Yaoliang Yu

According to our database1, Yaoliang Yu authored at least 62 papers between 2007 and 2019.

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Bibliography

2019
Convergence Behaviour of Some Gradient-Based Methods on Bilinear Games.
CoRR, 2019

Understanding Adversarial Robustness: The Trade-off between Minimum and Average Margin.
CoRR, 2019

Tails of Triangular Flows.
CoRR, 2019

Distributional Reinforcement Learning for Efficient Exploration.
CoRR, 2019

Sum-of-Squares Polynomial Flow.
CoRR, 2019

Distributional Reinforcement Learning for Efficient Exploration.
Proceedings of the 36th International Conference on Machine Learning, 2019

Sum-of-Squares Polynomial Flow.
Proceedings of the 36th International Conference on Machine Learning, 2019

Least Squares Estimation of Weakly Convex Functions.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Distributed Proximal Gradient Algorithm for Partially Asynchronous Computer Clusters.
J. Mach. Learn. Res., 2018

Deep Homogeneous Mixture Models: Representation, Separation, and Approximation.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Inductive Two-layer Modeling with Parametric Bregman Transfer.
Proceedings of the 35th International Conference on Machine Learning, 2018

Orpheus: Efficient Distributed Machine Learning via System and Algorithm Co-design.
Proceedings of the ACM Symposium on Cloud Computing, 2018

2017
Semantic Pooling for Complex Event Analysis in Untrimmed Videos.
IEEE Trans. Pattern Anal. Mach. Intell., 2017

Generalized Conditional Gradient for Sparse Estimation.
J. Mach. Learn. Res., 2017

Provably noise-robust, regularised k-means clustering.
CoRR, 2017

Convex-constrained Sparse Additive Modeling and Its Extensions.
CoRR, 2017

Convex-constrained Sparse Additive Modeling and Its Extensions.
Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

Bregman Divergence for Stochastic Variance Reduction: Saddle-Point and Adversarial Prediction.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Robust Top-k Multiclass SVM for Visual Category Recognition.
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

Learning Latent Space Models with Angular Constraints.
Proceedings of the 34th International Conference on Machine Learning, 2017

Dropout with Expectation-linear Regularization.
Proceedings of the 5th International Conference on Learning Representations, 2017

Efficient Multiple Instance Metric Learning Using Weakly Supervised Data.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016
Online Learning and Optimization.
Encyclopedia of Algorithms, 2016

Dropout with Expectation-linear Regularization.
CoRR, 2016

Additive Approximations in High Dimensional Nonparametric Regression via the SALSA.
CoRR, 2016

Lighter-Communication Distributed Machine Learning via Sufficient Factor Broadcasting.
Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

Convex Two-Layer Modeling with Latent Structure.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Additive Approximations in High Dimensional Nonparametric Regression via the SALSA.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Closed-Form Training of Mahalanobis Distance for Supervised Clustering.
Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

They are Not Equally Reliable: Semantic Event Search Using Differentiated Concept Classifiers.
Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

On Convergence of Model Parallel Proximal Gradient Algorithm for Stale Synchronous Parallel System.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Scalable and Sound Low-Rank Tensor Learning.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015
Petuum: A New Platform for Distributed Machine Learning on Big Data.
IEEE Trans. Big Data, 2015

Efficient Structured Matrix Rank Minimization.
CoRR, 2015

Distributed Machine Learning via Sufficient Factor Broadcasting.
CoRR, 2015

Searching Persuasively: Joint Event Detection and Evidence Recounting with Limited Supervision.
Proceedings of the 23rd Annual ACM Conference on Multimedia Conference, MM '15, Brisbane, Australia, October 26, 2015

Linear Time Samplers for Supervised Topic Models using Compositional Proposals.
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

Petuum: A New Platform for Distributed Machine Learning on Big Data.
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

Semantic Concept Discovery for Large-Scale Zero-Shot Event Detection.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Complex Event Detection using Semantic Saliency and Nearly-Isotonic SVM.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Minimizing Nonconvex Non-Separable Functions.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014
Generalized Conditional Gradient for Sparse Estimation.
CoRR, 2014

Efficient Structured Matrix Rank Minimization.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2013
Polar Operators for Structured Sparse Estimation.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Better Approximation and Faster Algorithm Using the Proximal Average.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

On Decomposing the Proximal Map.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Characterizing the Representer Theorem.
Proceedings of the 30th International Conference on Machine Learning, 2013

2012
Analysis of Kernel Mean Matching under Covariate Shift
CoRR, 2012

Rank/Norm Regularization with Closed-Form Solutions: Application to Subspace Clustering
CoRR, 2012

Accelerated Training for Matrix-norm Regularization: A Boosting Approach.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

A Polynomial-time Form of Robust Regression.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Convex Multi-view Subspace Learning.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Analysis of Kernel Mean Matching under Covariate Shift.
Proceedings of the 29th International Conference on Machine Learning, 2012

Regularizers versus Losses for Nonlinear Dimensionality Reduction: A Factored View with New Convex Relaxations.
Proceedings of the 29th International Conference on Machine Learning, 2012

2011
Distance metric learning by minimal distance maximization.
Pattern Recognition, 2011

Rank/Norm Regularization with Closed-Form Solutions: Application to Subspace Clustering.
Proceedings of the UAI 2011, 2011

Convex Sparse Coding, Subspace Learning, and Semi-Supervised Extensions.
Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, 2011

2010
Relaxed Clipping: A Global Training Method for Robust Regression and Classification.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

2009
A General Projection Property for Distribution Families.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

2007
Extensions of Manifold Learning Algorithms in Kernel Feature Space.
Proceedings of the Advances in Neural Networks, 2007

Discriminant Analysis with Label Constrained Graph Partition.
Proceedings of the Advances in Neural Networks, 2007

A Novel Facial Feature Point Localization Method on 3D Faces.
Proceedings of the International Conference on Image Processing, 2007


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