Asia
Imagine the Unseen World: A Benchmark for Systematic Generalization in Visual World Models
This work was partly done while C.G. was at Google DeepMind. C.G. is currently affiliated with EPFL.
Communication-Efficient Distributed Learning via Lazily Aggregated Quantized Gradients
Jun Sun, Tianyi Chen, Georgios Giannakis, Zaiyue Yang
Neural Information Processing Systems http://nips.cc/
Streamlining Variational Inference for Constraint Satisfaction Problems
Aditya Grover, Tudor Achim, Stefano Ermon
Neural Information Processing Systems http://nips.cc/
58a799d16fb0c1f2014e98f4ba972b25-Paper-Conference.pdf
RL that utilize function approximation to generalize observational data to unknown states/actions. The goal of this paper is to study the sample complexity of policy-based RL, which is arguably the simplest setting for RL with function approximation (Kearns et al., 1999; Kakade, 2003).
Extending Stein's unbiased risk estimator to train deep denoisers with correlated pairs of noisy images
Magauiya Zhussip, Shakarim Soltanayev, Se Young Chun
Neural Information Processing Systems http://nips.cc/
