determinantal point process

Scalable Sampling for Nonsymmetric Determinantal Point Processes ICLR 2022 Unbiased estimators for random design regression JMLR 2022 An analysis of Ermakov-Zolotukhin quadrature using kernels NeurIPS 2021 ARMOURED: Adversarially Robust MOdels using Unlabeled data by REgularizing Diversity ICLR 2021 Determinantal Beam Search ACL 2021 Determinantal point processes based on orthogonal polynomials for sampling minibatches in SGD NeurIPS 2021 Diversity-Aware Batch Active Learning for Dependency Parsing NAACL 2021 Efficient Balanced Treatment Assignments for Experimentation AISTATS 2021 GIBBON: General-purpose Information-Based Bayesian Optimisation JMLR 2021 How Certain is Your Transformer? EACL 2021 Modelling Behavioural Diversity for Learning in Open-Ended Games ICML 2021 Nonparametric estimation of continuous DPPs with kernel methods NeurIPS 2021 On the Convex Combination of Determinantal Point Processes ACML 2021 Probabilistic Generating Circuits ICML 2021 Regularized Submodular Maximization at Scale ICML 2021 Statistical mechanical analysis of neural network pruning UAI 2021 Submodular + Concave NeurIPS 2021 Unconstrained MAP Inference, Exponentiated Determinantal Point Processes, and Exponential Inapproximability AISTATS 2021 Adaptive Sampling for Stochastic Risk-Averse Learning NeurIPS 2020 A determinantal point process for column subset selection JMLR 2020 Bayesian experimental design using regularized determinantal point processes AISTATS 2020 Better Highlighting: Creating Sub-Sentence Summary Highlights EMNLP 2020 Convergence Analysis of Block Coordinate Algorithms with Determinantal Sampling AISTATS 2020 Debiasing Distributed Second Order Optimization with Surrogate Sketching and Scaled Regularization NeurIPS 2020 Deep Learning of Determinantal Point Processes via Proper Spectral Sub-gradient ICLR 2020