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Poster
Bundle Methods for Machine Learning
Alexander Smola · Vishwanathan S V N · Quoc V Le
Author Information
Alexander Smola (Amazon)
**AWS Machine Learning**
Vishwanathan S V N (National ICT Australia)
Quoc V Le (Stanford)
Related Events (a corresponding poster, oral, or spotlight)
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2007 Spotlight: Bundle Methods for Machine Learning »
Tue. Dec 4th 11:20 -- 11:30 PM Room
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2021 Spotlight: Mixture Proportion Estimation and PU Learning:A Modern Approach »
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2021 : Benchmarking Multimodal AutoML for Tabular Data with Text Fields »
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2022 : RLSBench: A Large-Scale Empirical Study of Domain Adaptation Under Relaxed Label Shift »
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2022 Poster: Adaptive Interest for Emphatic Reinforcement Learning »
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2022 Poster: Faster Deep Reinforcement Learning with Slower Online Network »
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2022 Poster: Graph Reordering for Cache-Efficient Near Neighbor Search »
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2021 Poster: Mixture Proportion Estimation and PU Learning:A Modern Approach »
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2021 Poster: Deep Explicit Duration Switching Models for Time Series »
Abdul Fatir Ansari · Konstantinos Benidis · Richard Kurle · Ali Caner Turkmen · Harold Soh · Alexander Smola · Bernie Wang · Tim Januschowski -
2021 Poster: Continuous Doubly Constrained Batch Reinforcement Learning »
Rasool Fakoor · Jonas Mueller · Kavosh Asadi · Pratik Chaudhari · Alexander Smola -
2020 Poster: Fast, Accurate, and Simple Models for Tabular Data via Augmented Distillation »
Rasool Fakoor · Jonas Mueller · Nick Erickson · Pratik Chaudhari · Alexander Smola -
2019 : Invited Talk - Alexander J. Smola - Sets and symmetries »
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2017 : TBA11 »
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2017 Oral: Deep Sets »
Manzil Zaheer · Satwik Kottur · Siamak Ravanbakhsh · Barnabas Poczos · Ruslan Salakhutdinov · Alexander Smola -
2017 Poster: Deep Sets »
Manzil Zaheer · Satwik Kottur · Siamak Ravanbakhsh · Barnabas Poczos · Ruslan Salakhutdinov · Alexander Smola -
2016 Poster: Variance Reduction in Stochastic Gradient Langevin Dynamics »
Kumar Avinava Dubey · Sashank J. Reddi · Sinead Williamson · Barnabas Poczos · Alexander Smola · Eric Xing -
2016 Poster: Proximal Stochastic Methods for Nonsmooth Nonconvex Finite-Sum Optimization »
Sashank J. Reddi · Suvrit Sra · Barnabas Poczos · Alexander Smola -
2015 : Scaling Machine Learning »
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2015 Workshop: Nonparametric Methods for Large Scale Representation Learning »
Andrew G Wilson · Alexander Smola · Eric Xing -
2015 Poster: Fast and Guaranteed Tensor Decomposition via Sketching »
Yining Wang · Hsiao-Yu Tung · Alexander Smola · Anima Anandkumar -
2015 Spotlight: Fast and Guaranteed Tensor Decomposition via Sketching »
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2015 Poster: On Variance Reduction in Stochastic Gradient Descent and its Asynchronous Variants »
Sashank J. Reddi · Ahmed Hefny · Suvrit Sra · Barnabas Poczos · Alexander Smola -
2014 Poster: Communication Efficient Distributed Machine Learning with the Parameter Server »
Mu Li · David G Andersen · Alexander Smola · Kai Yu -
2014 Poster: Spectral Methods for Indian Buffet Process Inference »
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2013 Workshop: Topic Models: Computation, Application, and Evaluation »
David Mimno · Amr Ahmed · Jordan Boyd-Graber · Ankur Moitra · Hanna Wallach · Alexander Smola · David Blei · Anima Anandkumar -
2013 Workshop: Randomized Methods for Machine Learning »
David Lopez-Paz · Quoc V Le · Alexander Smola -
2013 Workshop: Modern Nonparametric Methods in Machine Learning »
Arthur Gretton · Mladen Kolar · Samory Kpotufe · John Lafferty · Han Liu · Bernhard Schölkopf · Alexander Smola · Rob Nowak · Mikhail Belkin · Lorenzo Rosasco · peter bickel · Yue Zhao -
2013 Poster: Variance Reduction for Stochastic Gradient Optimization »
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2012 Workshop: Confluence between Kernel Methods and Graphical Models »
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2012 Session: Oral Session 10 »
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2012 Poster: Learning Networks of Heterogeneous Influence »
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2012 Poster: FastEx: Fast Clustering with Exponential Families »
Amr Ahmed · Sujith Ravi · Shravan M Narayanamurthy · Alexander Smola -
2012 Poster: Large Scale Distributed Deep Networks »
Jeff Dean · Greg Corrado · Rajat Monga · Kai Chen · Matthieu Devin · Quoc V Le · Mark Mao · Marc'Aurelio Ranzato · Andrew Senior · Paul Tucker · Ke Yang · Andrew Y Ng -
2012 Spotlight: Learning Networks of Heterogeneous Influence »
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2011 Workshop: Big Learning: Algorithms, Systems, and Tools for Learning at Scale »
Joseph E Gonzalez · Sameer Singh · Graham Taylor · James Bergstra · Alice Zheng · Misha Bilenko · Yucheng Low · Yoshua Bengio · Michael Franklin · Carlos Guestrin · Andrew McCallum · Alexander Smola · Michael Jordan · Sugato Basu -
2011 Tutorial: Graphical Models for the Internet »
Amr Ahmed · Alexander Smola -
2010 Workshop: Challenges of Data Visualization »
Barbara Hammer · Laurens van der Maaten · Fei Sha · Alexander Smola -
2010 Poster: Word Features for Latent Dirichlet Allocation »
James Petterson · Alexander Smola · Tiberio Caetano · Wray L Buntine · Shravan M Narayanamurthy -
2010 Poster: Optimal Web-Scale Tiering as a Flow Problem »
Gilbert Leung · Novi Quadrianto · Alexander Smola · Kostas Tsioutsiouliklis -
2010 Poster: Multitask Learning without Label Correspondences »
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2010 Poster: Parallelized Stochastic Gradient Descent »
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2009 Workshop: Large-Scale Machine Learning: Parallelism and Massive Datasets »
Alexander Gray · Arthur Gretton · Alexander Smola · Joseph E Gonzalez · Carlos Guestrin -
2009 Poster: Slow Learners are Fast »
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2009 Poster: Distribution Matching for Transduction »
Novi Quadrianto · James Petterson · Alexander Smola -
2008 Workshop: Optimization for Machine Learning »
Suvrit Sra · Sebastian Nowozin · Vishwanathan S V N -
2008 Workshop: Structured Input - Structured Output »
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2008 Poster: Kernelized Sorting »
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2008 Poster: Kernel Measures of Independence for non-iid Data »
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2008 Spotlight: Kernelized Sorting »
Novi Quadrianto · Le Song · Alexander Smola -
2008 Spotlight: Kernel Measures of Independence for non-iid Data »
Xinhua Zhang · Le Song · Arthur Gretton · Alexander Smola -
2008 Poster: Tighter Bounds for Structured Estimation »
Olivier Chapelle · Chuong B Do · Quoc V Le · Alexander Smola · Choon Hui Teo -
2008 Demonstration: High-Accuracy 3D Sensing for Mobile Manipulators »
Stephen Gould · Morgan Quigley · Siddarth Batra · Ellen Klingbiel · Quoc V Le · Andrew Y Ng -
2008 Poster: Robust Near-Isometric Matching via Structured Learning of Graphical Models »
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2007 Workshop: Representations and Inference on Probability Distributions »
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2007 Poster: Convex Learning with Invariances »
Choon Hui Teo · Amir Globerson · Sam T Roweis · Alexander Smola -
2007 Spotlight: A Kernel Statistical Test of Independence »
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2007 Poster: COFI RANK - Maximum Margin Matrix Factorization for Collaborative Ranking »
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2007 Oral: Colored Maximum Variance Unfolding »
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2007 Poster: Colored Maximum Variance Unfolding »
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2007 Poster: A Kernel Statistical Test of Independence »
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2007 Spotlight: COFI RANK - Maximum Margin Matrix Factorization for Collaborative Ranking »
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2007 Demonstration: Elefant »
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2007 Spotlight: Convex Learning with Invariances »
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2006 Poster: Fast Computation of Graph Kernels »
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2006 Poster: A Kernel Method for the Two-Sample-Problem »
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2006 Poster: Fast Iterative Kernel PCA »
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2006 Poster: Correcting Sample Selection Bias by Unlabeled Data »
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2006 Spotlight: Correcting Sample Selection Bias by Unlabeled Data »
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2006 Talk: A Kernel Method for the Two-Sample-Problem »
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2006 Poster: implicit Online Learning with Kernels »
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2006 Poster: Learning to Rank with Nonsmooth Cost Functions »
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