Asia
Curvilinear Distance Metric Learning
Shuo Chen, Lei Luo, Jian Yang, Chen Gong, Jun Li, Heng Huang
Neural Information Processing Systems http://nips.cc/
Quadratic Decomposable Submodular Function Minimization
Pan Li, Niao He, Olgica Milenkovic
Neural Information Processing Systems http://nips.cc/
Bayesian Pose Graph Optimization via Bingham Distributions and Tempered Geodesic MCMC
Tolga Birdal, Umut Simsekli, Mustafa Onur Eken, Slobodan Ilic
Wedevisetheoretical convergenceguarantees and extensively evaluate our method on synthetic and real benchmarks.
Triad Constraints for Learning Causal Structure of Latent Variables
Ruichu Cai, Feng Xie, Clark Glymour, Zhifeng Hao, Kun Zhang
Learning causal structure from observational data has attracted much attention, and it is notoriously challenging to find the underlying structure in the presence of confounders (hidden direct common causes of two variables).
f593c9c251d4d7cf14d4ab9861dfb7eb-Paper-Conference.pdf
However, some recent studies haverecognized that most ofthese approaches failtoimprovethe performance over empirical risk minimization especially when applied to overparameterized neural networks.
