暂无分享,去创建一个
[1] Nir Friedman,et al. Probabilistic Graphical Models - Principles and Techniques , 2009 .
[2] Lei Yu,et al. A Hybrid Collaborative Filtering Model with Deep Structure for Recommender Systems , 2017, AAAI.
[3] James R. Foulds,et al. Latent Topic Networks: A Versatile Probabilistic Programming Framework for Topic Models , 2015, ICML.
[4] Eric Xing,et al. Deep Generative Models with Learnable Knowledge Constraints , 2018, NeurIPS.
[5] Ning Chen,et al. Bayesian inference with posterior regularization and applications to infinite latent SVMs , 2012, J. Mach. Learn. Res..
[6] Hongzhe Li,et al. In Response to Comment on "Network-constrained regularization and variable selection for analysis of genomic data" , 2008, Bioinform..
[7] Marco Gori,et al. Bridging logic and kernel machines , 2011, Machine Learning.
[8] Rui Zhang,et al. Incorporating Knowledge Graph Embeddings into Topic Modeling , 2017, AAAI.
[9] Michael I. Jordan,et al. Information Constraints on Auto-Encoding Variational Bayes , 2018, NeurIPS.
[10] Bernhard Schölkopf,et al. Measuring Statistical Dependence with Hilbert-Schmidt Norms , 2005, ALT.
[11] Geoffrey E. Hinton,et al. Distilling the Knowledge in a Neural Network , 2015, ArXiv.
[12] Inderjit S. Dhillon,et al. Robust Principal Component Analysis with Side Information , 2016, ICML.
[13] E. F. Vogel,et al. A plant-wide industrial process control problem , 1993 .
[14] George A. Miller,et al. WordNet: A Lexical Database for English , 1995, HLT.
[15] Kevin P. Murphy,et al. Machine learning - a probabilistic perspective , 2012, Adaptive computation and machine learning series.
[16] Jun Zhu,et al. Robust RegBayes: Selectively Incorporating First-Order Logic Domain Knowledge into Bayesian Models , 2014, ICML.
[17] Tong Zhang,et al. A Framework for Learning Predictive Structures from Multiple Tasks and Unlabeled Data , 2005, J. Mach. Learn. Res..
[18] Matthew Richardson,et al. Markov logic networks , 2006, Machine Learning.
[19] John Blitzer,et al. Regularized Learning with Networks of Features , 2008, NIPS.
[20] Arthur Gretton,et al. A low variance consistent test of relative dependency , 2015, ICML.
[21] Zenglin Xu,et al. Learning with Feature Network and Label Network Simultaneously , 2017, AAAI.
[22] Diyi Yang,et al. Incorporating Word Correlation Knowledge into Topic Modeling , 2015, NAACL.
[23] Yu Hu,et al. Learning Semantic Word Embeddings based on Ordinal Knowledge Constraints , 2015, ACL.
[24] A. Kraskov,et al. Estimating mutual information. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.
[25] Max Welling,et al. Auto-Encoding Variational Bayes , 2013, ICLR.
[26] Jun Sakuma,et al. Fairness-Aware Classifier with Prejudice Remover Regularizer , 2012, ECML/PKDD.
[27] Maria L. Rizzo,et al. Measuring and testing dependence by correlation of distances , 2007, 0803.4101.
[28] Guoyin Wang,et al. Joint Embedding of Words and Labels for Text Classification , 2018, ACL.
[29] Yoshua Bengio,et al. Learning deep representations by mutual information estimation and maximization , 2018, ICLR.
[30] Eric P. Xing,et al. Grounding Topic Models with Knowledge Bases , 2016, IJCAI.
[31] Aaron C. Courville,et al. MINE: Mutual Information Neural Estimation , 2018, ArXiv.
[32] Naftali Tishby,et al. Learning to Select Features using their Properties , 2008 .
[33] Junzhou Huang,et al. Learning with structured sparsity , 2009, ICML '09.
[34] Le Song,et al. Feature Selection via Dependence Maximization , 2012, J. Mach. Learn. Res..
[35] Jude W. Shavlik,et al. Knowledge-Based Kernel Approximation , 2004, J. Mach. Learn. Res..
[36] Eric P. Xing,et al. Harnessing Deep Neural Networks with Logic Rules , 2016, ACL.
[37] Ben Taskar,et al. Posterior Regularization for Structured Latent Variable Models , 2010, J. Mach. Learn. Res..
[38] Koray Kavukcuoglu,et al. Pixel Recurrent Neural Networks , 2016, ICML.
[39] Yukihiro Tadokoro,et al. Structured Denoising Autoencoder for Fault Detection and Analysis , 2014, ACML.
[40] Naoya Takeishi,et al. Knowledge-Based Distant Regularization in Learning Probabilistic Models , 2018, ArXiv.
[41] Michael Mitzenmacher,et al. Detecting Novel Associations in Large Data Sets , 2011, Science.
[42] Yoshua Bengio,et al. Mutual Information Neural Estimation , 2018, ICML.
[43] Mikhail Belkin,et al. Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples , 2006, J. Mach. Learn. Res..
[44] Kristian Kersting,et al. Markov Logic Mixtures of Gaussian Processes: Towards Machines Reading Regression Data , 2012, AISTATS.
[45] Alexandros Kalousis,et al. Regularising Non-linear Models Using Feature Side-information , 2017, ICML.
[46] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[47] Max Welling,et al. Improved Variational Inference with Inverse Autoregressive Flow , 2016, NIPS 2016.
[48] Hugo Larochelle,et al. The Neural Autoregressive Distribution Estimator , 2011, AISTATS.
[49] Max Welling,et al. The Variational Fair Autoencoder , 2015, ICLR.
[50] Samy Bengio,et al. Density estimation using Real NVP , 2016, ICLR.
[51] David Pfau,et al. Unrolled Generative Adversarial Networks , 2016, ICLR.
[52] Richard S. Zemel,et al. Generative Moment Matching Networks , 2015, ICML.
[53] Philip S. Yu,et al. A Comprehensive Survey on Graph Neural Networks , 2019, IEEE Transactions on Neural Networks and Learning Systems.
[54] B. Schölkopf,et al. Kernel‐based tests for joint independence , 2016, 1603.00285.
[55] Samy Bengio,et al. Large-Scale Object Classification Using Label Relation Graphs , 2014, ECCV.
[56] Yoshua Bengio,et al. Generative Adversarial Nets , 2014, NIPS.
[57] Marco Gori,et al. Semantic-based regularization for learning and inference , 2017, Artif. Intell..
[58] Valero Laparra,et al. Fair Kernel Learning , 2017, ECML/PKDD.
[59] Xiaojin Zhu,et al. Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence A Framework for Incorporating General Domain Knowledge into Latent Dirichlet Allocation Using First-Order Logic , 2022 .
[60] Baogang Wei,et al. Incorporating Probabilistic Knowledge into Topic Models , 2015, PAKDD.
[61] Jeffrey Dean,et al. Distributed Representations of Words and Phrases and their Compositionality , 2013, NIPS.
[62] Naftali Tishby,et al. Incorporating Prior Knowledge on Features into Learning , 2007, AISTATS.
[63] Arthur Gretton,et al. Large-scale kernel methods for independence testing , 2016, Stat. Comput..