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1Optimizing Contrastive/Rank/Triplet Loss in Tensorflow for Neural Information Retrieval · Han Xiao Tech Blog - Deep Learning, NLP, AI
http://hanxiao.io/2017/11/08/Optimizing-Contrastive-Rank-Triplet-Loss-in-Tensorflow-for-Neural/
5 years ago by @nosebrain
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1Optimizing Contrastive/Rank/Triplet Loss in Tensorflow for Neural Information Retrieval · Han Xiao Tech Blog
https://hanxiao.github.io/2017/11/08/Optimizing-Contrastive-Rank-Triplet-Loss-in-Tensorflow-for-Neural/
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2Training Over-parameterized Models with Non-decomposable Objectives
H. Narasimhan, and A. Menon. Advances in Neural Information Processing Systems, (2021)
3 years ago by @becker
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9SimLoss: Class Similarities in Cross Entropy
K. Kobs, M. Steininger, A. Zehe, F. Lautenschlager, and A. Hotho. Foundations of Intelligent Systems, page 431--439. Cham, Springer International Publishing, (2020)
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5Right for the Right Reasons: Training Differentiable Models by Constraining their Explanations
A. Ross, M. Hughes, and F. Doshi-Velez. Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, IJCAI-17, page 2662--2670. (2017)
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2Learning Groupwise Scoring Functions Using Deep Neural Networks.
Q. Ai, X. Wang, N. Golbandi, M. Bendersky, and M. Najork. CoRR, (2018)
5 years ago by @nosebrain
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2Improving Top-N Recommendation with Heterogeneous Loss.
F. Zhao, and Y. Guo. IJCAI, page 2378-2384. IJCAI/AAAI Press, (2016)
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3Tying Word Vectors and Word Classifiers: A Loss Framework for Language Modeling.
H. Inan, K. Khosravi, and R. Socher. Proceedings of the 5th International Conference on Learning Representations, (2017)
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10BPR: Bayesian Personalized Ranking from Implicit Feedback
S. Rendle, C. Freudenthaler, Z. Gantner, and L. Schmidt-Thieme. Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence, page 452--461. Arlington, Virginia, United States, AUAI Press, (2009)
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2Extreme Multi-label Loss Functions for Recommendation, Tagging, Ranking & Other Missing Label Applications.
H. Jain, Y. Prabhu, and M. Varma. KDD, page 935-944. ACM, (2016)
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1Optimizing Contrastive/Rank/Triplet Loss in Tensorflow for Neural Information Retrieval · Han Xiao Tech Blog - Deep Learning, NLP, AI

1Optimizing Contrastive/Rank/Triplet Loss in Tensorflow for Neural Information Retrieval · Han Xiao Tech Blog

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2Training Over-parameterized Models with Non-decomposable Objectives

9SimLoss: Class Similarities in Cross Entropy

5Right for the Right Reasons: Training Differentiable Models by Constraining their Explanations

2Learning Groupwise Scoring Functions Using Deep Neural Networks.

2Improving Top-N Recommendation with Heterogeneous Loss.

3Tying Word Vectors and Word Classifiers: A Loss Framework for Language Modeling.

10BPR: Bayesian Personalized Ranking from Implicit Feedback

2Extreme Multi-label Loss Functions for Recommendation, Tagging, Ranking & Other Missing Label Applications.

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