Asia
2 ProblemFormulationandRelatedWorks Intypical graph learning problems, givenasetoflabeled graphsDtr ={(Gi,yi)}N
In this paper, we first mathematically formulate thetwochallenging problems forgraph data andtake an initiative on tackling them under a unified probabilistic model.
Subspace Attack: Exploiting Promising Subspaces for Query-Efficient Black-box Attacks
Yiwen Guo, Ziang Yan, Changshui Zhang
Neural Information Processing Systems http://nips.cc/
Provably Robust Temporal Difference Learning for Heavy-Tailed Rewards
We corroborate our theoretical results with numerical experiments.
Off-Policy Evaluationwith Deficient Support Using Side Information
Appendix B 4. Ifyouareusingexistingassets (e.g., code, data, models) orcurating/releasingnewassets... (a) Ifyourworkusesexistingassets, didyoucitethecreators?[Yes]See
Implicit Posterior Variational Inference for Deep Gaussian Processes
Haibin YU, Yizhou Chen, Bryan Kian Hsiang Low, Patrick Jaillet, Zhongxiang Dai
Neural Information Processing Systems http://nips.cc/