Nova Scotia
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- Overview (0.67)
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Tree Variational Autoencoders
TreeV AE hierarchically divides samples according to their intrinsic characteristics, shedding light on hidden structures in the data.
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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.
- Oceania > Australia > New South Wales > Sydney (0.14)
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- Information Technology > Artificial Intelligence > Machine Learning > Statistical Learning (0.93)
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- Information Technology > Artificial Intelligence > Machine Learning > Learning Graphical Models > Directed Networks > Bayesian Learning (0.46)
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/
- North America > United States > California > San Francisco County > San Francisco (0.14)
- Europe > United Kingdom > England > Cambridgeshire > Cambridge (0.04)
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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.
- Europe > Austria > Vienna (0.14)
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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/
- Oceania > Australia > New South Wales > Sydney (0.14)
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