From the 1 of 1.6k papers with an AI index.
24.4k citations
- University of California, BerkeleyUS97 papers
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52 papers · 1 filter
Interaction Networks for Learning about Objects, Relations and Physics
Peter W. Battaglia, Razvan Pascanu, Matthew Lai +2
Reasoning about objects, relations, and physics is central to human intelligence, and a key goal of artificial intelligence. Here we introduce the interaction network, a model whic…
Learning to Compose Words into Sentences with Reinforcement Learning
Dani Yogatama, Phil Blunsom, Chris Dyer +2
We use reinforcement learning to learn tree-structured neural networks for computing representations of natural language sentences. In contrast with prior work on tree-structured m…
Coded Caching with Distributed Storage
Tianqiong Luo, Vaneet Aggarwal, Borja Peleato
Content delivery networks store information distributed across multiple servers, so as to balance the load and avoid unrecoverable losses in case of node or disk failures. Coded ca…
Reinforcement Learning with Unsupervised Auxiliary Tasks
Max Jaderberg, Volodymyr Mnih, Wojciech Marian Czarnecki +4
Deep reinforcement learning agents have achieved state-of-the-art results by directly maximising cumulative reward. However, environments contain a much wider variety of possible t…
A Generic Coordinate Descent Framework for Learning from Implicit Feedback
Immanuel Bayer, Xiangnan He, Bhargav Kanagal +1
In recent years, interest in recommender research has shifted from explicit feedback towards implicit feedback data. A diversity of complex models has been proposed for a wide vari…
Neural Combinatorial Optimization with Reinforcement Learning
Irwan Bello, Hieu Pham, Quoc V. Le +2
This paper presents a framework to tackle combinatorial optimization problems using neural networks and reinforcement learning. We focus on the traveling salesman problem (TSP) and…