CoVeR: Learning Covariate-Specific Vector Representations with Tensor Decompositions
Comments 12 pages. Appears in ICML 2018
期刊&会议
ICML
International Conference on Machine Learning · 会议 · Machine Learning
SGD and Hogwild! Convergence Without the Bounded Gradients Assumption
Journal ref Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3747-3755, 2018
Nearly Optimal Robust Subspace Tracking
Comments A [short version](http://proceedings.mlr.press/v80/narayanamurthy18a.html) will be presented at ICML 2018 (Long Talk). arXiv admin note: text overlap with arXiv:1803.00651
A multidisciplinary task-based perspective for evaluating the impact of AI autonomy and generality on the future of work
Comments AEGAP2018 Workshop at ICML 2018, 7 pages, 1 table
Singing Style Transfer Using Cycle-Consistent Boundary Equilibrium Generative Adversarial Networks
Comments 3 pages, 3 figures, demo website: http://mirlab.org/users/haley.wu/cybegan
Journal ref ICML Workshop 2018 (Joint Music Workshop)
Been There, Done That: Meta-Learning with Episodic Recall
Comments ICML 2018
Goal-oriented Trajectories for Efficient Exploration
Comments ICML 2018 Exploration in RL Workshop, videos: https://sites.google.com/view/got-exploration
Variational Bayesian dropout: pitfalls and fixes
Comments Extended version of the paper accepted to ICML 2018: more details in the proofs, few minor modifications
Multi-robot Path Planning in Well-formed Infrastructures: Prioritized Planning vs. Prioritized Wait Adjustment (Preliminary Results)
Comments Submitted to the Federated AI for Robotics Workshop (FAIR) 2018 (https://sites.google.com/site/federatedai4robotics2018/home) held at July 15 2018 as part of the Federated AI Meeting (joint IJCAI-ECAI/ICML/AAMAS conferences)
Learning in Variational Autoencoders with Kullback-Leibler and Renyi Integral Bounds
Comments accepted at the ICML 2018 workshop on Theoretical Foundations and Applications of Deep Generative Models, Stockholm, Sweden, 2018
Program Language Translation Using a Grammar-Driven Tree-to-Tree Model
Comments Accepted at the ICML workshop Neural Abstract Machines & Program Induction v2. 4 pages excluding acknowledgements/references (6 pages total)
Pathwise Derivatives Beyond the Reparameterization Trick
Comments ICML 2018
Generating Realistic Geology Conditioned on Physical Measurements with Generative Adversarial Networks
Comments Added ICML workshop info, more specific training details and more details on how images are chosen
Quasi-Monte Carlo Variational Inference
Journal ref Published in the proceedings of the 35th International Conference on Machine Learning (ICML 2018)
Generating Multi-Categorical Samples with Generative Adversarial Networks
Journal ref Presented at the ICML 2018 workshop on Theoretical Foundations and Applications of Deep Generative Models, Stockholm, Sweden
Towards Mixed Optimization for Reinforcement Learning with Program Synthesis
Comments Updated publication details, format. Accepted at NAMPI workshop, ICML '18
A Novel Hybrid Machine Learning Model for Auto-Classification of Retinal Diseases
Comments Accepted at the Joint ICML and IJCAI Workshop on Computational Biology (ICML-IJCAI WCB) to be held in Stockholm SWEDEN, 2018. Referring to accepted-papers?authuser=0" target="_blank" rel="noopener">https://sites.google.com/view/wcb2018/accepted-papers?authuser=0
Journal ref ICML-IJCAI Workshop 2018
Rapid Adaptation with Conditionally Shifted Neurons
Comments ICML 2018; Added: additional ablation and speed comparison with MetaNet
Playing against Nature: causal discovery for decision making under uncertainty
Comments Accepted as poster presentation at the CausalML Workshop at ICML 2018
Hierarchical VampPrior Variational Fair Auto-Encoder
Comments ICML Workshop on Theoretical Foundations and Applications of Deep Generative Models 2018, final version
Bilevel Programming for Hyperparameter Optimization and Meta-Learning
Comments ICML 2018; code for replicating experiments at https://github.com/prolearner/hyper-representation, main package (Far-HO) at https://github.com/lucfra/FAR-HO
The Potential of the Return Distribution for Exploration in RL
Comments Published at the Exploration in Reinforcement Learning Workshop at the 35th International Conference on Machine Learning, Stockholm, Sweden
Improved Training of Generative Adversarial Networks Using Representative Features
Comments Accepted at ICML 2018
LeapsAndBounds: A Method for Approximately Optimal Algorithm Configuration
Comments to appear at ICML 2018
Sample Efficient Semantic Segmentation using Rotation Equivariant Convolutional Networks
Comments Presented at the ICML workshop: Towards learning with limited labels: Equivariance, Invariance, and Beyond, 2018
Progress & Compress: A scalable framework for continual learning
Comments Accepted at ICML 2018
Women also Snowboard: Overcoming Bias in Captioning Models (Extended Abstract)
Comments Burns and Hendricks contributed equally. 2018 ICML Workshop on Fairness, Accountability, and Transparency in Machine Learning (FAT/ML 2018)
Active Testing: An Efficient and Robust Framework for Estimating Accuracy
Comments accepted to ICML 2018
Accurate Uncertainties for Deep Learning Using Calibrated Regression
Comments ICML 2018
AI in Education needs interpretable machine learning: Lessons from Open Learner Modelling
Comments presented at 2018 ICML Workshop on Human Interpretability in Machine Learning (WHI 2018), Stockholm, Sweden
