approximation bound

Fair Division via the Cake-Cutting Share AAAI 2025 Guaranteed Approximation Bounds for Mixed-Precision Neural Operators ICLR 2024 Intrinsic Robustness of Prophet Inequality to Strategic Reward Signaling NeurIPS 2024 Light Unbalanced Optimal Transport NeurIPS 2024 Adaptivity Complexity for Causal Graph Discovery UAI 2023 Limits, approximation and size transferability for GNNs on sparse graphs via graphops NeurIPS 2023 Nonlinear Reconstruction for Operator Learning of PDEs with Discontinuities ICLR 2023 Optimizing Multiple Simultaneous Objectives for Voting and Facility Location AAAI 2023 Quantitative Universal Approximation Bounds for Deep Belief Networks ICML 2023 Recurrent Neural Networks and Universal Approximation of Bayesian Filters AISTATS 2023 Asymptotics of smoothed Wasserstein distances in the small noise regime NeurIPS 2022 Condorcet Relaxation In Spatial Voting AAAI 2021 Adaptive Greedy versus Non-Adaptive Greedy for Influence Maximization AAAI 2020 Concentration of Distortion: The Value of Extra Voters in Randomized Social Choice IJCAI 2020 Convex Representation Learning for Generalized Invariance in Semi-Inner-Product Space ICML 2020 Favorite-Candidate Voting for Eliminating the Least Popular Candidate in a Metric Space AAAI 2020 Simple and sharp analysis of k-means|| ICML 2020 On Making Stochastic Classifiers Deterministic NeurIPS 2019 Efficient Localized Inference for Large Graphical Models IJCAI 2018 Beyond Worst-case: A Probabilistic Analysis of Affine Policies in Dynamic Optimization NeurIPS 2017 k-variates++: more pluses in the k-means++ ICML 2016 Filtered Search for Submodular Maximization with Controllable Approximation Bounds AISTATS 2015 Provable Submodular Minimization using Wolfe's Algorithm NeurIPS 2014 Linear Regression With Random Projections JMLR 2012 Tensor Decomposition for Fast Parsing with Latent-Variable PCFGs NeurIPS 2012