
Real World Games Look Like Spinning Tops
This paper investigates the geometrical properties of real world games (...
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Minimax Theorem for Latent Games or: How I Learned to Stop Worrying about MixedNash and Love Neural Nets
Adversarial training, a special case of multiobjective optimization, is...
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A Deep Neural Network's Loss Surface Contains Every Lowdimensional Pattern
The work "Loss Landscape Sightseeing with MultiPoint Optimization" (Sko...
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Distilling Policy Distillation
The transfer of knowledge from one policy to another is an important too...
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Mix&Match  Agent Curricula for Reinforcement Learning
We introduce Mix&Match (M&M)  a training framework designed to facilita...
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Kickstarting Deep Reinforcement Learning
We present a method for using previouslytrained 'teacher' agents to kic...
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Population Based Training of Neural Networks
Neural networks dominate the modern machine learning landscape, but thei...
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Distral: Robust Multitask Reinforcement Learning
Most deep reinforcement learning algorithms are data inefficient in comp...
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Grounded Language Learning in a Simulated 3D World
We are increasingly surrounded by artificially intelligent technology th...
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ValueDecomposition Networks For Cooperative MultiAgent Learning
We study the problem of cooperative multiagent reinforcement learning w...
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Understanding Synthetic Gradients and Decoupled Neural Interfaces
When training neural networks, the use of Synthetic Gradients (SG) allow...
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How to evaluate word embeddings? On importance of data efficiency and simple supervised tasks
Maybe the single most important goal of representation learning is makin...
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Local minima in training of neural networks
There has been a lot of recent interest in trying to characterize the er...
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Reinforcement Learning with Unsupervised Auxiliary Tasks
Deep reinforcement learning agents have achieved stateoftheart result...
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Decoupled Neural Interfaces using Synthetic Gradients
Training directed neural networks typically requires forwardpropagating...
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Learning to SMILE(S)
This paper shows how one can directly apply natural language processing ...
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On the consistency of Multithreshold Entropy Linear Classifier
Multithreshold Entropy Linear Classifier (MELC) is a recent classifier i...
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Fast optimization of Multithreshold Entropy Linear Classifier
Multithreshold Entropy Linear Classifier (MELC) is a density based model...
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Multithreshold Entropy Linear Classifier
Linear classifiers separate the data with a hyperplane. In this paper we...
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