Papers
Simultaneous Clustering and Estimation of Heterogeneous Graphical Models
Botao Hao, Will Wei Sun, Yufeng Liu et al.
Reward Maximization Under Uncertainty: Leveraging Side-Observations on Networks
Swapna Buccapatnam, Fang Liu, Atilla Eryilmaz et al.
tick: a Python Library for Statistical Learning, with an emphasis on Hawkes Processes and Time-Dependent Models
Emmanuel Bacry, Martin Bompaire, Philip Deegan et al.
Gaussian Lower Bound for the Information Bottleneck Limit
Amichai Painsky, Naftali Tishby
Catalyst Acceleration for First-order Convex Optimization: from Theory to Practice
Hongzhou Lin, Julien Mairal, Zaid Harchaoui
Weighted SGD for ℓ_p Regression with Randomized Preconditioning
Jiyan Yang, Yin-Lam Chow, Christopher Ré et al.
Sparse Exchangeable Graphs and Their Limits via Graphon Processes
Christian Borgs, Jennifer T. Chayes, Henry Cohn et al.
Estimation of Graphical Models through Structured Norm Minimization
Davoud Ataee Tarzanagh, George Michailidis
A Tight Bound of Hard Thresholding
Jie Shen, Ping Li
An ℓ_∞ Eigenvector Perturbation Bound and Its Application
Jianqing Fan, Weichen Wang, Yiqiao Zhong
The Search Problem in Mixture Models
Avik Ray, Joe Neeman, Sujay Sanghavi et al.
Steering Social Activity: A Stochastic Optimal Control Point Of View
Ali Zarezade, Abir De, Utkarsh Upadhyay et al.
Permuted and Augmented Stick-Breaking Bayesian Multinomial Regression
Quan Zhang, Mingyuan Zhou
Post-Regularization Inference for Time-Varying Nonparanormal Graphical Models
Junwei Lu, Mladen Kolar, Han Liu
Sparse Concordance-assisted Learning for Optimal Treatment Decision
Shuhan Liang, Wenbin Lu, Rui Song et al.
Exact Learning of Lightweight Description Logic Ontologies
Boris Konev, Carsten Lutz, Ana Ozaki et al.
Surprising properties of dropout in deep networks
David P. Helmbold, Philip M. Long
Simple, Robust and Optimal Ranking from Pairwise Comparisons
Nihar B. Shah, Martin J. Wainwright
Nonasymptotic convergence of stochastic proximal point methods for constrained convex optimization
Andrei Patrascu, Ion Necoara
Saturating Splines and Feature Selection
Nicholas Boyd, Trevor Hastie, Stephen Boyd et al.
From Predictive Methods to Missing Data Imputation: An Optimization Approach
Dimitris Bertsimas, Colin Pawlowski, Ying Daisy Zhuo
Active Nearest-Neighbor Learning in Metric Spaces
Aryeh Kontorovich, Sivan Sabato, Ruth Urner
Enhancing Identification of Causal Effects by Pruning
Santtu Tikka, Juha Karvanen
Making Better Use of the Crowd: How Crowdsourcing Can Advance Machine Learning Research
Jennifer Wortman Vaughan