unbiased estimator

Bernoulli Race Particle Filters AISTATS 2019 Calibrated Stochastic Gradient Descent for Convolutional Neural Networks AAAI 2019 Complementary-Label Learning for Arbitrary Losses and Models ICML 2019 Correcting the bias in least squares regression with volume-rescaled sampling AISTATS 2019 On two ways to use determinantal point processes for Monte Carlo integration NeurIPS 2019 Processing Megapixel Images with Deep Attention-Sampling Models ICML 2019 Unbiased Smoothing using Particle Independent Metropolis-Hastings AISTATS 2019 Leveraged volume sampling for linear regression NeurIPS 2018 Minibatch Gibbs Sampling on Large Graphical Models ICML 2018 Reverse Iterative Volume Sampling for Linear Regression JMLR 2018 The price of debiasing automatic metrics in natural language evalaution ACL 2018 Learning from Complementary Labels NeurIPS 2017 Markov Chain Truncation for Doubly-Intractable Inference AISTATS 2017 Matrix Norm Estimation from a Few Entries NeurIPS 2017 Toward Efficient and Accurate Covariance Matrix Estimation on Compressed Data ICML 2017 Unbiased estimates for linear regression via volume sampling NeurIPS 2017 Pseudo-Marginal Slice Sampling AISTATS 2016 Gradient Estimation Using Stochastic Computation Graphs NeurIPS 2015 UPAL: Unbiased Pool Based Active Learning AISTATS 2012