206 citations · 386 across the 7 of their papers we have counts for
7 papers
Using Learned Indexes to Improve Time Series Indexing Performance on Embedded Sensor Devices
David Ding, Ivan Carvalho, Ramon Lawrence
Efficiently querying data on embedded sensor and IoT devices is challenging given the very limited memory and CPU resources. With the increasing volumes of collected data, it is cr…
Know your audience: specializing grounded language models with listener subtraction
Aaditya K. Singh, David Ding, Andrew Saxe +2
Effective communication requires adapting to the idiosyncrasies of each communicative context--such as the common ground shared with each partner. Humans demonstrate this ability t…
Perceiver IO: A General Architecture for Structured Inputs & Outputs
Andrew Jaegle, Sebastian Borgeaud, Jean-Baptiste Alayrac +12
A central goal of machine learning is the development of systems that can solve many problems in as many data domains as possible. Current architectures, however, cannot be applied…
Attention over learned object embeddings enables complex visual reasoning
David Ding, Felix Hill, Adam Santoro +2
Neural networks have achieved success in a wide array of perceptual tasks but often fail at tasks involving both perception and higher-level reasoning. On these more challenging ta…
Adapting Behaviour for Learning Progress
Tom Schaul, Diana Borsa, David Ding +4
Determining what experience to generate to best facilitate learning (i.e. exploration) is one of the distinguishing features and open challenges in reinforcement learning. The adve…
OpenSpiel: A Framework for Reinforcement Learning in Games
Marc Lanctot, Edward Lockhart, Jean-Baptiste Lespiau +24
OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games. OpenSpiel supports n-player (single- and multi…