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pro vyhledávání: '"Lee AD"'
The problem of nearest neighbor condensing has enjoyed a long history of study, both in its theoretical and practical aspects. In this paper, we introduce the problem of weighted distance nearest neighbor condensing, where one assigns weights to each
Externí odkaz:
http://arxiv.org/abs/2310.15951
Autor:
Kaufman, Eran, Gottlieb, Lee-Ad
In this work, we consider the task of automated emphasis detection for spoken language. This problem is challenging in that emphasis is affected by the particularities of speech of the subject, for example the subject accent, dialect or voice. To add
Externí odkaz:
http://arxiv.org/abs/2305.07791
Autor:
Schmidt, Arne, Morales-Álvarez, Pablo, Cooper, Lee AD, Newberg, Lee A., Enquobahrie, Andinet, Molina, Rafael, Katsaggelos, Aggelos K.
Publikováno v:
In Medical Image Analysis July 2024 95
Autor:
Gottlieb, Lee-Ad, Kontorovich, Aryeh
We generalize the classical notion of packing a set by balls with identical radii to the case where the radii may be different. The largest number of such balls that fit inside the set without overlapping is called its {\em non-uniform packing number
Externí odkaz:
http://arxiv.org/abs/2008.01581
We initiate a program of average smoothness analysis for efficiently learning real-valued functions on metric spaces. Rather than using the Lipschitz constant as the regularizer, we define a local slope at each point and gauge the function complexity
Externí odkaz:
http://arxiv.org/abs/2007.06283
We consider the rooted orienteering problem in Euclidean space: Given $n$ points $P$ in $\mathbb R^d$, a root point $s\in P$ and a budget $\mathcal B>0$, find a path that starts from $s$, has total length at most $\mathcal B$, and visits as many poin
Externí odkaz:
http://arxiv.org/abs/2002.07727
We propose a new embedding method which is particularly well-suited for settings where the sample size greatly exceeds the ambient dimension. Our technique consists of partitioning the space into simplices and then embedding the data points into feat
Externí odkaz:
http://arxiv.org/abs/2002.01999
We consider the problem of cost sensitive multiclass classification, where we would like to increase the sensitivity of an important class at the expense of a less important one. We adopt an {\em apportioned margin} framework to address this problem,
Externí odkaz:
http://arxiv.org/abs/2002.01408
Autor:
Lee, Sanghoon, Amgad, Mohamed, Chittajallu, Deepak R., McCormick, Matt, Pollack, Brian P, Elfandy, Habiba, Hussein, Hagar, Gutman, David A, Cooper, Lee AD
Extracting quantitative phenotypic information from whole-slide images presents significant challenges for investigators who are not experienced in developing image analysis algorithms. We present new software that enables rapid learn-by-example trai
Externí odkaz:
http://arxiv.org/abs/2001.11547
Autor:
Gottlieb, Lee-Ad, Ozeri, Shira
We initiate the rigorous study of classification in quasi-metric spaces. These are point sets endowed with a distance function that is non-negative and also satisfies the triangle inequality, but is asymmetric. We develop and refine a learning algori
Externí odkaz:
http://arxiv.org/abs/1909.09969