Papers
Robust Discriminative Clustering with Sparse Regularizers
Nicolas Flammarion, Balamurugan Palaniappan, Francis Bach
Scalable Influence Maximization for Multiple Products in Continuous-Time Diffusion Networks
Nan Du, Yingyu Liang, Maria-Florina Balcan et al.
Second-Order Stochastic Optimization for Machine Learning in Linear Time
Naman Agarwal, Brian Bullins, Elad Hazan
Sharp Oracle Inequalities for Square Root Regularization
Benjamin Stucky, Sara van de Geer
Simplifying Probabilistic Expressions in Causal Inference
Santtu Tikka, Juha Karvanen
SnapVX: A Network-Based Convex Optimization Solver
David Hallac, Christopher Wong, Steven Diamond et al.
Soft Margin Support Vector Classification as Buffered Probability Minimization
Matthew Norton, Alexander Mafusalov, Stan Uryasev
Spectral Clustering Based on Local PCA
Ery Arias-Castro, Gilad Lerman, Teng Zhang
Stability of Controllers for Gaussian Process Dynamics
Julia Vinogradska, Bastian Bischoff, Duy Nguyen-Tuong et al.
Stabilized Sparse Online Learning for Sparse Data
Yuting Ma, Tian Zheng
Statistical and Computational Guarantees for the Baum-Welch Algorithm
Fanny Yang, Sivaraman Balakrishnan, Martin J. Wainwright
Statistical Inference with Unnormalized Discrete Models and Localized Homogeneous Divergences
Takashi Takenouchi, Takafumi Kanamori
Stochastic Gradient Descent as Approximate Bayesian Inference
Stephan Mandt, Matthew D. Hoffman, David M. Blei
Stochastic Primal-Dual Coordinate Method for Regularized Empirical Risk Minimization
Yuchen Zhang, Lin Xiao
STORE: Sparse Tensor Response Regression and Neuroimaging Analysis
Will Wei Sun, Lexin Li
Target Curricula via Selection of Minimum Feature Sets: a Case Study in Boolean Networks
Shannon Fenn, Pablo Moscato
Tests of Mutual or Serial Independence of Random Vectors with Applications
Martin Bilodeau, Aurélien Guetsop Nangue
The Impact of Random Models on Clustering Similarity
Alexander J. Gates, Yong-Yeol Ahn
The MADP Toolbox: An Open Source Library for Planning and Learning in (Multi-)Agent Systems
Frans A. Oliehoek, Matthijs T. J. Spaan, Bas Terwijn et al.
Time-Accuracy Tradeoffs in Kernel Prediction: Controlling Prediction Quality
Samory Kpotufe, Nakul Verma
Time for a Change: a Tutorial for Comparing Multiple Classifiers Through Bayesian Analysis
Alessio Benavoli, Giorgio Corani, Janez Demšar et al.
Two New Approaches to Compressed Sensing Exhibiting Both Robust Sparse Recovery and the Grouping Effect
Mehmet Eren Ahsen, Niharika Challapalli, Mathukumalli Vidyasagar
Uniform Hypergraph Partitioning: Provable Tensor Methods and Sampling Techniques
Debarghya Ghoshdastidar, Ambedkar Dukkipati
Variational Particle Approximations
Ardavan Saeedi, Tejas D. Kulkarni, Vikash K. Mansinghka et al.