Mathematics & Optimization

Incentivized Bandit Learning with Self-Reinforcing User Preferences ICML 2021 Incentivizing Compliance with Algorithmic Instruments ICML 2021 Incentivizing Truthfulness Through Audits in Strategic Classification AAAI 2021 Increasing Iterate Averaging for Solving Saddle-Point Problems AAAI 2021 Incremental Learning via Rate Reduction CVPR 2021 In-Database Regression in Input Sparsity Time ICML 2021 Individual Fairness in Kidney Exchange Programs AAAI 2021 Indoor Lighting Estimation Using an Event Camera CVPR 2021 Inductive Mutual Information Estimation: A Convex Maximum-Entropy Copula Approach AISTATS 2021 Inference for Multiple Heterogeneous Networks with a Common Invariant Subspace JMLR 2021 Inference for the Case Probability in High-dimensional Logistic Regression JMLR 2021 Inference In High-dimensional Single-Index Models Under Symmetric Designs JMLR 2021 Inference in Stochastic Epidemic Models via Multinomial Approximations AISTATS 2021 Inference of Black Hole Fluid-Dynamics From Sparse Interferometric Measurements ICCV 2021 Inferring Morphological Complexity from Syntactic Dependency Networks: A Test NAACL 2021 Inferring serial correlation with dynamic backgrounds ICML 2021 Infinite-Dimensional Fisher Markets: Equilibrium, Duality and Optimization AAAI 2021 Infinite-Dimensional Optimization for Zero-Sum Games via Variational Transport ICML 2021 Information-constrained optimization: can adaptive processing of gradients help? NeurIPS 2021 Information Directed Sampling for Sparse Linear Bandits NeurIPS 2021 Information-Theoretic Generalization Bounds for Stochastic Gradient Descent COLT 2021 Instance-Dependent Bounds for Zeroth-order Lipschitz Optimization with Error Certificates NeurIPS 2021 Instance Specific Approximations for Submodular Maximization ICML 2021 Instance-Wise Minimax-Optimal Algorithms for Logistic Bandits AISTATS 2021 Integrated Defense for Resilient Graph Matching ICML 2021