Papers
Tensor Train Decomposition on TensorFlow (T3F)
Alexander Novikov, Pavel Izmailov, Valentin Khrulkov et al.
The Error-Feedback framework: SGD with Delayed Gradients
Sebastian U. Stich, Sai Praneeth Karimireddy
The Kalai-Smorodinsky solution for many-objective Bayesian optimization
Mickael Binois, Victor Picheny, Patrick Taillandier et al.
The Maximum Separation Subspace in Sufficient Dimension Reduction with Categorical Response
Xin Zhang, Qing Mai, Hui Zou
The Optimal Ridge Penalty for Real-world High-dimensional Data Can Be Zero or Negative due to the Implicit Ridge Regularization
Dmitry Kobak, Jonathan Lomond, Benoit Sanchez
Theory of Curriculum Learning, with Convex Loss Functions
Daphna Weinshall, Dan Amir
The weight function in the subtree kernel is decisive
Romain Azaïs, Florian Ingels
ThunderGBM: Fast GBDTs and Random Forests on GPUs
Zeyi Wen, Hanfeng Liu, Jiashuai Shi et al.
Topology of Deep Neural Networks
Gregory Naitzat, Andrey Zhitnikov, Lek-Heng Lim
Towards the Systematic Reporting of the Energy and Carbon Footprints of Machine Learning
Peter Henderson, Jieru Hu, Joshua Romoff et al.
Trust-Region Variational Inference with Gaussian Mixture Models
Oleg Arenz, Mingjun Zhong, Gerhard Neumann
Tslearn, A Machine Learning Toolkit for Time Series Data
Romain Tavenard, Johann Faouzi, Gilles Vandewiele et al.
Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly
Kirthevasan Kandasamy, Karun Raju Vysyaraju, Willie Neiswanger et al.
Two-Stage Approach to Multivariate Linear Regression with Sparsely Mismatched Data
Martin Slawski, Emanuel Ben-David, Ping Li
Ultra-High Dimensional Single-Index Quantile Regression
Yuankun Zhang, Heng Lian, Yan Yu
Union of Low-Rank Tensor Spaces: Clustering and Completion
Morteza Ashraphijuo, Xiaodong Wang
Unique Sharp Local Minimum in L1-minimization Complete Dictionary Learning
Yu Wang, Siqi Wu, Bin Yu
Universal Latent Space Model Fitting for Large Networks with Edge Covariates
Zhuang Ma, Zongming Ma, Hongsong Yuan
Variational Inference for Computational Imaging Inverse Problems
Francesco Tonolini, Jack Radford, Alex Turpin et al.
Weighted Message Passing and Minimum Energy Flow for Heterogeneous Stochastic Block Models with Side Information
T. Tony Cai, Tengyuan Liang, Alexander Rakhlin
Wide Neural Networks with Bottlenecks are Deep Gaussian Processes
Devanshu Agrawal, Theodore Papamarkou, Jacob Hinkle
WONDER: Weighted One-shot Distributed Ridge Regression in High Dimensions
Edgar Dobriban, Yue Sheng
A Bootstrap Method for Error Estimation in Randomized Matrix Multiplication
Miles E. Lopes, Shusen Wang, Michael W. Mahoney
Accelerated Alternating Projections for Robust Principal Component Analysis
HanQin Cai, Jian-Feng Cai, Ke Wei