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Found 5 papers, 3 papers with code
Learning from Drivers to Tackle the Amazon Last Mile Routing Research Challenge
On the one hand, our method encodes driver know-how by learning a sequential probability model from historical routes at the zone level, where each zone contains a few parcel stops.
A Position-aware Bidirectional Attention Network for Aspect-level Sentiment Analysis
PBAN not only concentrates on the position information of aspect terms, but also mutually models the relation between aspect term and sentence by employing bidirectional attention mechanism.
Aspect-Based Sentiment Analysis (ABSA)
Feature Engineering
+2
A Potts-Mixture Spatiotemporal Joint Model for Combined MEG and EEG Data
Our new model incorporates two major extensions: (i) We combine EEG and MEG data together and formulate a joint model for dealing with the two modalities simultaneously; (ii) we incorporate the Potts model to represent the spatial dependence in an allocation process that partitions the cortical surface into a small number of latent states termed mesostates.
Applications
Learning Hidden Structures with Relational Models by Adequately Involving Rich Information in A Network
In this work, we propose an informative relational model (InfRM) framework to adequately involve rich information and its granularity in a network, including metadata information about each entity and various forms of link data.
Characterizing A Database of Sequential Behaviors with Latent Dirichlet Hidden Markov Models
These sequence-level latent parameters for each sequence are modeled as latent Dirichlet random variables and parameterized by a set of deterministic database-level hyper-parameters.
