
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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Linear unittests for invariance discovery
There is an increasing interest in algorithms to learn invariant correla...
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Inductive Bias and Language Expressivity in Emergent Communication
Referential games and reconstruction games are the most common game type...
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Neural Function Modules with Sparse Arguments: A Dynamic Approach to Integrating Information across Layers
Feedforward neural networks consist of a sequence of layers, in which e...
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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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Structural Inductive Biases in Emergent Communication
In order to communicate, humans flatten a complex representation of idea...
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Analyzing Structural Priors in MultiAgent Communication
Human language and thought are characterized by the ability to systemati...
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Towards Graph Representation Learning in Emergent Communication
Recent findings in neuroscience suggest that the human brain represents ...
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Spatial Graph Convolutional Networks
Graph Convolutional Networks (GCNs) have recently be come the primary ...
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Bayesian Optimisation with Gaussian Processes for Premise Selection
Heuristics in theorem provers are often parameterised. Modern theorem pr...
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Geometric Graph Convolutional Neural Networks
Graph Convolutional Networks (GCNs) have recently become the primary cho...
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Completing partial recipes using itembased collaborative filtering to recommend ingredients
Increased public interest in healthy lifestyles has motivated the study ...
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Dilated DenseNets for Relational Reasoning
Despite their impressive performance in many tasks, deep neural networks...
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Agnieszka Słowik
verfied profile
Thirdyear PhD student at the University of Cambridge