Asia
A loss framework for calibrated anomaly detection
Neural Information Processing Systems http://nips.cc/
Credit Assignment For Collective Multiagent RL With Global Rewards
Duc Thien Nguyen, Akshat Kumar, Hoong Chuin Lau
Neural Information Processing Systems http://nips.cc/
6d0bf1265ea9635fb4f9d56f16d7efb2-Paper-Conference.pdf
Recent works have shown that line search methods can speed up Stochastic Gradient Descent (SGD) and Adam in modern over-parameterized settings. However, existing line searches may take steps that are smaller than necessary since they require a monotone decrease of the (mini-)batch objective function.
Ultrametric Fitting by Gradient Descent
Giovanni Chierchia, Benjamin Perret
We study the problem of fitting an ultrametric distance to a dissimilarity graph in the context of hierarchical cluster analysis.
Neural Architecture Optimization
Renqian Luo, Fei Tian, Tao Qin, Enhong Chen, Tie-Yan Liu
Such a better embedding is then decoded to a network by the decoder.
Visual Object Networks: Image Generation with Disentangled 3D Representations
Jun-Yan Zhu, Zhoutong Zhang, Chengkai Zhang, Jiajun Wu, Antonio Torralba, Josh Tenenbaum, Bill Freeman
However,while existing models cansynthesize photorealistic images, they lack an understanding of our underlying 3D world. We present a new generative model,Visual Object Networks (VON), synthesizing natural images of objects with a disentangled 3D representation.
Uncovering motifs of concurrent signaling across multiple neuronal populations
Modern recording techniques now allow us to record from distinct neuronal populations in different brain networks.