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Representing Data by Sparse Combination of Contextual Data Points for Classification., , , , and . ISNN, volume 9377 of Lecture Notes in Computer Science, page 373-381. Springer, (2015)Running Out of Time: The Impact and Value of Flexibility in On-Demand Crowdwork., , and . CHI, page 430. ACM, (2018)On Instance-Dependent Bounds for Offline Reinforcement Learning with Linear Function Approximation., , , , and . AAAI, page 9310-9318. AAAI Press, (2023)Optimal Uniform OPE and Model-based Offline Reinforcement Learning in Time-Homogeneous, Reward-Free and Task-Agnostic Settings., and . NeurIPS, page 12890-12903. (2021)Near-Optimal Offline Reinforcement Learning via Double Variance Reduction., , and . NeurIPS, page 7677-7688. (2021)Band-Level Correlation Noise Modeling for Wyner-Ziv Video Coding with Gaussian Mixture Models., , , and . Circuits Syst. Signal Process., 34 (7): 2237-2254 (2015)Understanding the Microtask Crowdsourcing Experience for Workers with Disabilities: A Comparative View., and . Proc. ACM Hum. Comput. Interact., 6 (CSCW2): 1-30 (2022)View knowledge transfer network for multi-view action recognition., , , , and . Image Vis. Comput., (2022)Blind image deblurring via coupled sparse representation., , , and . J. Vis. Commun. Image Represent., 25 (5): 814-821 (2014)Supervised learning of sparse context reconstruction coefficients for data representation and classification., , , , and . Neural Comput. Appl., 28 (1): 135-143 (2017)