Zobrazeno 1 - 10
of 7 661
pro vyhledávání: '"Citovsky"'
Autor:
Fahrbach, Matthew, Ramalingam, Srikumar, Zadimoghaddam, Morteza, Ahmadian, Sara, Citovsky, Gui, DeSalvo, Giulia
We propose a novel subset selection task called min-distance diverse data summarization ($\textsf{MDDS}$), which has a wide variety of applications in machine learning, e.g., data sampling and feature selection. Given a set of points in a metric spac
Externí odkaz:
http://arxiv.org/abs/2405.18754
Autor:
Ye, Ke, Jiang, Heinrich, Rostamizadeh, Afshin, Chakrabarti, Ayan, DeSalvo, Giulia, Kagy, Jean-François, Karydas, Lazaros, Citovsky, Gui, Kumar, Sanjiv
Pre-training large language models is known to be extremely resource intensive and often times inefficient, under-utilizing the information encapsulated in the training text sequences. In this paper, we present SpacTor, a new training procedure consi
Externí odkaz:
http://arxiv.org/abs/2401.13160
Autor:
Citovsky, Gui, DeSalvo, Giulia, Kumar, Sanjiv, Ramalingam, Srikumar, Rostamizadeh, Afshin, Wang, Yunjuan
We present a subset selection algorithm designed to work with arbitrary model families in a practical batch setting. In such a setting, an algorithm can sample examples one at a time but, in order to limit overhead costs, is only able to update its s
Externí odkaz:
http://arxiv.org/abs/2301.12052
Autor:
Trewavas, Anthony
Publikováno v:
The Quarterly Review of Biology, 2012 Sep . 87(3), 268-269.
Externí odkaz:
https://www.jstor.org/stable/10.1086/666800
Autor:
Citovsky, Gui, DeSalvo, Giulia, Gentile, Claudio, Karydas, Lazaros, Rajagopalan, Anand, Rostamizadeh, Afshin, Kumar, Sanjiv
The ability to train complex and highly effective models often requires an abundance of training data, which can easily become a bottleneck in cost, time, and computational resources. Batch active learning, which adaptively issues batched queries to
Externí odkaz:
http://arxiv.org/abs/2107.14263
Autor:
Sumengen, Baris, Rajagopalan, Anand, Citovsky, Gui, Simcha, David, Bachem, Olivier, Mitra, Pradipta, Blasiak, Sam, Liang, Mason, Kumar, Sanjiv
Hierarchical Agglomerative Clustering (HAC) is one of the oldest but still most widely used clustering methods. However, HAC is notoriously hard to scale to large data sets as the underlying complexity is at least quadratic in the number of data poin
Externí odkaz:
http://arxiv.org/abs/2105.11653
Autor:
Vainstein, Danny, Chatziafratis, Vaggos, Citovsky, Gui, Rajagopalan, Anand, Mahdian, Mohammad, Azar, Yossi
Recently, Hierarchical Clustering (HC) has been considered through the lens of optimization. In particular, two maximization objectives have been defined. Moseley and Wang defined the \emph{Revenue} objective to handle similarity information given by
Externí odkaz:
http://arxiv.org/abs/2101.10639
Publikováno v:
Communications Biology, Vol 6, Iss 1, Pp 1-11 (2023)
The plant histone deubiquitinase, OTLD1, interacts with the Arabidopsis transcription factor, LSH10, and both transcriptionally regulate a set of common target genes.
Externí odkaz:
https://doaj.org/article/b63e6032c1cf4b6f8e3061b1bc6fa584
Publikováno v:
In Heliyon September 2023 9(9)
Publikováno v:
Science signaling [Sci Signal] 2017 Jul 11; Vol. 10 (487). Date of Electronic Publication: 2017 Jul 11.