Zobrazeno 1 - 10
of 34
pro vyhledávání: '"Sugato Basu"'
The area of constrained clustering has been extensively explored by researchers and used by practitioners. Constrained clustering formulations exist for popular algorithms such as k-means, mixture models, and spectral clustering but have several limi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::af80c59e11a8dcd529c679e08ed2917a
http://arxiv.org/abs/2101.02792
http://arxiv.org/abs/2101.02792
Autor:
Wanrong Zhu, Kazoo Sone, Xin Wang, An Yan, Sugato Basu, William Yang Wang, Tsu-Jui Fu, Pradyumna Narayana
Publikováno v:
EACL
Scopus-Elsevier
Scopus-Elsevier
One of the most challenging topics in Natural Language Processing (NLP) is visually-grounded language understanding and reasoning. Outdoor vision-and-language navigation (VLN) is such a task where an agent follows natural language instructions and na
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::34afb2748327ab99c343fc322083fa7e
https://doi.org/10.18653/v1/2021.eacl-main.103
https://doi.org/10.18653/v1/2021.eacl-main.103
Autor:
Sahaana Suri, Peter Bailis, Sugato Basu, Yemao Zeng, Abishek Sethi, Raghuveer Chanda, Girija Narlikar, Christopher Ré, Pradyumna Narayana, Neslihan Bulut
As applications in large organizations evolve, the machine learning (ML) models that power them must adapt the same predictive tasks to newly arising data modalities (e.g., a new video content launch in a social media application requires existing te
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::52a379b278e7935766fed0f090e8eb77
Publikováno v:
Machine Learning and Knowledge Discovery in Databases ISBN: 9783030461492
ECML/PKDD (1)
ECML/PKDD (1)
The area of constrained clustering has been extensively explored by researchers and used by practitioners. Constrained clustering formulations exist for popular algorithms such as k-means, mixture models, and spectral clustering but have several limi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::85b3af08e9e00331ae9b94cb09a5d149
https://doi.org/10.1007/978-3-030-46150-8_4
https://doi.org/10.1007/978-3-030-46150-8_4
Publikováno v:
EMNLP (1)
A major challenge in visually grounded language generation is to build robust benchmark datasets and models that can generalize well in real-world settings. To do this, it is critical to ensure that our evaluation protocols are correct, and benchmark
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9a40f08226759c9a3e2469a4c07144c5
https://doi.org/10.18653/v1/2020.emnlp-main.708
https://doi.org/10.18653/v1/2020.emnlp-main.708
Publikováno v:
WWW (Companion Volume)
Analyzing commercial pages to infer the products or services being offered by a web-based business is a task central to product search, product recommendation, ad placement and other e-commerce tasks. What makes this task challenging is that there ar
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::03dc76f948055b6b99506cac6e66aa2f
https://doi.org/10.1145/3308560.3316608
https://doi.org/10.1145/3308560.3316608
Publikováno v:
BlackboxNLP@EMNLP
How much does “free shipping!” help an advertisement’s ability to persuade? This paper presents two methods for performance attribution: finding the degree to which an outcome can be attributed to parts of a text while controlling for potential
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::06fe7e50ab455fd70e4638ff0fe9847a
https://doi.org/10.18653/v1/w18-5415
https://doi.org/10.18653/v1/w18-5415
Publikováno v:
ICDE
Click-through rate (CTR) is a key signal of relevance for search engine results, both organic and sponsored. CTR of a result has two core components: (a) the probability of examination of a result by a user, and (b) the perceived relevance of the res
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d3ff01faf262f00c8413c4552f27fcac
Publikováno v:
Proceedings of the VLDB Endowment. 2:1426-1437
Classification and regression tree learning on massive datasets is a common data mining task at Google, yet many state of the art tree learning algorithms require training data to reside in memory on a single machine. While more scalable implementati
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ad615ece16a23dd4fb0cef67304c91af
https://doi.org/10.14778/1687553.1687569
https://doi.org/10.14778/1687553.1687569
Publikováno v:
ICML
Semi-supervised clustering algorithms aim to improve clustering results using limited supervision. The supervision is generally given as pairwise constraints; such constraints are natural for graphs, yet most semi-supervised clustering algorithms are
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::10001fdfb81478a170d425238673f56e
https://doi.org/10.1007/s10994-008-5084-4
https://doi.org/10.1007/s10994-008-5084-4