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pro vyhledávání: '"Keshavan, Raghunandan H."'
Autor:
Rajput, Shashank, Mehta, Nikhil, Singh, Anima, Keshavan, Raghunandan H., Vu, Trung, Heldt, Lukasz, Hong, Lichan, Tay, Yi, Tran, Vinh Q., Samost, Jonah, Kula, Maciej, Chi, Ed H., Sathiamoorthy, Maheswaran
Modern recommender systems perform large-scale retrieval by first embedding queries and item candidates in the same unified space, followed by approximate nearest neighbor search to select top candidates given a query embedding. In this paper, we pro
Externí odkaz:
http://arxiv.org/abs/2305.05065
We consider the problem of reconstructing a low rank matrix from noisy observations of a subset of its entries. This task has applications in statistical learning, computer vision, and signal processing. In these contexts, "noise" generically refers
Externí odkaz:
http://arxiv.org/abs/1001.0279
Autor:
Keshavan, Raghunandan H., Oh, Sewoong
We consider the problem of reconstructing a low-rank matrix from a small subset of its entries. In this paper, we describe the implementation of an efficient algorithm called OptSpace, based on singular value decomposition followed by local manifold
Externí odkaz:
http://arxiv.org/abs/0910.5260
We consider a problem of significant practical importance, namely, the reconstruction of a low-rank data matrix from a small subset of its entries. This problem appears in many areas such as collaborative filtering, computer vision and wireless senso
Externí odkaz:
http://arxiv.org/abs/0910.0921
Given a matrix M of low-rank, we consider the problem of reconstructing it from noisy observations of a small, random subset of its entries. The problem arises in a variety of applications, from collaborative filtering (the `Netflix problem') to stru
Externí odkaz:
http://arxiv.org/abs/0906.2027
How many random entries of an n by m, rank r matrix are necessary to reconstruct the matrix within an accuracy d? We address this question in the case of a random matrix with bounded rank, whereby the observed entries are chosen uniformly at random.
Externí odkaz:
http://arxiv.org/abs/0812.2599
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