Learning Task-Agnostic Embedding of Multiple Black-Box Experts for Multi-Task Model Fusion
暂无分享,去创建一个
Patrick Jaillet | Bryan Kian Hsiang Low | Trong Nghia Hoang | Chi Thanh Lam | Patrick Jaillet | T. Hoang | B. Low
[1] Mohan S. Kankanhalli,et al. Active Learning Is Planning: Nonmyopic ε-Bayes-Optimal Active Learning of Gaussian Processes , 2014, ECML/PKDD.
[2] Jimeng Sun,et al. CHEER: Rich Model Helps Poor Model via Knowledge Infusion , 2020, ArXiv.
[3] Kian Hsiang Low,et al. Decentralized High-Dimensional Bayesian Optimization with Factor Graphs , 2017, AAAI.
[4] Kian Hsiang Low,et al. Gaussian process decentralized data fusion meets transfer learning in large-scale distributed cooperative perception , 2017, Autonomous Robots.
[5] Sijia Liu,et al. On the Design of Black-Box Adversarial Examples by Leveraging Gradient-Free Optimization and Operator Splitting Method , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[6] Max Welling,et al. Auto-Encoding Variational Bayes , 2013, ICLR.
[7] Kian Hsiang Low,et al. A Unifying Framework of Anytime Sparse Gaussian Process Regression Models with Stochastic Variational Inference for Big Data , 2015, ICML.
[8] John Shawe-Taylor,et al. Tighter PAC-Bayes Bounds , 2006, NIPS.
[9] Bryan Kian Hsiang Low,et al. Information-Based Multi-Fidelity Bayesian Optimization , 2017 .
[10] Kian Hsiang Low,et al. A Distributed Variational Inference Framework for Unifying Parallel Sparse Gaussian Process Regression Models , 2016, ICML.
[11] Kian Hsiang Low,et al. A General Framework for Interacting Bayes-Optimally with Self-Interested Agents using Arbitrary Parametric Model and Model Prior , 2013, IJCAI.
[12] Jimeng Sun,et al. CASTER: Predicting Drug Interactions with Chemical Substructure Representation , 2019, AAAI.
[13] Kian Hsiang Low,et al. Stochastic Variational Inference for Bayesian Sparse Gaussian Process Regression , 2017, 2019 International Joint Conference on Neural Networks (IJCNN).
[14] Sergey Levine,et al. Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks , 2017, ICML.
[15] Jimeng Sun,et al. RDPD: Rich Data Helps Poor Data via Imitation , 2018, IJCAI.
[16] Girish Chowdhary,et al. Communication efficient decentralized Gaussian Process Fusion for multi-UAS path planning , 2017, 2017 American Control Conference (ACC).
[17] Shai Ben-David,et al. Understanding Machine Learning: From Theory to Algorithms , 2014 .
[18] Blaise Agüera y Arcas,et al. Communication-Efficient Learning of Deep Networks from Decentralized Data , 2016, AISTATS.
[19] Yasaman Khazaeni,et al. Bayesian Nonparametric Federated Learning of Neural Networks , 2019, ICML.
[20] Jimeng Sun,et al. DDL: Deep Dictionary Learning for Predictive Phenotyping , 2019, IJCAI.
[21] Kian Hsiang Low,et al. Information-Theoretic Approach to Efficient Adaptive Path Planning for Mobile Robotic Environmental Sensing , 2009, ICAPS.
[22] Kian Hsiang Low,et al. Collective Model Fusion for Multiple Black-Box Experts , 2019, ICML.
[23] Kian Hsiang Low,et al. Parallel Gaussian Process Regression with Low-Rank Covariance Matrix Approximations , 2013, UAI.
[24] Seong Joon Oh,et al. Modeling Uncertainty with Hedged Instance Embedding , 2018, ICLR 2018.
[25] Jonathan P. How,et al. Near-Optimal Adversarial Policy Switching for Decentralized Asynchronous Multi-Agent Systems , 2017, 2018 IEEE International Conference on Robotics and Automation (ICRA).
[26] Kristjan H. Greenewald,et al. Statistical Model Aggregation via Parameter Matching , 2019, NeurIPS.
[27] Kian Hsiang Low,et al. Adaptive Sampling for Multi-Robot Wide-Area Exploration , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.
[28] Marc Peter Deisenroth,et al. Distributed Gaussian Processes , 2015, ICML.
[29] Kian Hsiang Low,et al. Parallel Gaussian Process Regression for Big Data: Low-Rank Representation Meets Markov Approximation , 2014, AAAI.
[30] Andrew L. Beam,et al. Adversarial attacks on medical machine learning , 2019, Science.
[31] Gaurav S. Sukhatme,et al. Decentralized Data Fusion and Active Sensing with Mobile Sensors for Modeling and Predicting Spatiotemporal Traffic Phenomena , 2012, UAI.
[32] David A. McAllester. PAC-Bayesian model averaging , 1999, COLT '99.
[33] Kian Hsiang Low,et al. Gaussian Process-Based Decentralized Data Fusion and Active Sensing for Mobility-on-Demand System , 2013, Robotics: Science and Systems.
[34] Hugo Larochelle,et al. Optimization as a Model for Few-Shot Learning , 2016, ICLR.
[35] Kian Hsiang Low,et al. A Generalized Stochastic Variational Bayesian Hyperparameter Learning Framework for Sparse Spectrum Gaussian Process Regression , 2016, AAAI.
[36] Yoshua Bengio,et al. Bayesian Model-Agnostic Meta-Learning , 2018, NeurIPS.
[37] François Laviolette,et al. PAC-Bayesian learning of linear classifiers , 2009, ICML '09.
[38] Kian Hsiang Low,et al. Telesupervised remote surface water quality sensing , 2010, 2010 IEEE Aerospace Conference.
[39] Kian Hsiang Low,et al. Collective Online Learning of Gaussian Processes in Massive Multi-Agent Systems , 2019, AAAI.
[40] Peter B. Walker,et al. Federated Learning for Healthcare Informatics , 2019, Journal of Healthcare Informatics Research.