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Found 7 papers, 3 papers with code
Controlling Class Layout for Deep Ordinal Classification via Constrained Proxies Learning
For deep ordinal classification, learning a well-structured feature space specific to ordinal classification is helpful to properly capture the ordinal nature among classes.
End-to-End Learning of User Equilibrium with Implicit Neural Networks
The centerpiece of the proposed framework is to use deep neural networks to represent travelers’ route choice preferences and then encapsulate the neural networks in a variational inequality that prescribes the user equilibrium flow distribution.
Learning to Classify Open Intent via Soft Labeling and Manifold Mixup
In our method, soft labeling is used to reshape the label distribution of the known intent samples, aiming at reducing model's overconfident on known intents.
Real-Time Cross-Fleet Pareto-Improving Truck Platoon Coordination
The profit of each fleet incorporates platooning rewards and costs for waiting at hubs.
Heuristics for Customer-focused Ride-pooling Assignment
Ride-pooling has become an important service option offered by ride-hailing platforms as it serves multiple trip requests in a single ride.
A Symmetric Local Search Network for Emotion-Cause Pair Extraction
Each subnetwork is composed of a clause representation learner and a local pair searcher.
Enriching Word Embeddings with Domain Knowledge for Readability Assessment
In this paper, we present a method which learns the word embedding for readability assessment.
