HyperGAN: A Generative Model for Diverse, Performant Neural Networks
Comments 11 pages, 10 figures, 6 tables, Accepted to ICML 2019
期刊&会议
ICML
International Conference on Machine Learning · 会议 · Machine Learning
Predicting feature imputability in the absence of ground truth
Comments 5 pages, 3 figures, 1 table. In: Proceedings of the 37th International Conference on Machine Learning (ICML), 2020
Automated Synthetic-to-Real Generalization
Comments Accepted to ICML 2020
Lifelong Learning using Eigentasks: Task Separation, Skill Acquisition, and Selective Transfer
Comments Accepted at the 4th Lifelong Machine Learning Workshop at the Thirty-seventh International Conference on Machine Learning (ICML) 2020
Our Evaluation Metric Needs an Update to Encourage Generalization
Comments Accepted to ICML UDL 2020
What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design
Comments Presented at the workshop on Participatory Approaches to Machine Learning at ICML 2020
Revisiting Fundamentals of Experience Replay
Comments Published at ICML 2020. First two authors contributed equally and code available at https://github.com/google-research/google-research/tree/master/experience_replay
Recovery of Sparse Signals from a Mixture of Linear Samples
Comments International Conference on Machine Learning (ICML), 2020. (26 pages, 3 figures)
HNHN: Hypergraph Networks with Hyperedge Neurons
Journal ref Graph Representation Learning and Beyond Workshop at ICML 2020
Distributional Robustness and Regularization in Reinforcement Learning
Comments Accepted at the "Theoretical Foundations of Reinforcement Learning" Workshop - ICML 2020
Not to Cry Wolf: Distantly Supervised Multitask Learning in Critical Care
Journal ref Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4518-4527, 2018
Random extrapolation for primal-dual coordinate descent
Comments To appear in ICML 2020
On uncertainty estimation in active learning for image segmentation
Comments Presented at ICML 2020 Workshop on Uncertainty & Robustness in Deep Learning
Disentanglement of Color and Shape Representations for Continual Learning
Comments Accepted at CL-ICML 2020
Monitoring and explainability of models in production
Comments Workshop on Challenges in Deploying and Monitoring Machine Learning Systems (ICML 2020)
Deep Claim: Payer Response Prediction from Claims Data with Deep Learning
Comments To be presented at the Healthcare Systems, Population Health, and the Role of Health-Tech (HSYS) Workshop at the 37th International Conference on Machine Learning, Vienna, Austria, July 13-18, 2020
Model Fusion with Kullback--Leibler Divergence
Comments ICML 2020
OtoWorld: Towards Learning to Separate by Learning to Move
Comments Published in Self Supervision in Audio and Speech Workshop, 37th International Conference on Machine Learning, Vienna, Austria (ICML 2020)
BaCOUn: Bayesian Classifers with Out-of-Distribution Uncertainty
Comments ICML 2020 Workshop on Uncertainty and Robustness in Deep Learning
Sparse Graph to Sequence Learning for Vision Conditioned Long Textual Sequence Generation
Comments International Conference on Machine Learning (ICML) 2020 Workshop (https://logicalreasoninggnn.github.io/)
State Space Expectation Propagation: Efficient Inference Schemes for Temporal Gaussian Processes
Comments Accepted to International Conference on Machine Learning (ICML) 2020
Towards Robust Classification with Deep Generative Forests
Comments Presented at the ICML 2020 Workshop on Uncertainty and Robustness in Deep Learning
Variable Skipping for Autoregressive Range Density Estimation
Comments ICML 2020. Code released at: https://var-skip.github.io/
Learning Speech Representations from Raw Audio by Joint Audiovisual Self-Supervision
Comments Accepted at the Workshop on Self-supervision in Audio and Speech at ICML 2020
Software Engineering Event Modeling using Relative Time in Temporal Knowledge Graphs
Comments 11 pages, 1 figure. 37th International Conference on Machine Learning (ICML 2020) - Workshop on Graph Representation Learning and Beyond
Generative Modelling for Controllable Audio Synthesis of Expressive Piano Performance
Journal ref Published at ICML Workshop on Machine Learning for Media Discovery Workshop (ML4MD) 2020
Density Deconvolution with Normalizing Flows
Comments Appearing at the second workshop on Invertible Neural Networks, Normalizing Flows, and Explicit Likelihood Models (ICML 2020), Virtual Conference. 8 pages, 6 figures, 5 tables
Streaming Coresets for Symmetric Tensor Factorization
Comments Accepted at ICML 2020. Included algorithm with improved update time and fixed minor bugs
Efficient Intervention Design for Causal Discovery with Latents
Comments International Conference on Machine Learning 2020
Fair Learning with Private Demographic Data
Comments ICML 2020
