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Found 5 papers, 1 papers with code
Representation Learning via Variational Bayesian Networks
We present Variational Bayesian Network (VBN) - a novel Bayesian entity representation learning model that utilizes hierarchical and relational side information and is particularly useful for modeling entities in the ``long-tail'', where the data is scarce.
On the Evolution of Word Order
We also show that adding information to the sentence, such as case markers and noun-verb distinction, reduces the need for fixed word order, in accordance with the typological findings.
Bayesian Hierarchical Words Representation Learning
BHWR facilitates Variational Bayes word representation learning combined with semantic taxonomy modeling via hierarchical priors.
Top-k Combinatorial Bandits with Full-Bandit Feedback
Top-k Combinatorial Bandits generalize multi-armed bandits, where at each round any subset of $k$ out of $n$ arms may be chosen and the sum of the rewards is gained.
Inducing Regular Grammars Using Recurrent Neural Networks
Grammar induction is the task of learning a grammar from a set of examples.
