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Texture analysis with variational hidden Markov trees., and . IEEE Trans. Signal Process., 54 (6-1): 2353-2356 (2006)Active learning and basis selection for kernel-based linear models: a Bayesian perspective., , and . IEEE Trans. Signal Process., 58 (5): 2686-2700 (2010)Probabilistic Topic Models., , and . IEEE Signal Process. Mag., 27 (6): 55-65 (2010)Information-Theoretic Compressive Measurement Design., , , , , and . IEEE Trans. Pattern Anal. Mach. Intell., 39 (6): 1150-1164 (2017)Variational Bayes for Continuous Hidden Markov Models and Its Application to Active Learning., , and . IEEE Trans. Pattern Anal. Mach. Intell., 28 (4): 522-532 (2006)Proactive Pseudo-Intervention: Causally Informed Contrastive Learning For Interpretable Vision Models., , , , , and . CoRR, (2020)Nonlocal Low-Rank Tensor Factor Analysis for Image Restoration., , and . CVPR, page 8232-8241. Computer Vision Foundation / IEEE Computer Society, (2018)Towards Fair Federated Learning With Zero-Shot Data Augmentation., , , , , , and . CVPR Workshops, page 3310-3319. Computer Vision Foundation / IEEE, (2021)Kernel-Based Approaches for Sequence Modeling: Connections to Neural Methods., , , , and . NeurIPS, page 3387-3398. (2019)Scalable Model Selection for Belief Networks., , , and . NIPS, page 4609-4619. (2017)