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Partial and Asymmetric Contrastive Learning for Out-of-Distribution Detection in Long-Tailed Recognition


Jul 04, 2022
Haotao Wang, Aston Zhang, Yi Zhu, Shuai Zheng, Mu Li, Alex Smola, Zhangyang Wang

* ICML 2022 

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Mixture Proportion Estimation and PU Learning: A Modern Approach


Nov 01, 2021
Saurabh Garg, Yifan Wu, Alex Smola, Sivaraman Balakrishnan, Zachary C. Lipton

* Spotlight at NeurIPS 2021 

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Tiering as a Stochastic Submodular Optimization Problem


May 16, 2020
Hyokun Yun, Michael Froh, Roshan Makhijani, Brian Luc, Alex Smola, Trishul Chilimbi


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Recognizing Variables from their Data via Deep Embeddings of Distributions


Sep 11, 2019
Jonas Mueller, Alex Smola

* IEEE International Conference on Data Mining (ICDM), 2019 

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Deep Factors for Forecasting


May 28, 2019
Yuyang Wang, Alex Smola, Danielle C. Maddix, Jan Gasthaus, Dean Foster, Tim Januschowski

* Proceedings of Machine Learning Research, Volume 97: International Conference on Machine Learning, 2019 
* http://proceedings.mlr.press/v97/wang19k/wang19k.pdf. arXiv admin note: substantial text overlap with arXiv:1812.00098 

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SysML: The New Frontier of Machine Learning Systems


May 01, 2019
Alexander Ratner, Dan Alistarh, Gustavo Alonso, David G. Andersen, Peter Bailis, Sarah Bird, Nicholas Carlini, Bryan Catanzaro, Jennifer Chayes, Eric Chung, Bill Dally, Jeff Dean, Inderjit S. Dhillon, Alexandros Dimakis, Pradeep Dubey, Charles Elkan, Grigori Fursin, Gregory R. Ganger, Lise Getoor, Phillip B. Gibbons, Garth A. Gibson, Joseph E. Gonzalez, Justin Gottschlich, Song Han, Kim Hazelwood, Furong Huang, Martin Jaggi, Kevin Jamieson, Michael I. Jordan, Gauri Joshi, Rania Khalaf, Jason Knight, Jakub Konečný, Tim Kraska, Arun Kumar, Anastasios Kyrillidis, Aparna Lakshmiratan, Jing Li, Samuel Madden, H. Brendan McMahan, Erik Meijer, Ioannis Mitliagkas, Rajat Monga, Derek Murray, Kunle Olukotun, Dimitris Papailiopoulos, Gennady Pekhimenko, Theodoros Rekatsinas, Afshin Rostamizadeh, Christopher Ré, Christopher De Sa, Hanie Sedghi, Siddhartha Sen, Virginia Smith, Alex Smola, Dawn Song, Evan Sparks, Ion Stoica, Vivienne Sze, Madeleine Udell, Joaquin Vanschoren, Shivaram Venkataraman, Rashmi Vinayak, Markus Weimer, Andrew Gordon Wilson, Eric Xing, Matei Zaharia, Ce Zhang, Ameet Talwalkar


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Deep Factors with Gaussian Processes for Forecasting


Nov 30, 2018
Danielle C. Maddix, Yuyang Wang, Alex Smola

* Third workshop on Bayesian Deep Learning (NeurIPS 2018), Montreal, Canada 

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Efficient Multitask Feature and Relationship Learning


Sep 16, 2018
Han Zhao, Otilia Stretcu, Alex Smola, Geoff Gordon


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Detecting and Correcting for Label Shift with Black Box Predictors


Jul 26, 2018
Zachary C. Lipton, Yu-Xiang Wang, Alex Smola

* Published at the International Conference on Machine Learning (ICML) 2018 

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