Papers
4,025 papers found
Towards Efficient Data Valuation Based on the Shapley Value
Ruoxi Jia, David Dao, Boxin Wang et al.
Towards Gradient Free and Projection Free Stochastic Optimization
Anit Kumar Sahu, Manzil Zaheer, Soummya Kar
Towards Optimal Transport with Global Invariances
David Alvarez-Melis, Stefanie Jegelka, Tommi S. Jaakkola
Towards Understanding the Generalization Bias of Two Layer Convolutional Linear Classifiers with Gradient Descent
Yifan Wu, Barnabas Poczos, Aarti Singh
Training a Spiking Neural Network with Equilibrium Propagation
Peter O’Connor, Efstratios Gavves, Max Welling
Training Variational Autoencoders with Buffered Stochastic Variational Inference
Rui Shu, Hung Bui, Jay Whang et al.
Truncated Back-propagation for Bilevel Optimization
Amirreza Shaban, Ching-An Cheng, Nathan Hatch et al.
Two-temperature logistic regression based on the Tsallis divergence
Ehsan Amid, Manfred K. Warmuth, Sriram Srinivasan
Unbiased Implicit Variational Inference
Michalis K. Titsias, Francisco Ruiz
Unbiased Smoothing using Particle Independent Metropolis-Hastings
Lawrece Middleton, George Deligiannidis, Arnaud Doucet et al.
Uncertainty Autoencoders: Learning Compressed Representations via Variational Information Maximization
Aditya Grover, Stefano Ermon
Universal Hypothesis Testing with Kernels: Asymptotically Optimal Tests for Goodness of Fit
Shengyu Zhu, Biao Chen, Pengfei Yang et al.
Universal Statistics of Fisher Information in Deep Neural Networks: Mean Field Approach
Ryo Karakida, Shotaro Akaho, Shun-ichi Amari
Unsupervised Alignment of Embeddings with Wasserstein Procrustes
Edouard Grave, Armand Joulin, Quentin Berthet
Variable selection for Gaussian processes via sensitivity analysis of the posterior predictive distribution
Topi Paananen, Juho Piironen, Michael Riis Andersen et al.
Variance reduction properties of the reparameterization trick
Ming Xu, Matias Quiroz, Robert Kohn et al.
Variational Information Planning for Sequential Decision Making
Jason Pacheco, John Fisher
Variational Noise-Contrastive Estimation
Benjamin Rhodes, Michael U. Gutmann
Vine copula structure learning via Monte Carlo tree search
Bo Chang, Shenyi Pan, Harry Joe
Wasserstein regularization for sparse multi-task regression
Hicham Janati, Marco Cuturi, Alexandre Gramfort
What made you do this? Understanding black-box decisions with sufficient input subsets
Brandon Carter, Jonas Mueller, Siddhartha Jain et al.
XBART: Accelerated Bayesian Additive Regression Trees
Jingyu He, Saar Yalov, P. Richard Hahn
Accelerated Stochastic Mirror Descent: From Continuous-time Dynamics to Discrete-time Algorithms
Pan Xu, Tianhao Wang, Quanquan Gu
Accelerated Stochastic Power Iteration
Peng Xu, Bryan He, Christopher De Sa et al.
Achieving the time of 1-NN, but the accuracy of k-NN
Lirong Xue, Samory Kpotufe