A dual framework for low-rank tensor completion

A dual framework for low-rank tensor completion

4 December 2017

Pratik Jawanpuria

Papers citing "A dual framework for low-rank tensor completion"

7 / 7 papers shown

Title
Get the Best of Both Worlds: Improving Accuracy and Transferability by Grassmann Class Representation Haoqi Wang Zhizhong Li Wayne Zhang 33 3 0 03 Aug 2023
Subquadratic Kronecker Regression with Applications to Tensor Decomposition Matthew Fahrbach Thomas Fu Mehrdad Ghadiri 40 15 0 11 Sep 2022
Riemannian Hamiltonian methods for min-max optimization on manifolds Andi Han Bamdev Mishra Pratik Jawanpuria Pawan Kumar Junbin Gao 43 17 0 25 Apr 2022
On Riemannian Optimization over Positive Definite Matrices with the Bures-Wasserstein Geometry Andi Han Bamdev Mishra Pratik Jawanpuria Junbin Gao 29 38 0 01 Jun 2021
Learning Representations from Imperfect Time Series Data via Tensor Rank Regularization Paul Pu Liang Zhun Liu Yao-Hung Hubert Tsai Qibin Zhao Ruslan Salakhutdinov Louis-Philippe Morency AI4TS 30 81 0 01 Jul 2019
McTorch, a manifold optimization library for deep learning Mayank Meghwanshi Pratik Jawanpuria Anoop Kunchukuttan Hiroyuki Kasai Bamdev Mishra AI4CE 28 41 0 03 Oct 2018
Beyond Unfolding: Exact Recovery of Latent Convex Tensor Decomposition under Reshuffling Chao Li Mohammad Emtiyaz Khan Zhun Sun Gang Niu Bo Han Shengli Xie Qibin Zhao 19 7 0 22 May 2018