Halifax Regional Municipality
Tree Variational Autoencoders
TreeV AE hierarchically divides samples according to their intrinsic characteristics, shedding light on hidden structures in the data.
Towards Hybrid-grained Feature Interaction Selection for Deep Sparse Network
Results from experiments on three large real-world benchmark datasets demonstrate that OptFeature performs well in terms of accuracy and efficiency. Additional studies support the feasibility of our method.
Representation Learning for Treatment Effect Estimation from Observational Data
Liuyi Yao, Sheng Li, Yaliang Li, Mengdi Huai, Jing Gao, Aidong Zhang
Neural Information Processing Systems http://nips.cc/
dist(x,y) andavg(A,B) = 1 |A| |B| X
In this paper, we present a comprehensive study of the performance of average-link in metric spaces, regarding several natural criteria that capture separability and cohesion, and aremore interpretable than Dasgupta'scost function and itsvariants.
A no-regret generalization of hierarchical softmax to extreme multi-label classification
Marek Wydmuch, Kalina Jasinska, Mikhail Kuznetsov, Róbert Busa-Fekete, Krzysztof Dembczynski
Neural Information Processing Systems http://nips.cc/
