Kamu erişimi zorunlu olan makaleler - Nicholas MonathDaha fazla bilgi edinin
Bir yerde sunuluyor: 20
A hierarchical algorithm for extreme clustering
A Kobren, N Monath, A Krishnamurthy, A McCallum
Proceedings of the 23rd ACM SIGKDD international conference on knowledge …, 2017
Zorunlu olanlar: US National Science Foundation, US Department of Defense
Gradient-based hierarchical clustering using continuous representations of trees in hyperbolic space
N Monath, M Zaheer, D Silva, A McCallum, A Ahmed
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019
Zorunlu olanlar: US National Science Foundation
Autoregressive structured prediction with language models
T Liu, Y Jiang, N Monath, R Cotterell, M Sachan
arXiv preprint arXiv:2210.14698, 2022
Zorunlu olanlar: Swiss National Science Foundation
Scalable hierarchical agglomerative clustering
N Monath, KA Dubey, G Guruganesh, M Zaheer, A Ahmed, A McCallum, ...
Proceedings of the 27th ACM SIGKDD Conference on knowledge discovery & data …, 2021
Zorunlu olanlar: US National Science Foundation
Scalable hierarchical clustering with tree grafting
N Monath, A Kobren, A Krishnamurthy, MR Glass, A McCallum
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019
Zorunlu olanlar: US National Science Foundation, Chan Zuckerberg Initiative
Supervised hierarchical clustering with exponential linkage
N Yadav, A Kobren, N Monath, A Mccallum
International Conference on Machine Learning, 6973-6983, 2019
Zorunlu olanlar: US National Science Foundation, Chan Zuckerberg Initiative
Entity linking via explicit mention-mention coreference modeling
D Agarwal, R Angell, N Monath, A McCallum
Proceedings of the 2022 Conference of the North American Chapter of the …, 2022
Zorunlu olanlar: US National Science Foundation, Chan Zuckerberg Initiative
Low resource recognition and linking of biomedical concepts from a large ontology
S Mohan, R Angell, N Monath, A McCallum
Proceedings of the 12th ACM International Conference on Bioinformatics …, 2021
Zorunlu olanlar: US National Science Foundation, Chan Zuckerberg Initiative
Capacity and bias of learned geometric embeddings for directed graphs
M Boratko, D Zhang, N Monath, L Vilnis, KL Clarkson, A McCallum
Advances in Neural Information Processing Systems 34, 16423-16436, 2021
Zorunlu olanlar: US National Science Foundation, US Department of Defense, Chan Zuckerberg …
Compact representation of uncertainty in clustering
C Greenberg, N Monath, A Kobren, P Flaherty, A McGregor, A McCallum
Advances in Neural Information Processing Systems 31, 2018
Zorunlu olanlar: US National Science Foundation, US Department of Defense
Sublinear time approximation of text similarity matrices
A Ray, N Monath, A McCallum, C Musco
Proceedings of the AAAI Conference on Artificial Intelligence 36 (7), 8072-8080, 2022
Zorunlu olanlar: US National Science Foundation
Learning String Alignments for Entity Aliases
A Traylor, N Monath, R Das, A McCallum
NIPS Workshop on Automatic Knowledge Base Construction (AKBC), 2017
Zorunlu olanlar: US National Science Foundation, US Department of Defense
Integrating user feedback under identity uncertainty in knowledge base construction
A Kobren, N Monath, A McCallum
Automated Knowledge Base Construction (AKBC), 2019
Zorunlu olanlar: US National Science Foundation
Interactive correlation clustering with existential cluster constraints
R Angell, N Monath, N Yadav, A McCallum
International Conference on Machine Learning, 703-716, 2022
Zorunlu olanlar: US National Science Foundation, Chan Zuckerberg Initiative
An evaluative measure of clustering methods incorporating hyperparameter sensitivity
S Mishra, N Monath, M Boratko, A Kobren, A McCallum
Proceedings of the AAAI Conference on Artificial Intelligence 36 (7), 7788-7796, 2022
Zorunlu olanlar: US National Science Foundation, US Department of Defense
Event and entity coreference using trees to encode uncertainty in joint decisions
N Yadav, N Monath, R Angell, A McCallum
Proceedings of the Fourth Workshop on Computational Models of Reference …, 2021
Zorunlu olanlar: US National Science Foundation, Chan Zuckerberg Initiative
Exact and approximate hierarchical clustering using A
CS Greenberg, S Macaluso, N Monath, A Dubey, P Flaherty, M Zaheer, ...
Uncertainty in Artificial Intelligence, 2061-2071, 2021
Zorunlu olanlar: US National Science Foundation
Dag-structured clustering by nearest neighbors
N Monath, M Zaheer, KA Dubey, A Ahmed, A McCallum
International Conference on Artificial Intelligence and Statistics, 2854-2862, 2021
Zorunlu olanlar: US National Science Foundation
Cluster trellis: Data structures & algorithms for exact inference in hierarchical clustering
S Macaluso, C Greenberg, N Monath, JA Lee, P Flaherty, K Cranmer, ...
International Conference on Artificial Intelligence and Statistics, 2467-2475, 2021
Zorunlu olanlar: US National Science Foundation
Cluster trellis: Data structures & algorithms for exact inference in hierarchical clustering
C Greenberg, S Macaluso, N Monath, JA Lee, P Flaherty, K Cranmer, ...
AISTATS, 2021
Zorunlu olanlar: US National Science Foundation
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