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07/24/2021
Algorithmic Bias and Data Bias: Understanding the Relation between Distributionally Robust Optimization and Data Curation
Machine learning systems based on minimizing average error have been sho...
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07/24/2021
Linear unit-tests for invariance discovery
There is an increasing interest in algorithms to learn invariant correla...
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07/24/2021
Inductive Bias and Language Expressivity in Emergent Communication
Referential games and reconstruction games are the most common game type...
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07/24/2021
Neural Function Modules with Sparse Arguments: A Dynamic Approach to Integrating Information across Layers
Feed-forward neural networks consist of a sequence of layers, in which e...
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07/24/2021
Bayesian Optimisation for Premise Selection in Automated Theorem Proving (Student Abstract)
Modern theorem provers utilise a wide array of heuristics to control the...
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07/24/2021
Structural Inductive Biases in Emergent Communication
In order to communicate, humans flatten a complex representation of idea...
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07/24/2021
Analyzing Structural Priors in Multi-Agent Communication
Human language and thought are characterized by the ability to systemati...
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07/24/2021
Towards Graph Representation Learning in Emergent Communication
Recent findings in neuroscience suggest that the human brain represents ...
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07/24/2021
Spatial Graph Convolutional Networks
Graph Convolutional Networks (GCNs) have recently be- come the primary ...
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09/18/2019
Bayesian Optimisation with Gaussian Processes for Premise Selection
Heuristics in theorem provers are often parameterised. Modern theorem pr...
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09/11/2019
Geometric Graph Convolutional Neural Networks
Graph Convolutional Networks (GCNs) have recently become the primary cho...
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07/23/2019
Completing partial recipes using item-based collaborative filtering to recommend ingredients
Increased public interest in healthy lifestyles has motivated the study ...
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11/01/2018
