Papers
A Unified Framework for Structured Graph Learning via Spectral Constraints
Sandeep Kumar, Jiaxi Ying, José Vinícius de M. Cardoso et al.
A Unified Framework of Online Learning Algorithms for Training Recurrent Neural Networks
Owen Marschall, Kyunghyun Cho, Cristina Savin
A Unified q-Memorization Framework for Asynchronous Stochastic Optimization
Bin Gu, Wenhan Xian, Zhouyuan Huo et al.
Bayesian Closed Surface Fitting Through Tensor Products
Olivier Binette, Debdeep Pati, David B. Dunson
Bayesian Model Selection with Graph Structured Sparsity
Youngseok Kim, Chao Gao
Best Practices for Scientific Research on Neural Architecture Search
Marius Lindauer, Frank Hutter
Beyond Trees: Classification with Sparse Pairwise Dependencies
Yaniv Tenzer, Amit Moscovich, Mary Frances Dorn et al.
Branch and Bound for Piecewise Linear Neural Network Verification
Rudy Bunel, Jingyue Lu, Ilker Turkaslan et al.
Breaking the Curse of Nonregularity with Subagging --- Inference of the Mean Outcome under Optimal Treatment Regimes
Chengchun Shi, Wenbin Lu, Rui Song
Causal Discovery from Heterogeneous/Nonstationary Data
Biwei Huang, Kun Zhang, Jiji Zhang et al.
Causal Discovery Toolbox: Uncovering causal relationships in Python
Diviyan Kalainathan, Olivier Goudet, Ritik Dutta
Chaining Meets Chain Rule: Multilevel Entropic Regularization and Training of Neural Networks
Amir R. Asadi, Emmanuel Abbe
Change Point Estimation in a Dynamic Stochastic Block Model
Monika Bhattacharjee, Moulinath Banerjee, George Michailidis
Communication-Efficient Distributed Optimization in Networks with Gradient Tracking and Variance Reduction
Boyue Li, Shicong Cen, Yuxin Chen et al.
Community-Based Group Graphical Lasso
Eugen Pircalabelu, Gerda Claeskens
Complete Dictionary Learning via L4-Norm Maximization over the Orthogonal Group
Yuexiang Zhai, Zitong Yang, Zhenyu Liao et al.
Conic Optimization for Quadratic Regression Under Sparse Noise
Igor Molybog, Ramtin Madani, Javad Lavaei
Conjugate Gradients for Kernel Machines
Simon Bartels, Philipp Hennig
Connecting Spectral Clustering to Maximum Margins and Level Sets
David P. Hofmeyr
Consistency of Semi-Supervised Learning Algorithms on Graphs: Probit and One-Hot Methods
Franca Hoffmann, Bamdad Hosseini, Zhi Ren et al.
Constrained Dynamic Programming and Supervised Penalty Learning Algorithms for Peak Detection in Genomic Data
Toby Dylan Hocking, Guillem Rigaill, Paul Fearnhead et al.
Contextual Bandits with Continuous Actions: Smoothing, Zooming, and Adapting
Akshay Krishnamurthy, John Langford, Aleksandrs Slivkins et al.
Contextual Explanation Networks
Maruan Al-Shedivat, Avinava Dubey, Eric Xing
Continuous-Time Birth-Death MCMC for Bayesian Regression Tree Models
Reza Mohammadi, Matthew Pratola, Maurits Kaptein
Convergence of Sparse Variational Inference in Gaussian Processes Regression
David R. Burt, Carl Edward Rasmussen, Mark van der Wilk