arXiv:2605.09509v2 Announce Type: replace-cross
Abstract: The problem of predicting unobserved entries in a binary matrix, known as 1-bit matrix completion, has found diverse applications in fields s...
By Takeru Matsuda
arXiv:2412. 20802v3 Announce Type: replace-cross Abstract: Recommender systems are widely used in the digital landscape to match users with content fitting their preferences.
By Aurore Archimbaud, Andreas Alfons, Ines Wilms
arXiv:2507.02248v2 Announce Type: replace-cross
Abstract: In this paper, we explore the knowledge transfer under the setting of matrix completion, which aims to enhance the estimation of a low-rank t...
By Dali Liu, Yuying Xie, Haolei Weng
arXiv:2506.04166v3 Announce Type: replace
Abstract: Nearest neighbor (NN) methods have re-emerged as competitive tools for matrix completion, offering strong empirical performance and recent theoreti...
By Caleb Chin, Aashish Khubchandani, Harshvardhan Maskara, Kyuseong Choi, Jacob Feitelberg, Albert Gong, Manit Paul, Tathagata Sadhukhan, Dwaipayan Saha, Anish Agarwal, Raaz Dwivedi
arXiv:2411.12965v3 Announce Type: replace-cross
Abstract: Nearest neighbor (NN) algorithms have been extensively used for missing data problems in recommender systems and sequential decision-making s...
By Tathagata Sadhukhan, Manit Paul, Raaz Dwivedi
arXiv:2606. 04176v1 Announce Type: new Abstract: We study a distributional generalization of the matrix completion problem in which each entry of the target matrix is a probability distribution rather than a scalar.
By Jiayi Wang, Raymond K. W. Wong