Papers
8,340 papers found
The Hedge Algorithm on a Continuum
Walid Krichene, Maximilian Balandat, Claire Tomlin et al.
The Kendall and Mallows Kernels for Permutations
Yunlong Jiao, Jean-Philippe Vert
The Ladder: A Reliable Leaderboard for Machine Learning Competitions
Avrim Blum, Moritz Hardt
Theory of Dual-sparse Regularized Randomized Reduction
Tianbao Yang, Lijun Zhang, Rong Jin et al.
The Power of Randomization: Distributed Submodular Maximization on Massive Datasets
Rafael Barbosa, Alina Ene, Huy Nguyen et al.
Threshold Influence Model for Allocating Advertising Budgets
Atsushi Miyauchi, Yuni Iwamasa, Takuro Fukunaga et al.
Towards a Learning Theory of Cause-Effect Inference
David Lopez-Paz, Krikamol Muandet, Bernhard Schölkopf et al.
Towards a Lower Sample Complexity for Robust One-bit Compressed Sensing
Rongda Zhu, Quanquan Gu
Tracking Approximate Solutions of Parameterized Optimization Problems over Multi-Dimensional (Hyper-)Parameter Domains
Katharina Blechschmidt, Joachim Giesen, Soeren Laue
Training Deep Convolutional Neural Networks to Play Go
Christopher Clark, Amos Storkey
Trust Region Policy Optimization
John Schulman, Sergey Levine, Pieter Abbeel et al.
Universal Value Function Approximators
Tom Schaul, Daniel Horgan, Karol Gregor et al.
Un-regularizing: approximate proximal point and faster stochastic algorithms for empirical risk minimization
Roy Frostig, Rong Ge, Sham Kakade et al.
Unsupervised Domain Adaptation by Backpropagation
Yaroslav Ganin, Victor Lempitsky
Unsupervised Learning of Video Representations using LSTMs
Nitish Srivastava, Elman Mansimov, Ruslan Salakhudinov
Variational Generative Stochastic Networks with Collaborative Shaping
Philip Bachman, Doina Precup
Variational Inference for Gaussian Process Modulated Poisson Processes
Chris Lloyd, Tom Gunter, Michael Osborne et al.
Variational Inference with Normalizing Flows
Danilo Rezende, Shakir Mohamed
Vector-Space Markov Random Fields via Exponential Families
Wesley Tansey, Oscar Hernan Madrid Padilla, Arun Sai Suggala et al.
Weight Uncertainty in Neural Network
Charles Blundell, Julien Cornebise, Koray Kavukcuoglu et al.
Yinyang K-Means: A Drop-In Replacement of the Classic K-Means with Consistent Speedup
Yufei Ding, Yue Zhao, Xipeng Shen et al.
A Bayesian Framework for Online Classifier Ensemble
Qinxun Bai, Henry Lam, Stan Sclaroff
A Bayesian Wilcoxon signed-rank test based on the Dirichlet process
Alessio Benavoli, Giorgio Corani, Francesca Mangili et al.
Accelerated Proximal Stochastic Dual Coordinate Ascent for Regularized Loss Minimization
Shai Shalev-Shwartz, Tong Zhang