Feb. 9, 2024, 5:43 a.m. | Xin Chen Sukanya Kudva Yongzheng Dai Anil Aswani Chen Chen

cs.LG updates on arXiv.org arxiv.org

The main challenge with the tensor completion problem is a fundamental tension between computation power and the information-theoretic sample complexity rate. Past approaches either achieve the information-theoretic rate but lack practical algorithms to compute the corresponding solution, or have polynomial-time algorithms that require an exponentially-larger number of samples for low estimation error. This paper develops a novel tensor completion algorithm that resolves this tension by achieving both provable convergence (in numerical tolerance) in a linear number of oracle steps and …

algorithms challenge complexity computation compute cs.lg error information low math.oc optimization paper polynomial power practical rate sample samples solution tensor the information via

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