Mathematics & Optimization

Computing Diverse Shortest Paths Efficiently: A Theoretical and Experimental Study AAAI 2022 Computing Wasserstein-p Distance Between Images With Linear Cost CVPR 2022 Conditional Gradients for the Approximately Vanishing Ideal AISTATS 2022 Conditional Loss and Deep Euler Scheme for Time Series Generation AAAI 2022 Confident Approximate Policy Iteration for Efficient Local Planning in q^π-realizable MDPs NeurIPS 2022 Conflict-Based Steiner Search for Multi-Agent Combinatorial Path Finding RSS 2022 Conformal Frequency Estimation with Sketched Data NeurIPS 2022 Conformalized Fairness via Quantile Regression NeurIPS 2022 Congested Bandits: Optimal Routing via Short-term Resets ICML 2022 Consensus Multiplicative Weights Update: Learning to Learn using Projector-based Game Signatures ICML 2022 CoNSoLe: Convex Neural Symbolic Learning NeurIPS 2022 Constrained Discrete Black-Box Optimization using Mixed-Integer Programming ICML 2022 Constrained Langevin Algorithms with L-mixing External Random Variables NeurIPS 2022 Constrained Optimization with Dynamic Bound-scaling for Effective NLP Backdoor Defense ICML 2022 Constrained Prescriptive Trees via Column Generation AAAI 2022 Constrained Stochastic Nonconvex Optimization with State-dependent Markov Data NeurIPS 2022 Construction Repetition Reduces Information Rate in Dialogue AACL 2022 Context-Based Dynamic Pricing with Partially Linear Demand Model NeurIPS 2022 Contextual Bandits with Knapsacks for a Conversion Model NeurIPS 2022 Contextual Bandits with Large Action Spaces: Made Practical ICML 2022 Contextual Bandits with Smooth Regret: Efficient Learning in Continuous Action Spaces ICML 2022 Contextual Dynamic Pricing with Unknown Noise: Explore-then-UCB Strategy and Improved Regrets NeurIPS 2022 Contextual Information-Directed Sampling ICML 2022 Continuous Deep Q-Learning in Optimal Control Problems: Normalized Advantage Functions Analysis NeurIPS 2022 Continuously Tempered PDMP samplers NeurIPS 2022