. CoRR abs/2211.05236 (2022) - [i12]Ainhize Barrainkua, Paula Gordaliza, José Antonio Lozano, Novi Quadrianto:
A Survey on Preserving Fairness Guarantees in Changing Environments. CoRR abs/2211.07530 (2022) - 2021
- [j7]Novi Quadrianto, Björn W. Schuller, Finnian Rachel Lattimore:
Editorial: Ethical Machine Learning and Artificial Intelligence. Frontiers Big Data 4: 742589 (2021) - [j6]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: 612551 (2021) - [c30]Oliver Thomas, Miri Zilka, Adrian Weller, Novi Quadrianto:
An Algorithmic Framework for Positive Action. EAAMO 2021: 18:1-18:13 - 2020
- [j5]Thomas Kehrenberg, Zexun Chen, Novi Quadrianto:
Tuning Fairness by Balancing Target Labels. Frontiers Artif. Intell. 3: 33 (2020) - [c29]Artyom Gadetsky, Kirill Struminsky, Christopher Robinson, Novi Quadrianto, Dmitry P. Vetrov:
Low-Variance Black-Box Gradient Estimates for the Plackett-Luce Distribution. AAAI 2020: 10126-10135 - [c28]Thomas Kehrenberg, Myles Bartlett, Oliver Thomas, Novi Quadrianto:
Null-Sampling for Interpretable and Fair Representations. ECCV (26) 2020: 565-580 - [i11]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 abs/2003.07182 (2020) - [i10]Viktoriia Sharmanska, Lisa Anne Hendricks, Trevor Darrell, Novi Quadrianto:
Contrastive Examples for Addressing the Tyranny of the Majority. CoRR abs/2004.06524 (2020) - [i9]Thomas Kehrenberg, Myles Bartlett, Oliver Thomas, Novi Quadrianto:
Null-sampling for Interpretable and Fair Representations. CoRR abs/2008.05248 (2020)
2010 – 2019
- 2019
- [c27]David Spence, Christopher Inskip, Novi Quadrianto, David Weir:
Quantification under class-conditional dataset shift. ASONAM 2019: 528-529 - [c26]Novi Quadrianto, Viktoriia Sharmanska, Oliver Thomas:
Discovering Fair Representations in the Data Domain. CVPR 2019: 8227-8236 - [i8]Artyom Gadetsky, Kirill Struminsky, Christopher Robinson, Novi Quadrianto, Dmitry P. Vetrov:
Low-variance Black-box Gradient Estimates for the Plackett-Luce Distribution. CoRR abs/1911.10036 (2019) - 2018
- [i7]Thomas Kehrenberg, Zexun Chen, Novi Quadrianto:
Interpretable Fairness via Target Labels in Gaussian Process Models. CoRR abs/1810.05598 (2018) - [i6]Novi Quadrianto, Viktoriia Sharmanska, Oliver Thomas:
Neural Styling for Interpretable Fair Representations. CoRR abs/1810.06755 (2018) - 2017
- [c25]Pietro Galliani, Amir Dezfouli, Edwin V. Bonilla, Novi Quadrianto:
Gray-box Inference for Structured Gaussian Process Models. AISTATS 2017: 353-361 - [c24]Xiuyan Ni, Novi Quadrianto, Yusu Wang, Chao Chen:
Composing Tree Graphical Models with Persistent Homology Features for Clustering Mixed-Type Data. ICML 2017: 2622-2631 - [c23]Novi Quadrianto, Viktoriia Sharmanska:
Recycling Privileged Learning and Distribution Matching for Fairness. NIPS 2017: 677-688 - [r9]Novi Quadrianto, Kristian Kersting, Zhao Xu:
Gaussian Process. Encyclopedia of Machine Learning and Data Mining 2017: 535-548 - [r8]Viktoriia Sharmanska, Novi Quadrianto:
Learning Using Privileged Information. Encyclopedia of Machine Learning and Data Mining 2017: 734-737 - [r7]Novi Quadrianto, Wray L. Buntine:
Linear Discriminant. Encyclopedia of Machine Learning and Data Mining 2017: 745-747 - [r6]Novi Quadrianto, Wray L. Buntine:
Linear Regression. Encyclopedia of Machine Learning and Data Mining 2017: 747-750 - [r5]Novi Quadrianto, Wray L. Buntine:
Regression. Encyclopedia of Machine Learning and Data Mining 2017: 1075-1080 - 2016
- [c22]Viktoriia Sharmanska, Daniel Hernández-Lobato, José Miguel Hernández-Lobato, Novi Quadrianto:
Ambiguity Helps: Classification with Disagreements in Crowdsourced Annotations. CVPR 2016: 2194-2202 - [c21]Viktoriia Sharmanska, Novi Quadrianto:
Learning from the Mistakes of Others: Matching Errors in Cross-Dataset Learning. CVPR 2016: 3967-3975 - [c20]Chao Chen, Novi Quadrianto:
Clustering High Dimensional Categorical Data via Topographical Features. ICML 2016: 2732-2740 - [c19]Joseph G. Taylor, Viktoriia Sharmanska, Kristian Kersting, David Weir, Novi Quadrianto:
Learning Using Unselected Features (LUFe). IJCAI 2016: 2060-2066 - 2015
- [j4]Novi Quadrianto, Zoubin Ghahramani:
A Very Simple Safe-Bayesian Random Forest. IEEE Trans. Pattern Anal. Mach. Intell. 37(6): 1297-1303 (2015) - [j3]Sébastien Bratières, Novi Quadrianto, Zoubin Ghahramani:
GPstruct: Bayesian Structured Prediction Using Gaussian Processes. IEEE Trans. Pattern Anal. Mach. Intell. 37(7): 1514-1520 (2015) - 2014
- [c18]Sébastien Bratières, Novi Quadrianto, Sebastian Nowozin, Zoubin Ghahramani:
Scalable Gaussian Process Structured Prediction for Grid Factor Graph Applications. ICML 2014: 334-342 - [c17]Daniel Hernández-Lobato, Viktoriia Sharmanska, Kristian Kersting, Christoph H. Lampert, Novi Quadrianto:
Mind the Nuisance: Gaussian Process Classification using Privileged Noise. NIPS 2014: 837-845 - [i5]Daniel Hernández-Lobato, Viktoriia Sharmanska, Kristian Kersting, Christoph H. Lampert, Novi Quadrianto:
Mind the Nuisance: Gaussian Process Classification using Privileged Noise. CoRR abs/1407.0179 (2014) - [i4]Viktoriia Sharmanska, Novi Quadrianto, Christoph H. Lampert:
Learning to Transfer Privileged Information. CoRR abs/1410.0389 (2014) - 2013
- [c16]Viktoriia Sharmanska, Novi Quadrianto, Christoph H. Lampert:
Learning to Rank Using Privileged Information. ICCV 2013: 825-832 - [c15]Novi Quadrianto, Viktoriia Sharmanska, David A. Knowles, Zoubin Ghahramani:
The Supervised IBP: Neighbourhood Preserving Infinite Latent Feature Models. UAI 2013 - [i3]Sébastien Bratières, Novi Quadrianto, Zoubin Ghahramani:
Bayesian Structured Prediction Using Gaussian Processes. CoRR abs/1307.3846 (2013) - [i2]Novi Quadrianto, Viktoriia Sharmanska, David A. Knowles, Zoubin Ghahramani:
The Supervised IBP: Neighbourhood Preserving Infinite Latent Feature Models. CoRR abs/1309.6858 (2013) - 2012
- [c14]Tatiana Tommasi, Novi Quadrianto, Barbara Caputo, Christoph H. Lampert:
Beyond Dataset Bias: Multi-task Unaligned Shared Knowledge Transfer. ACCV (1) 2012: 1-15 - [c13]Viktoriia Sharmanska, Novi Quadrianto, Christoph H. Lampert:
Augmented Attribute Representations. ECCV (5) 2012: 242-255 - [c12]Novi Quadrianto, Chao Chen, Christoph H. Lampert:
The Most Persistent Soft-Clique in a Set of Sampled Graphs. ICML 2012 - [i1]Novi Quadrianto, Chao Chen, Christoph H. Lampert:
The Most Persistent Soft-Clique in a Set of Sampled Graphs. CoRR abs/1206.4652 (2012) - 2011
- [c11]Novi Quadrianto, Christoph H. Lampert:
Learning Multi-View Neighborhood Preserving Projections. ICML 2011: 425-432 - 2010
- [j2]Novi Quadrianto, Alexander J. Smola, Le Song, Tinne Tuytelaars:
Kernelized Sorting. IEEE Trans. Pattern Anal. Mach. Intell. 32(10): 1809-1821 (2010) - [c10]Novi Quadrianto, Dale Schuurmans, Alexander J. Smola:
Distributed Flow Algorithms for Scalable Similarity Visualization. ICDM Workshops 2010: 1220-1227 - [c9]Novi Quadrianto, Kristian Kersting, Tinne Tuytelaars, Wray L. Buntine:
Beyond 2D-grids: a dependence maximization view on image browsing. Multimedia Information Retrieval 2010: 339-348 - [c8]Gilbert Leung, Novi Quadrianto, Alexander J. Smola, Kostas Tsioutsiouliklis:
Optimal Web-Scale Tiering as a Flow Problem. NIPS 2010: 1333-1341 - [c7]Novi Quadrianto, Alexander J. Smola, Tibério S. Caetano, S. V. N. Vishwanathan, James Petterson:
Multitask Learning without Label Correspondences. NIPS 2010: 1957-1965 - [r4]Novi Quadrianto, Kristian Kersting, Zhao Xu:
Gaussian Process. Encyclopedia of Machine Learning 2010: 428-439 - [r3]Novi Quadrianto, Wray L. Buntine:
Linear Discriminant. Encyclopedia of Machine Learning 2010: 601-603 - [r2]Novi Quadrianto, Wray L. Buntine:
Linear Regression. Encyclopedia of Machine Learning 2010: 603-606 - [r1]Novi Quadrianto, Wray L. Buntine:
Regression. Encyclopedia of Machine Learning 2010: 838-842
2000 – 2009
- 2009
- [j1]Novi Quadrianto, Alexander J. Smola, Tibério S. Caetano, Quoc V. Le:
Estimating Labels from Label Proportions. J. Mach. Learn. Res. 10: 2349-2374 (2009) - [c6]Akshay Asthana, Roland Goecke, Novi Quadrianto, Tom Gedeon:
Learning based automatic face annotation for arbitrary poses and expressions from frontal images only. CVPR 2009: 1635-1642 - [c5]Novi Quadrianto, Kristian Kersting, Mark D. Reid, Tibério S. Caetano, Wray L. Buntine:
Kernel Conditional Quantile Estimation via Reduction Revisited. ICDM 2009: 938-943 - [c4]Novi Quadrianto, Tibério S. Caetano, John Lim, Dale Schuurmans:
Convex Relaxation of Mixture Regression with Efficient Algorithms. NIPS 2009: 1491-1499 - [c3]Novi Quadrianto, James Petterson, Alexander J. Smola:
Distribution Matching for Transduction. NIPS 2009: 1500-1508 - 2008
- [c2]Novi Quadrianto, Alexander J. Smola, Tibério S. Caetano, Quoc V. Le:
Estimating labels from label proportions. ICML 2008: 776-783 - [c1]Novi Quadrianto, Le Song, Alexander J. Smola:
Kernelized Sorting. NIPS 2008: 1289-1296
Coauthor Index
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