no code implementations • 7 Apr 2021 • Jinyoung Choi, Christopher R. Dance, Jung-eun Kim, Seulbin Hwang, Kyung-sik Park
Modern navigation algorithms based on deep reinforcement learning (RL) show promising efficiency and robustness.
1 code implementation • 26 Jul 2018 • Gabriela Csurka, Christopher R. Dance, Martin Humenberger
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.
1 code implementation • 17 Sep 2017 • Théo Trouillon, Éric Gaussier, Christopher R. Dance, Guillaume Bouchard
Latent factor models are increasingly popular for modeling multi-relational knowledge graphs.
no code implementations • 29 Mar 2017 • Christopher R. Dance, Tomi Silander
We discuss computation of that index, give closed-form formulae for it, and compare the performance of the associated index policy with heuristic policies.
2 code implementations • 22 Feb 2017 • Théo Trouillon, Christopher R. Dance, Johannes Welbl, Sebastian Riedel, Éric Gaussier, Guillaume Bouchard
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
no code implementations • NeurIPS 2015 • Christopher R. Dance, Tomi Silander
We study the restless bandit associated with an extremely simple scalar Kalman filter model in discrete time.