Zobrazeno 1 - 10
of 346
pro vyhledávání: '"DasGupta, Anirban"'
While coresets have been growing in terms of their application, barring few exceptions, they have mostly been limited to unsupervised settings. We consider supervised classification problems, and non-decomposable evaluation measures in such settings.
Externí odkaz:
http://arxiv.org/abs/2312.09885
Optical Character Recognition (OCR) technology finds applications in digitizing books and unstructured documents, along with applications in other domains such as mobility statistics, law enforcement, traffic, security systems, etc. The state-of-the-
Externí odkaz:
http://arxiv.org/abs/2307.04245
In this paper, we propose localized versions of Weisfeiler-Leman (WL) algorithms in an effort to both increase the expressivity, as well as decrease the computational overhead. We focus on the specific problem of subgraph counting and give localized
Externí odkaz:
http://arxiv.org/abs/2305.19659
Autor:
Portnoy, Stephen, DasGupta, Anirban
Portnoy (2019) considered the problem of constructing an optimal confidence interval for the mean based on a single observation $\, X \sim {\cal{N}}(\mu , \, \sigma^2) \,$. Here we extend this result to obtaining 1-sample confidence intervals for $\,
Externí odkaz:
http://arxiv.org/abs/2202.03556
Publikováno v:
In BBA - Gene Regulatory Mechanisms September 2024 1867(3)
Curriculum learning is a training strategy that sorts the training examples by some measure of their difficulty and gradually exposes them to the learner to improve the network performance. Motivated by our insights from implicit curriculum ordering,
Externí odkaz:
http://arxiv.org/abs/2103.00147
Low-latency gravitational wave search pipelines such as GstLAL take advantage of low-rank factorization of the template matrix via singular value decomposition (SVD). With unprecedented improvements in detector bandwidth and sensitivity in advanced-L
Externí odkaz:
http://arxiv.org/abs/2101.03226
We present algorithms that create coresets in an online setting for clustering problems according to a wide subset of Bregman divergences. Notably, our coresets have a small additive error, similar in magnitude to the lightweight coresets Bachem et.
Externí odkaz:
http://arxiv.org/abs/2012.06522
A real-valued set function is (additively) approximately submodular if it satisfies the submodularity conditions with an additive error. Approximate submodularity arises in many settings, especially in machine learning, where the function evaluation
Externí odkaz:
http://arxiv.org/abs/2010.02912
We address the problem of large scale real-time classification of content posted on social networks, along with the need to rapidly identify novel spam types. Obtaining manual labels for user-generated content using editorial labeling and taxonomy de
Externí odkaz:
http://arxiv.org/abs/2008.10828