Link label prediction in signed social networks, IJCAI, pp.2591-2597, 2013. ,
Learning a Distance Metric by Empirical Loss Minimization, IJCAI, pp.1186-1191, 2011. ,
Manifold Adaptive Experimental Design for Text Categorization, IEEE Transactions on Knowledge and Data Engineering, vol.24, issue.4, pp.707-719, 2012. ,
Generalization Bounds for Metric and Similarity Learning, 2012. ,
Distance Metric Learning Revisited, ECML/PKDD, pp.283-298, 2012. ,
An empirical evaluation of supervised learning in high dimensions, ICML, pp.96-103, 2008. ,
LIBSVM : a library for support vector machines, ACM Transactions on Intelligent Systems and Technology, vol.2, issue.3, pp.27-27, 2011. ,
Training and Testing Low-degree Polynomial Data Mappings via Linear SVM, Journal of Machine Learning Research, vol.11, pp.1471-1490, 2010. ,
An online algorithm for large scale image similarity learning, NIPS, pp.306-314, 2009. ,
Large-scale behavioral targeting, KDD, 2009. ,
Coresets, sparse greedy approximation, and the Frank-Wolfe algorithm, ACM Transactions on Algorithms, vol.6, issue.4, pp.1-30, 2010. ,
Scaling-up Empirical Risk Minimization: Optimization of Incomplete U-statistics, Journal of Machine Learning Research, vol.17, issue.76, pp.1-36, 2016. ,
Ranking and Empirical Minimization of Ustatistics, Annals of Statistics, vol.36, issue.2, pp.844-874, 2008. ,
Information-theoretic metric learning, ICML, pp.209-216, 2007. ,
LIBLINEAR: A Library for Large Linear Classification, Journal of Machine Learning Research, vol.9, pp.1871-1874, 2008. ,
A Mathematical Introduction to Compressive Sensing, 2013. ,
Experiments with random projections for machine learning, KDD, pp.517-522, 2003. ,
An algorithm for quadratic programming, Naval Research Logistics Quarterly, vol.3, issue.1-2, pp.95-110, 1956. ,
New Analysis and Results for the Conditional Gradient Method, 2013. ,
SOML: Sparse Online Metric Learning with Application to Image Retrieval, AAAI, pp.1206-1212, 2014. ,
Neighbourhood Components Analysis, NIPS, pp.513-520, 2004. ,
Some comments on Wolfe's away step, Mathematical Programming, vol.35, issue.1, pp.110-119, 1986. ,
Is that you? Metric learning approaches for face identification, ICCV, pp.498-505, 2009. ,
URL : https://hal.archives-ouvertes.fr/inria-00439290
Guaranteed Classification via Regularized Similarity Learning, Neural Computation, vol.26, issue.3, pp.497-522, 2014. ,
Result Analysis of the NIPS 2003 Feature Selection Challenge, NIPS, 2004. ,
A Class of Statistics with Asymptotically Normal Distribution, The Annals of Mathematical Statistics, vol.19, issue.3, pp.293-325, 1948. ,
DOI : 10.1007/978-1-4612-0865-5_8
Sparse Convex Optimization Methods for Machine Learning, 2011. ,
Revisiting Frank-Wolfe: Projection-Free Sparse Convex Optimization, ICML, 2013. ,
Learning Low-Dimensional Metrics, NIPS, 2017. ,
Regularized Distance Metric Learning: Theory and Algorithm, NIPS, 2009. ,
Non-linear Metric Learning, NIPS, pp.2582-2590, 2012. ,
, Metric Learning: A Survey. Foundations and Trends in Machine Learning, vol.5, pp.287-364, 2012.
DOI : 10.1561/2200000019
On the Global Linear Convergence of Frank-Wolfe Optimization Variants, NIPS, 2015. ,
URL : https://hal.archives-ouvertes.fr/hal-01248675
An Introduction to Chemoinformatics, 2007. ,
U-Statistics: Theory and Practice, 1990. ,
Robust Structural Metric Learning, ICML, 2013. ,
Similarity Learning for High-Dimensional Sparse Data, AISTATS, pp.653-662, 2015. ,
URL : https://hal.archives-ouvertes.fr/hal-01430854
Low-Rank Similarity Metric Learning in High Dimensions, AAAI, 2015. ,
On the method of bounded differences, vol.141, pp.148-188, 1989. ,
An Efficient Sparse Metric Learning in High-Dimensional Space via l1-Penalized Log-Determinant Regularization, ICML, 2009. ,
DOI : 10.1145/1553374.1553482
URL : http://www.cs.mcgill.ca/~icml2009/papers/46.pdf
An Integrated Framework for High Dimensional Distance Metric Learning and Its Application to Fine-Grained Visual Categorization, 2014. ,
Towards making high dimensional distance metric learning practical, 2015. ,
Learning Sparse Metrics via Linear Programming, KDD, pp.367-373, 2006. ,
DOI : 10.1145/1150402.1150444
Learning a Distance Metric from Relative Comparisons, NIPS, 2003. ,
Probability inequalities for the sum in sampling without replacement, The Annals of Statistics, vol.2, issue.1, pp.39-48, 1974. ,
DOI : 10.1214/aos/1176342611
URL : https://doi.org/10.1214/aos/1176342611
Understanding Machine Learning: From Theory to Algorithms, 2014. ,
Positive Semidefinite Metric Learning Using Boosting-like Algorithms, Journal of Machine Learning Research, vol.13, pp.1007-1036, 2012. ,
Sparse Compositional Metric Learning, AAAI, pp.2078-2084, 2014. ,
URL : https://hal.archives-ouvertes.fr/hal-01430847
Sparse Compositional Local Metric Learning, KDD, 2017. ,
Sample complexity of learning mahalanobis distance metrics, NIPS, 2015. ,
Parametric Local Metric Learning for Nearest Neighbor Classification, NIPS, pp.1610-1618, 2012. ,
Distance Metric Learning for Large Margin Nearest Neighbor Classification, Journal of Machine Learning Research, vol.10, pp.207-244, 2009. ,
High-dimensional Similarity Learning via Dual-sparse Random Projection, IJCAI, 2018. ,
DOI : 10.24963/ijcai.2018/417
URL : https://www.ijcai.org/proceedings/2018/0417.pdf
Distance Metric Learning with Eigenvalue Optimization, Journal of Machine Learning Research, vol.13, pp.1-26, 2012. ,
Sparse Metric Learning via Smooth Optimization, NIPS, pp.2214-2222, 2009. ,
Efficient Stochastic Optimization for Low-Rank Distance Metric Learning, AAAI, 2017. ,