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Representation Learning with Weighted Inner Product for Universal Approximation of General Similarities.

, , , and . IJCAI, page 5031-5038. ijcai.org, (2019)

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A probabilistic framework for multi-view feature learning with many-to-many associations via neural networks., , and . ICML, volume 80 of Proceedings of Machine Learning Research, page 3885-3894. PMLR, (2018)Robust Graph Embedding with Noisy Link Weights., and . AISTATS, volume 89 of Proceedings of Machine Learning Research, page 664-673. PMLR, (2019)Representation Learning with Weighted Inner Product for Universal Approximation of General Similarities., , , and . IJCAI, page 5031-5038. ijcai.org, (2019)Graph Embedding with Shifted Inner Product Similarity and Its Improved Approximation Capability., , and . AISTATS, volume 89 of Proceedings of Machine Learning Research, page 644-653. PMLR, (2019)Studies on Neural Network-Based Graph Embedding and Its Extensions.. Kyoto University, Japan, (2020)Graph Embedding with Shifted Inner Product Similarity and Its Improved Approximation Capability., , and . CoRR, (2018)A Generalization Gap Estimation for Overparameterized Models via the Langevin Functional Variance., and . J. Comput. Graph. Stat., 32 (4): 1287-1295 (2023)Image and tag retrieval by leveraging image-group links with multi-domain graph embedding., , and . ICIP, page 221-225. IEEE, (2016)An integrated perspective of robustness in regression through the lens of the bias-variance trade-off.. CoRR, (2024)Extrapolation Towards Imaginary 0-Nearest Neighbour and Its Improved Convergence Rate., and . NeurIPS, (2020)