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Found 6 papers, 1 papers with code
Towards Better Understanding with Uniformity and Explicit Regularization of Embeddings in Embedding-based Neural Topic Models
In this paper, we propose an embedding regularized neural topic model, which applies the specially designed training constraints on word embedding and topic embedding to reduce the optimization space of parameters.
Zero-shot Cross-lingual Conversational Semantic Role Labeling
While conversational semantic role labeling (CSRL) has shown its usefulness on Chinese conversational tasks, it is still under-explored in non-Chinese languages due to the lack of multilingual CSRL annotations for the parser training.
Phocus: Picking Valuable Research from a Sea of Citations
The global influential factor of the reference to the citing paper is the product of the local influential factor and the total influential factor of the citing paper.
Multi-Complementary and Unlabeled Learning for Arbitrary Losses and Models
We first give an unbiased estimator of the classification risk from samples with multiple complementary labels, and then further improve the estimator by incorporating unlabeled samples into the risk formulation.
Ranked #20 on
Image Classification
on Kuzushiji-MNIST
Efficient Multi-robot Exploration via Multi-head Attention-based Cooperation Strategy
The goal of coordinated multi-robot exploration tasks is to employ a team of autonomous robots to explore an unknown environment as quickly as possible.
Attention-based Fault-tolerant Approach for Multi-agent Reinforcement Learning Systems
The aim of multi-agent reinforcement learning systems is to provide interacting agents with the ability to collaboratively learn and adapt to the behavior of other agents.
Multi-agent Reinforcement Learning
reinforcement-learning
+1
