Papers
Model Consistency for Learning with Mirror-Stratifiable Regularizers
Jalal Fadili, Guillaume Garrigos, Jérôme Malick et al.
Subsampled Renyi Differential Privacy and Analytical Moments Accountant
Yu-Xiang Wang, Borja Balle, Shiva Prasad Kasiviswanathan
Lagrange Coded Computing: Optimal Design for Resiliency, Security, and Privacy
Qian Yu, Songze Li, Netanel Raviv et al.
Fast and Faster Convergence of SGD for Over-Parameterized Models and an Accelerated Perceptron
Sharan Vaswani, Francis Bach, Mark Schmidt
Optimal Minimization of the Sum of Three Convex Functions with a Linear Operator
Seyoon Ko, Joong-Ho Won
Bayesian optimisation under uncertain inputs
Rafael Oliveira, Lionel Ott, Fabio Ramos
Towards Efficient Data Valuation Based on the Shapley Value
Ruoxi Jia, David Dao, Boxin Wang et al.
Auto-Encoding Total Correlation Explanation
Shuyang Gao, Rob Brekelmans, Greg Ver Steeg et al.
Online Multiclass Boosting with Bandit Feedback
Daniel T. Zhang, Young Hun Jung, Ambuj Tewari
A Swiss Army Infinitesimal Jackknife
Ryan Giordano, William Stephenson, Runjing Liu et al.
XBART: Accelerated Bayesian Additive Regression Trees
Jingyu He, Saar Yalov, P. Richard Hahn
Hadamard Response: Estimating Distributions Privately, Efficiently, and with Little Communication
Jayadev Acharya, Ziteng Sun, Huanyu Zhang
Are we there yet? Manifold identification of gradient-related proximal methods
Yifan Sun, Halyun Jeong, Julie Nutini et al.
Deep Neural Networks with Multi-Branch Architectures Are Intrinsically Less Non-Convex
Hongyang Zhang, Junru Shao, Ruslan Salakhutdinov
SPONGE: A generalized eigenproblem for clustering signed networks
Mihai Cucuringu, Peter Davies, Aldo Glielmo et al.
Learning to Optimize under Non-Stationarity
Wang Chi Cheung, David Simchi-Levi, Ruihao Zhu
Towards Understanding the Generalization Bias of Two Layer Convolutional Linear Classifiers with Gradient Descent
Yifan Wu, Barnabas Poczos, Aarti Singh
Autoencoding any Data through Kernel Autoencoders
Pierre Laforgue, Stéphan Clémençon, Florence d’Alche-Buc
On the Connection Between Learning Two-Layer Neural Networks and Tensor Decomposition
Marco Mondelli, Andrea Montanari
Conditional Sparse L_p-norm Regression With Optimal Probability
John Hainline, Brendan Juba, Hai S. Le et al.
Universal Statistics of Fisher Information in Deep Neural Networks: Mean Field Approach
Ryo Karakida, Shotaro Akaho, Shun-ichi Amari
Can You Trust This Prediction? Auditing Pointwise Reliability After Learning
Peter Schulam, Suchi Saria
$β^3$-IRT: A New Item Response Model and its Applications
Yu Chen, Telmo Silva Filho, Ricardo B. Prudencio et al.
Learning Invariant Representations with Kernel Warping
Yingyi Ma, Vignesh Ganapathiraman, Xinhua Zhang