We invite submissions presenting research on topics including but not limited to the following:
Applications (e.g., vision, language, speech and audio)
Deep learning (e.g., architectures, generative models, optimization for deep networks)
Evaluation (e.g., methodology, meta-studies, replicability and validity)
General machine learning (supervised, unsupervised, online, active, etc.)
Infrastructure (e.g., libraries, improved implementation and scalability, distributed solutions)
Machine learning for sciences (e.g. climate, health, life sciences, physics, social sciences)
Neuroscience and cognitive science (e.g., neural coding, brain-computer interfaces)
Optimization (e.g., convex and non-convex, stochastic, robust)
Probabilistic methods (e.g., variational inference, causal inference, Gaussian processes)
Reinforcement learning (e.g., decision and control, planning, hierarchical RL, robotics)
Social and economic aspects of machine learning (e.g., fairness, interpretability, human-AI interaction, privacy, safety, strategic behaviour)
Theory (e.g., control theory, learning theory, algorithmic game theory)
Each presentation is around 15 mins, followed by 5 mins Q&A.
To present your work, please register here, and then upload your abstract hereÂ
(maximum 500 words ).
The authors of the accepted work will be invited to upload their slides.