| 2019 | Online Decentralized Leverage Score Sampling for Streaming Multidimensional Time Series. | Rui Xie, Zengyan Wang, Shuyang Bai, Ping Ma, Wenxuan Zhong |
| 2019 | Lifelong Optimization with Low Regret. | Yi-Shan Wu, Po-An Wang, Chi-Jen Lu |
| 2019 | Towards Understanding the Generalization Bias of Two Layer Convolutional Linear Classifiers with Gradient Descent. | Yifan Wu, Barnabs Pczos, Aarti Singh |
| 2019 | Differentiable Antithetic Sampling for Variance Reduction in Stochastic Variational Inference. | Mike Wu, Noah D. Goodman, Stefano Ermon |
| 2019 | Fast Gaussian process based gradient matching for parameter identification in systems of nonlinear ODEs. | Philippe Wenk, Alkis Gotovos, Stefan Bauer, Nico S. Gorbach, Andreas Krause, Joachim M. Buhmann |
| 2019 | Credit Assignment Techniques in Stochastic Computation Graphs. | Thophane Weber, Nicolas Heess, Lars Buesing, David Silver |
| 2019 | Multitask Metric Learning: Theory and Algorithm. | Boyu Wang, Hejia Zhang, Peng Liu, Zebang Shen, Joelle Pineau |
| 2019 | Stochastic Variance-Reduced Cubic Regularization for Nonconvex Optimization. | Zhe Wang, Yi Zhou, Yingbin Liang, Guanghui Lan |
| 2019 | Generalizing the theory of cooperative inference. | Pei Wang, Pushpi Paranamana, Patrick Shafto |
| 2019 | Computation Efficient Coded Linear Transform. | Sinong Wang, Jiashang Liu, Ness B. Shroff, Pengyu Yang |
| 2019 | Fixing Mini-batch Sequences with Hierarchical Robust Partitioning. | Shengjie Wang, Wenruo Bai, Chandrashekhar Lavania, Jeff A. Bilmes |
| 2019 | Subsampled Renyi Differential Privacy and Analytical Moments Accountant. | Yu-Xiang Wang, Borja Balle, Shiva Prasad Kasiviswanathan |
| 2019 | Improved Semi-Supervised Learning with Multiple Graphs. | Krishnamurthy Viswanathan, Sushant Sachdeva, Andrew Tomkins, Sujith Ravi |
| 2019 | The LORACs Prior for VAEs: Letting the Trees Speak for the Data. | Sharad Vikram, Matthew D. Hoffman, Matthew J. Johnson |
| 2019 | Online Algorithm for Unsupervised Sensor Selection. | Arun Verma, Manjesh Kumar Hanawal, Csaba Szepesvri, Venkatesh Saligrama |
| 2019 | Contrasting Exploration in Parameter and Action Space: A Zeroth-Order Optimization Perspective. | Anirudh Vemula, Wen Sun, J. Andrew Bagnell |
| 2019 | Empirical Risk Minimization and Stochastic Gradient Descent for Relational Data. | Victor Veitch, Morgane Austern, Wenda Zhou, David M. Blei, Peter Orbanz |
| 2019 | Fast and Faster Convergence of SGD for Over-Parameterized Models and an Accelerated Perceptron. | Sharan Vaswani, Francis R. Bach, Mark Schmidt |
| 2019 | Confidence-based Graph Convolutional Networks for Semi-Supervised Learning. | Shikhar Vashishth, Prateek Yadav, Manik Bhandari, Partha P. Talukdar |
| 2019 | Evaluating model calibration in classification. | Juozas Vaicenavicius, David Widmann, Carl R. Andersson, Fredrik Lindsten, Jacob Roll, Thomas B. Schn |
| 2019 | Safe Convex Learning under Uncertain Constraints. | Ilnura Usmanova, Andreas Krause, Maryam Kamgarpour |
| 2019 | Efficient Bayesian Optimization for Target Vector Estimation. | Anders Kirk Uhrenholt, Bjrn Sand Jensen |
| 2019 | Causal Discovery in the Presence of Missing Data. | Ruibo Tu, Cheng Zhang, Paul Ackermann, Karthika Mohan, Hedvig Kjellstrm, Kun Zhang |
| 2019 | Calibrating Deep Convolutional Gaussian Processes. | Gia-Lac Tran, Edwin V. Bonilla, John P. Cunningham, Pietro Michiardi, Maurizio Filippone |
| 2019 | Black Box Quantiles for Kernel Learning. | Anthony Tompkins, Ransalu Senanayake, Philippe Morere, Fabio Ramos |