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Found 6 papers, 3 papers with code
Risk-Conditioned Distributional Soft Actor-Critic for Risk-Sensitive Navigation
Modern navigation algorithms based on deep reinforcement learning (RL) show promising efficiency and robustness.
From handcrafted to deep local features
This paper presents an overview of the evolution of local features from handcrafted to deep-learning-based methods, followed by a discussion of several benchmarks and papers evaluating such local features.
On Inductive Abilities of Latent Factor Models for Relational Learning
Latent factor models are increasingly popular for modeling multi-relational knowledge graphs.
Optimal Policies for Observing Time Series and Related Restless Bandit Problems
We discuss computation of that index, give closed-form formulae for it, and compare the performance of the associated index policy with heuristic policies.
Knowledge Graph Completion via Complex Tensor Factorization
In statistical relational learning, knowledge graph completion deals with automatically understanding the structure of large knowledge graphs---labeled directed graphs---and predicting missing relationships---labeled edges.
Ranked #2 on
Knowledge Graphs
on FB15k
When are Kalman-filter restless bandits indexable?
We study the restless bandit associated with an extremely simple scalar Kalman filter model in discrete time.
