distributed algorithm

Agent-based Substructure Counting under Local Differential Privacy ACL 2026 Pessimism Principle Can Be Effective: Towards a Framework for Zero-Shot Transfer Reinforcement Learning ICML 2025 Towards Explaining the Power of Constant-depth Graph Neural Networks for Structured Linear Programming ICLR 2025 Distributed Kernel-Driven Data Clustering JMLR 2024 Distributed Least Squares in Small Space via Sketching and Bias Reduction NeurIPS 2024 Massively Parallel Single-Source SimRanks in O(log N) Rounds IJCAI 2024 Optimal Private and Communication Constraint Distributed Goodness-of-Fit Testing for Discrete Distributions in the Large Sample Regime NeurIPS 2024 Recovery Guarantees for Distributed-OMP AISTATS 2024 Asynchronous Communication Aware Multi-Agent Task Allocation IJCAI 2023 DASH: A Distributed and Parallelizable Algorithm for Size-Constrained Submodular Maximization AAAI 2023 Distributed Algorithms for U-statistics-based Empirical Risk Minimization JMLR 2023 Fast Algorithms for Distributed k-Clustering with Outliers ICML 2023 Fast Distributed k-Means with a Small Number of Rounds AISTATS 2023 Taming graph kernels with random features ICML 2023 Adapting k-means Algorithms for Outliers ICML 2022 A Regret Minimization Approach to Multi-Agent Control ICML 2022 DGD^2: A Linearly Convergent Distributed Algorithm For High-dimensional Statistical Recovery NeurIPS 2022 Distributed Optimisation and Deconstruction of Bridges by Self-Assembling Robots RSS 2022 Fast Algorithms for Packing Proportional Fairness and its Dual NeurIPS 2022 Learning Distributed and Fair Policies for Network Load Balancing as Markov Potential Game NeurIPS 2022 Optimal Algorithms for Decentralized Stochastic Variational Inequalities NeurIPS 2022 Private and Communication-Efficient Algorithms for Entropy Estimation NeurIPS 2022 Shard Systems: Scalable, Robust and Persistent Multi-Agent Path Finding with Performance Guarantees AAAI 2022 A Law of Iterated Logarithm for Multi-Agent Reinforcement Learning NeurIPS 2021 Asynchronous Optimization Methods for Efficient Training of Deep Neural Networks with Guarantees AAAI 2021