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Objective-Based Hierarchical Clustering of Deep Embedding Vectors.

, , and . AAAI, page 9055-9063. AAAI Press, (2021)

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Tree Learning: Optimal Algorithms and Sample Complexity., , , , , and . CoRR, (2023)Objective-Based Hierarchical Clustering of Deep Embedding Vectors., , and . AAAI, page 9055-9063. AAAI Press, (2021)"Bring Your Own Greedy"+Max: Near-Optimal 1/2-Approximations for Submodular Knapsack., , and . AISTATS, volume 108 of Proceedings of Machine Learning Research, page 3263-3274. PMLR, (2020)Adversarially Robust Submodular Maximization under Knapsack Constraints., , , and . KDD, page 148-156. ACM, (2019)Approximation Scheme for Weighted Metric Clustering via Sherali-Adams., , , and . AAAI, page 7926-7934. AAAI Press, (2024)Multi-Dimensional Balanced Graph Partitioning via Projected Gradient Descent., , and . Proc. VLDB Endow., 12 (8): 906-919 (2019)Objective-Based Hierarchical Clustering of Deep Embedding Vectors., , and . CoRR, (2020)Tree Learning: Optimal Sample Complexity and Algorithms., , , , , and . AAAI, page 6701-6708. AAAI Press, (2023)Escaping Saddle Points with Compressed SGD., and . NeurIPS, page 10273-10284. (2021)Federated Learning under Arbitrary Communication Patterns., and . ICML, volume 139 of Proceedings of Machine Learning Research, page 425-435. PMLR, (2021)