More from the Same Authors

• 2021 Spotlight: Mixture Proportion Estimation and PU Learning:A Modern Approach »
  Saurabh Garg · Yifan Wu · Alexander Smola · Sivaraman Balakrishnan · Zachary Lipton
• 2021 : Benchmarking Multimodal AutoML for Tabular Data with Text Fields »
  Xingjian Shi · Jonas Mueller · Nick Erickson · Mu Li · Alexander Smola
• 2022 : RLSBench: A Large-Scale Empirical Study of Domain Adaptation Under Relaxed Label Shift »
  Saurabh Garg · Nick Erickson · James Sharpnack · Alexander Smola · Sivaraman Balakrishnan · Zachary Lipton
• 2022 Poster: Adaptive Interest for Emphatic Reinforcement Learning »
  Martin Klissarov · Rasool Fakoor · Jonas Mueller · Kavosh Asadi · Taesup Kim · Alexander Smola
• 2022 Poster: Faster Deep Reinforcement Learning with Slower Online Network »
  Kavosh Asadi · Rasool Fakoor · Omer Gottesman · Taesup Kim · Michael Littman · Alexander Smola
• 2022 Poster: Graph Reordering for Cache-Efficient Near Neighbor Search »
  Benjamin Coleman · Santiago Segarra · Alexander Smola · Anshumali Shrivastava
• 2021 Poster: Mixture Proportion Estimation and PU Learning:A Modern Approach »
  Saurabh Garg · Yifan Wu · Alexander Smola · Sivaraman Balakrishnan · Zachary Lipton
• 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 »
  Alexander Smola
• 2017 : TBA11 »
  Alexander Smola
• 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 »
  Alexander Smola
• 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 »
  Yining Wang · Hsiao-Yu Tung · Alexander Smola · Anima Anandkumar
• 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 »
  Hsiao-Yu Tung · Alexander Smola
• 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 »
  Chong Wang · Xi Chen · Alexander Smola · Eric Xing
• 2012 Workshop: Confluence between Kernel Methods and Graphical Models »
  Le Song · Arthur Gretton · Alexander Smola
• 2012 Session: Oral Session 10 »
  Alexander Smola
• 2012 Poster: Learning Networks of Heterogeneous Influence »
  Nan Du · Le Song · Alexander Smola · Ming Yuan
• 2012 Poster: FastEx: Fast Clustering with Exponential Families »
  Amr Ahmed · Sujith Ravi · Shravan M Narayanamurthy · Alexander Smola
• 2012 Spotlight: Learning Networks of Heterogeneous Influence »
  Nan Du · Le Song · Alexander Smola · Ming Yuan
• 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 »
  Novi Quadrianto · Alexander Smola · Tiberio Caetano · S.V.N. Vishwanathan · James Petterson
• 2010 Poster: Parallelized Stochastic Gradient Descent »
  Martin A Zinkevich · Markus Weimer · Alexander Smola · Lihong Li
• 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 »
  Martin A Zinkevich · Alexander Smola · John Langford
• 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 »
  Karsten Borgwardt · Koji Tsuda · Vishwanathan S V N · Xifeng Yan
• 2008 Poster: Kernelized Sorting »
  Novi Quadrianto · Le Song · Alexander Smola
• 2008 Poster: Kernel Measures of Independence for non-iid Data »
  Xinhua Zhang · Le Song · Arthur Gretton · Alexander Smola
• 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 Poster: Robust Near-Isometric Matching via Structured Learning of Graphical Models »
  Julian J McAuley · Tiberio Caetano · Alexander Smola
• 2007 Workshop: Representations and Inference on Probability Distributions »
  Kenji Fukumizu · Arthur Gretton · Alexander Smola
• 2007 Poster: Convex Learning with Invariances »
  Choon Hui Teo · Amir Globerson · Sam T Roweis · Alexander Smola
• 2007 Spotlight: A Kernel Statistical Test of Independence »
  Arthur Gretton · Kenji Fukumizu · Choon Hui Teo · Le Song · Bernhard Schölkopf · Alexander Smola
• 2007 Spotlight: Bundle Methods for Machine Learning »
  Alexander Smola · Vishwanathan S V N · Quoc V Le
• 2007 Poster: COFI RANK - Maximum Margin Matrix Factorization for Collaborative Ranking »
  Markus Weimer · Alexandros Karatzoglou · Quoc V Le · Alexander Smola
• 2007 Oral: Colored Maximum Variance Unfolding »
  Le Song · Alexander Smola · Karsten Borgwardt · Arthur Gretton
• 2007 Poster: Colored Maximum Variance Unfolding »
  Le Song · Alexander Smola · Karsten Borgwardt · Arthur Gretton
• 2007 Poster: A Kernel Statistical Test of Independence »
  Arthur Gretton · Kenji Fukumizu · Choon Hui Teo · Le Song · Bernhard Schölkopf · Alexander Smola
• 2007 Poster: Bundle Methods for Machine Learning »
  Alexander Smola · Vishwanathan S V N · Quoc V Le
• 2007 Spotlight: COFI RANK - Maximum Margin Matrix Factorization for Collaborative Ranking »
  Markus Weimer · Alexandros Karatzoglou · Quoc V Le · Alexander Smola
• 2007 Spotlight: Convex Learning with Invariances »
  Choon Hui Teo · Amir Globerson · Sam T Roweis · Alexander Smola
• 2006 Poster: Fast Computation of Graph Kernels »
  Vishwanathan S V N · Karsten Borgwardt · Nic Schraudolph
• 2006 Poster: A Kernel Method for the Two-Sample-Problem »
  Arthur Gretton · Karsten Borgwardt · Malte J Rasch · Bernhard Schölkopf · Alexander Smola
• 2006 Poster: Fast Iterative Kernel PCA »
  Nic Schraudolph · Simon Günter · Vishwanathan S V N
• 2006 Poster: Correcting Sample Selection Bias by Unlabeled Data »
  Jiayuan Huang · Alexander Smola · Arthur Gretton · Karsten Borgwardt · Bernhard Schölkopf
• 2006 Spotlight: Correcting Sample Selection Bias by Unlabeled Data »
  Jiayuan Huang · Alexander Smola · Arthur Gretton · Karsten Borgwardt · Bernhard Schölkopf
• 2006 Talk: A Kernel Method for the Two-Sample-Problem »
  Arthur Gretton · Karsten Borgwardt · Malte J Rasch · Bernhard Schölkopf · Alexander Smola
• 2006 Poster: implicit Online Learning with Kernels »
  Li Cheng · Vishwanathan S V N · Dale Schuurmans · Shaojun Wang · Terry Caelli