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Found 6 papers, 1 papers with code
Neural Datalog Through Time: Informed Temporal Modeling via Logical Specification
Learning how to predict future events from patterns of past events is difficult when the set of possible event types is large.
NSTM: Real-Time Query-Driven News Overview Composition at Bloomberg
Millions of news articles from hundreds of thousands of sources around the globe appear in news aggregators every day.
Informed Temporal Modeling via Logical Specification of Factorial LSTMs
Consider a world in which events occur that involve various entities.
Understanding Goal-Oriented Active Learning via Influence Functions
Active learning (AL) concerns itself with learning a model from as few labelled data as possible through actively and iteratively querying an oracle with selected unlabelled samples.
Fast Parallel SVM using Data Augmentation
As one of the most popular classifiers, linear SVMs still have challenges in dealing with very large-scale problems, even though linear or sub-linear algorithms have been developed recently on single machines.
Distributed Bayesian Posterior Sampling via Moment Sharing
We propose a distributed Markov chain Monte Carlo (MCMC) inference algorithm for large scale Bayesian posterior simulation.
