Our Publications

2017

  • Novi Quadrianto and Viktoriia Sharmanska.
    Recycling Privileged Learning and Distribution Matching for Fairness. Neural Information Processing Systems NIPS,
    Long Beach, California, USA, 2017. (678 out of 3240, 20.9% acceptance rate)
  • Xiuyan Ni, Novi Quadrianto, Yusu Wang, and Chao Chen.
    Composing Tree Graphical Models with Persistent Homology Features for Clustering Mixed-Type Data. International Conference on Machine Learning ICML,
    Sydney, Australia, 2017. (25% acceptance rate)
  • Pietro Galliani, Amir Dezfouli, Edwin V. Bonilla, and Novi Quadrianto.
    Gray-box Inference for Structured Gaussian Process Models. International Conference on Artificial Intelligence and Statistics AISTATS,
    Fort Lauderdale, Florida, USA, 2017. (168 out of 530, 32% acceptance rate)

2016

  • Viktoriia Sharmanska and Novi Quadrianto.
    Learning from the Mistakes of Others: Matching Errors in Cross Dataset Learning. IEEE Conference on Computer Vision and Pattern Recognition CVPR,
    Las Vegas, Nevada, USA, 2016. (9.7% acceptance rate)
  • Pietro Galliani and Amir Dezfouli and Edwin V. Bonilla and Novi Quadrianto.
    Gray-box Inference for Structured Gaussian Process Models. arXiv:1609.04289
  • Chao Chen and Novi Quadrianto.
    Clustering High Dimensional Categorical Data via Topographical Features. International Conference on Machine Learning ICML,
    New York City, USA, 2016. (322 out of 1327, 24.26% acceptance rate)
  • Viktoriia Sharmanska, Daniel Hernández-Lobato, Jose Miguel Hernández-Lobato, and Novi Quadrianto.
    Ambiguity Helps: Classification with Disagreements in Crowdsourced Annotations. IEEE Conference on Computer Vision and Pattern Recognition CVPR,
    Las Vegas, Nevada, USA, 2016. (29.9% acceptance rate)
  • Joseph Taylor, Viktoriia Sharmanska, Kristian Kersting, David Weir and Novi Quadrianto.
    Learning using Unselected Features (LUFe). International Joint Conference on Artificial Intelligence IJCAI,
    New York City, USA, 2016 (an acceptance rate below 25%)
  • Viktoriia Sharmanska and Novi Quadrianto.
    In the Era of Deep Convolutional Features: Are Attributes still Useful Privileged Data? Visual Attributes,
    Rogerio Feris, Devi Parikh, Christoph H. Lampert (Eds.), Springer, 2016

2015

  • Novi Quadrianto and Zoubin Ghahramani.
    A Very Simple Safe-Bayesian Random Forest. IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI,
    vol. 37 (6), pp. 1297-1303, 2015.
  • Anastasia Pentina, Viktoriia Sharmanska, Christoph H. Lampert.
    Curriculum Learning of Multiple Tasks. IEEE Conference on Computer Vision and Pattern Recognition CVPR,
    Boston, USA, 2015.
  • Sébastien Bratières, Novi Quadrianto, Zoubin Ghahramani.
    GPStruct: Bayesian Structured Prediction using Gaussian Processes. IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI,
    vol. 37 (7), pp. 1514-1520, 2015.
  • Stephane Gaubert, Zheng Qu, Srinivas Sridharan.
    Maximizing concave piecewise affine functions on the unitary group. Optimization Letters, 2015
    [Link]

2014

  • Daniel Hernández-Lobato, Viktoriia Sharmanska, Kristian Kersting, Christoph H. Lampert, Novi Quadrianto.
    Mind the Nuisance: Gaussian Process Classification using Privileged Noise. Neural Information Processing Systems NIPS,
    Montreal, Quebec, Canada, 2014. (414 out of 1678, 24.67% acceptance rate)
    arXiv:1407.0179 [stat.ML]
  • Sébastien Bratières, Novi Quadrianto, Sebastian Nowozin, Zoubin Ghahramani.
    Scalable Gaussian Process Structured Prediction for Grid Factor Graph Applications. International Conference on Machine Learning ICML,
    Beijing, China, 2014. (310 out of 1238, 25% acceptance rate)
    [PDF] [Supp]
  • Viktoriia Sharmanska, Novi Quadrianto, Christoph H. Lampert.
    Learning to Transfer Privileged Information.
    arXiv:1410.0389 [cs.CV]

2013

  • Viktoriia Sharmanska, Novi Quadrianto, Christoph H. Lampert.
    Learning to Rank Using Privileged Information. International Conference on Computer Vision ICCV,
    Sydney, Australia, 2013. (454 out of 1629, 27.8% acceptance rate)
    [PDF]
  • Sébastien Bratières, Novi Quadrianto, Zoubin Ghahramani.
    Bayesian Structured Prediction using Gaussian Processes.
    [arXiv:1307.3846]
  • Novi Quadrianto, Viktoriia Sharmanska, David A. Knowles, Zoubin Ghahramani.
    The Supervised IBP: Neighbourhood Preserving Infinite Latent Feature Models. Uncertainty in Artificial Intelligence UAI,
    Bellevue, Washington, USA, 2013. (73 out of 233, 31% acceptance rate)
    [PDF][Poster]

2012

  • Novi Quadrianto, Chao Chen, Christoph H. Lampert.
    The Most Persistent Soft-Clique in a Set of Sampled Graphs. International Conference on Machine Learning ICML,
    Edinburgh, Scotland, UK, 2012. (243 out of 890, 27.3% acceptance rate)
    [PDF][Bibtex] [Poster] [Talk] [Code]
  • Viktoriia Sharmanska, Novi Quadrianto, Christoph H. Lampert.
    Augmented Attribute Representations.European Conference on Computer Vision ECCV,
    Firenze, Italy, 2012.
    [PDF] [Bibtex]
  • Tatiana Tommasi, Novi Quadrianto, Barbara Caputo, Christoph H. Lampert.
    Beyond Dataset Bias: Multi-task Unaligned Shared Knowledge Transfer. Asian Conference on Computer Vision ACCV,
    Daejeon, Korea, 2012. (31 out of 869, 3.6% acceptance rate)
    [PDF]

2011

  • Novi Quadrianto.
    Learning for the Internet: Kernel Embeddings and Optimisation. PhD Thesis,
    Australian National University, 2011.
    [PDF] [Bibtex]
  • Novi Quadrianto and Christoph H. Lampert.
    Learning Multi-View Neighborhood Preserving Projections. International Conference on Machine Learning ICML,
    Bellevue, Washington, USA, 2011. (152 out of 589, 25.8% acceptance rate)
    [PDF] [Bibtex] [Poster] [Talk]
  • Novi Quadrianto and Christoph H. Lampert.
    Kernel-based Learning. Encyclopedia of Systems Biology, Werner Dubitzky, Olaf Wolkenhauer, Kwang-Hyun Cho, Hiroki Yokota (Eds.), Springer
    [Link]

2010

  • Novi Quadrianto, Alex J. Smola, Le Song, Tinne Tuytelaars.
    Kernelized Sorting. IEEE Trans. on Pattern Analysis and Machine Intelligence PAMI,
    vol. 32(10), pp. 1809-1821, 2010.
    [PDF] [Bibtex]
  • W. P. Malcolm, Novi Quadrianto, Lakhdar Aggoun.
    State Estimation Schemes for Independent Component Coupled Hidden Markov Models. Journal of Stochastic Analysis and Applications, vol. 28(3), pp. 430-446, 2010.
    [PDF] [Bibtex]
  • Novi Quadrianto, Alex J. Smola, Tiberio S. Caetano, S.V.N. Vishwanathan, James Petterson.
    Multitask Learning without Label Correspondences. Advances in Neural Information Processing Systems NIPS 23,
    Vancouver, B.C., Canada, 2010. (accepted, 293 out of 1219, 24% acceptance rate)
    [PDF] [Bibtex] [Poster]
  • Gilbert Leung, Novi Quadrianto, Alex J. Smola, Kostas Tsioutsiouliklis.
    Optimal Web-scale Tiering as a Flow Problem. Advances in Neural Information Processing Systems NIPS 23,
    Vancouver, B.C., Canada, 2010. (accepted, 293 out of 1219, 24% acceptance rate)
    [PDF] [Bibtex] [Poster]
  • Novi Quadrianto, Kristian Kersting, Tinne Tuytelaars, Wray L. Buntine.
    Beyond 2D-Grids: A Dependence Maximization View on Image Browsing. ACM International Conference on Multimedia Information Retrieval MIR,
    2010. (29% acceptance rate)
    [PDF] [Bibtex] [Poster]
  • Novi Quadrianto, Dale Schuurmans, Alex J. Smola.
    Distributed Flow Algorithms for Scalable Similarity Visualization. ICDM Workshop on Optimization Based Methods for Emerging Data Mining Problems,
    2010.
    [PDF]
  • Novi Quadrianto, Kristian Kersting, Zhao Xu.
    Gaussian Processes. Encyclopedia of Machine Learning, Claude Sammut and Geoff Webb (Eds.), Springer
    [Link]
  • Novi Quadrianto and Wray L. Buntine.
    Regression. Encyclopedia of Machine Learning, Claude Sammut and Geoff Webb (Eds.), Springer
    [Link]
  • Novi Quadrianto and Wray L. Buntine.
    Linear Regression. Encyclopedia of Machine Learning, Claude Sammut and Geoff Webb (Eds.), Springer
    [Link]
  • Novi Quadrianto and Wray L. Buntine.
    Linear Discriminant. Encyclopedia of Machine Learning,Claude Sammut and Geoff Webb (Eds.), Springer
    [Link]

2009

  • Novi Quadrianto, Alex J. Smola, Tiberio S. Caetano, Quoc V. Le.
    Estimating Labels from Label Proportions. Journal of Machine Learning Research JMLR,
    10:2349-2374, 2009.
    [PDF] [Bibtex]
  • Novi Quadrianto, James Petterson, Alex J. Smola.
    Distribution Matching for Transduction. Advances in Neural Information Processing Systems NIPS 22,
    Vancouver, B.C., Canada, 2009. (accepted, 263 out of 1105, 24% acceptance rate)
    [PDF] [Bibtex] [Poster]
  • Novi Quadrianto, Tiberio S. Caetano, John Lim, Dale Schuurmans.
    Convex Relaxation of Mixture Regression with Efficient Algorithms. Advances in Neural Information Processing Systems NIPS 22,
    Vancouver, B.C., Canada, 2009. (accepted, 263 out of 1105, 24% acceptance rate)
    [PDF] [Bibtex] [Poster]
  • Novi Quadrianto, Kristian Kersting, Mark D. Reid, Tiberio S. Caetano, Wray L. Buntine.
    Kernel Conditional Quantile Estimation via Reduction Revisited. IEEE International Conference on Data Mining ICDM,
    Miami Beach, Florida, USA, 2009. (accepted, 140 out of 786, 18% acceptance rate)
    [PDF] [Bibtex] [Talk]
  • Akshay Asthana, Roland Goecke, Novi Quadrianto, Tom Gedeon.
    Learning based Automatic Face Annotation for Arbitrary Poses and Expressions from Frontal Images Only.
    IEEE Computer Society Conference on Computer Vision and Pattern Recognition CVPR,
    Miami Beach, Florida, USA, 2009. (accepted, 383 out of 1464, 26.2% acceptance rate)
    [PDF] [Bibtex]

2008

  • Novi Quadrianto, Le Song, Alex J. Smola.
    Kernelized Sorting. Advances in Neural Information Processing Systems NIPS 21,
    Vancouver, B.C., Canada, 2008. (accepted as spotlight, 123 out of 1022, 12% acceptance rate)
    [PDF] [Bibtex] [Appendix] [Spotlight] [Poster] [Code]
  • Novi Quadrianto, Alex J. Smola, Tiberio S. Caetano, Quoc V. Le.
    Estimating Labels from Label Proportions.International Conference on Machine Learning ICML,
    Helsinki, Finland, 2008. (155 out of 583, 26.5% acceptance rate)
    [PDF] [Bibtex] [Poster]

2007

  • Novi Quadrianto, Guan Cuntai, Tran Huy Dat, Xue Ping.
    Sub-Band Common Spatial Pattern (SBCSP) for Brain-Computer Interface. The 3rd International IEEE EMBS Conference on Neural Engineering,
    Hawaii, USA, 2007. (accepted as oral)
    [PDF] [Bibtex]