| 2018 | Slow and Stale Gradients Can Win the Race: Error-Runtime Trade-offs in Distributed SGD. | Sanghamitra Dutta, Gauri Joshi, Soumyadip Ghosh, Parijat Dube, Priya Nagpurkar |
| 2018 | Learning Determinantal Point Processes in Sublinear Time. | Christophe Dupuy, Francis R. Bach |
| 2018 | Bayesian Nonparametric Poisson-Process Allocation for Time-Sequence Modeling. | Hongyi Ding, Mohammad Emtiyaz Khan, Issei Sato, Masashi Sugiyama |
| 2018 | Sketching for Kronecker Product Regression and P-splines. | Huaian Diao, Zhao Song, Wen Sun, David P. Woodruff |
| 2018 | Subsampling for Ridge Regression via Regularized Volume Sampling. | Michal Derezinski, Manfred K. Warmuth |
| 2018 | Batch-Expansion Training: An Efficient Optimization Framework. | Michal Derezinski, Dhruv Mahajan, S. Sathiya Keerthi, S. V. N. Vishwanathan, Markus Weimer |
| 2018 | Bootstrapping EM via Power EM and Convergence in the Naive Bayes Model. | Costis Daskalakis, Christos Tzamos, Manolis Zampetakis |
| 2018 | On denoising modulo 1 samples of a function. | Mihai Cucuringu, Hemant Tyagi |
| 2018 | Beating Monte Carlo Integration: a Nonasymptotic Study of Kernel Smoothing Methods. | Stphan Clmenon, Franois Portier |
| 2018 | Parallel and Distributed MCMC via Shepherding Distributions. | Arkabandhu Chowdhury, Christopher M. Jermaine |
| 2018 | The Geometry of Random Features. | Krzysztof Choromanski, Mark Rowland, Tams Sarls, Vikas Sindhwani, Richard E. Turner, Adrian Weller |
| 2018 | Community Detection in Hypergraphs: Optimal Statistical Limit and Efficient Algorithms. | I (Eli) Chien, Chung-Yi Lin, I-Hsiang Wang |
| 2018 | An Optimization Approach to Learning Falling Rule Lists. | Chaofan Chen, Cynthia Rudin |
| 2018 | Metrics for Deep Generative Models. | Nutan Chen, Alexej Klushyn, Richard Kurle, Xueyan Jiang, Justin Bayer, Patrick van der Smagt |
| 2018 | Online Continuous Submodular Maximization. | Lin Chen, Hamed Hassani, Amin Karbasi |
| 2018 | FLAG n' FLARE: Fast Linearly-Coupled Adaptive Gradient Methods. | Xiang Cheng, Fred (Farbod) Roosta, Stefan Palombo, Peter L. Bartlett, Michael W. Mahoney |
| 2018 | Matrix completability analysis via graph k-connectivity. | Dehua Cheng, Natali Ruchansky, Yan Liu |
| 2018 | Convergence of Value Aggregation for Imitation Learning. | Ching-An Cheng, Byron Boots |
| 2018 | Symmetric Variational Autoencoder and Connections to Adversarial Learning. | Liqun Chen, Shuyang Dai, Yunchen Pu, Erjin Zhou, Chunyuan Li, Qinliang Su, Changyou Chen, Lawrence Carin |
| 2018 | Crowdclustering with Partition Labels. | Junxiang Chen, Yale Chang, Peter J. Castaldi, Michael H. Cho, Brian D. Hobbs, Jennifer G. Dy |
| 2018 | Sparse Linear Isotonic Models. | Sheng Chen, Arindam Banerjee |
| 2018 | Near-Optimal Machine Teaching via Explanatory Teaching Sets. | Yuxin Chen, Oisin Mac Aodha, Shihan Su, Pietro Perona, Yisong Yue |
| 2018 | Convergence diagnostics for stochastic gradient descent with constant learning rate. | Jerry Chee, Panos Toulis |
| 2018 | Dropout as a Low-Rank Regularizer for Matrix Factorization. | Jacopo Cavazza, Pietro Morerio, Benjamin D. Haeffele, Connor Lane, Vittorio Murino, Ren Vidal |
| 2018 | Nearly second-order optimality of online joint detection and estimation via one-sample update schemes. | Yang Cao, Liyan Xie, Yao Xie, Huan Xu |