A Bandit Approach to Maximum Inner Product Search

15 December 2018

Papers citing "A Bandit Approach to Maximum Inner Product Search"

7 / 7 papers shown

Title
A more efficient method for large-sample model-free feature screening via multi-armed bandits Xiaxue Ouyang Xinlai Kang Mengyu Li Zhenxing Dou Jun Yu Cheng Meng 58 0 0 19 Sep 2025
Automating Nearest Neighbor Search Configuration with Constrained OptimizationInternational Conference on Learning Representations (ICLR), 2023 Philip Sun Ruiqi Guo Surinder Kumar 146 7 0 04 Jan 2023
Faster Maximum Inner Product Search in High DimensionsInternational Conference on Machine Learning (ICML), 2022 Mo Tiwari Ryan Kang Je-Yong Lee Luke Lee Chris Piech Sebastian Thrun Ilan Shomorony Martin Jinye Zhang 232 6 0 14 Dec 2022
Flashlight: Scalable Link Prediction with Effective DecodersLOG IN (LOG IN), 2022 Yiwei Wang Bryan Hooi Yozen Liu Tong Zhao Zhichun Guo Neil Shah BDL 288 9 0 17 Sep 2022
Transformer with Memory ReplayAAAI Conference on Artificial Intelligence (AAAI), 2022 R. Liu Barzan Mozafari OffRL 207 4 0 19 May 2022
Adam with Bandit Sampling for Deep LearningNeural Information Processing Systems (NeurIPS), 2020 Rui Liu Tianyi Wu Barzan Mozafari 142 27 0 24 Oct 2020
Scalable Approximate Inference and Some Applications Jun Han BDL 136 1 0 07 Mar 2020