NIPS2018 Workshop一览

NIPS2018 Workshops

NIPS2018 会议为我们带来39个Workshop和两个竞赛track，涵盖了机器学习、深度学习、强化学习、因果、推理、表示、优化等各方面的基础研究，以及图像、检测、游戏、健康、医学图像处理、安全、隐私、金融、化学、语音、交通运输和设计等方面，同时还涵盖了对于社会、政治方面的诸多考量，又可以学习很长时间了~~~

Critiquing and Correcting Trends in Machine Learning
Workshop on Security in Machine Learning
Continual Learning
NIPS 2018 workshop on Compact Deep Neural Networks with industrial applications
Machine Learning for Geophysical & Geochemical Signals
Visually grounded interaction and language
Challenges and Opportunities for AI in Financial Services: the Impact of Fairness, Explainability, Accuracy, and Privacy
Deep Reinforcement Learning
All of Bayesian Nonparametrics (Especially the Useful Bits)
MLSys: Workshop on Systems for ML and Open Source Software
Imitation Learning and its Challenges in Robotics
The second Conversational AI workshop – today’s practice and tomorrow’s potential
Modeling the Physical World: Learning, Perception, and Control
Modeling and decision-making in the spatiotemporal domain
Smooth Games Optimization and Machine Learning
2nd Workshop on Machine Learning on the Phone and other Consumer Devices (MLPCD 2)
Bayesian Deep Learning
Causal Learning
Competition Track
Workshop on Social, Political, and Ethical Issues in AI
Machine Learning Open Source Software 2018: Sustainable communities

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Second Workshop on Machine Learning for Creativity and Design
CiML 2018 - Machine Learning competitions “in the wild”: Playing in the real world or in real time
Machine Learning for Health (ML4H): Moving beyond supervised learning in healthcare
Wordplay: Reinforcement and Language Learning in Text-based Games
Medical Imaging meets NIPS
Machine Learning for the Developing World (ML4D): Achieving sustainable impact
Reinforcement Learning under Partial Observability
Machine Learning for Systems
Privacy Preserving Machine Learning
AI for social good
Infer to Control: Probabilistic Reinforcement Learning and Structured Control
Learning by Instruction
NIPS 2018 Workshop on Meta-Learning
Emergent Communication Workshop
Machine Learning for Molecules and Materials
NIPS Workshop on Machine Learning for Intelligent Transportation Systems 2018
Relational Representation Learning
Integration of Deep Learning Theories
Interpretability and Robustness in Audio, Speech, and Language