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An Information-Theoretic Perspective on Credit Assignment in Reinforcement Learning
How do we formalize the challenge of credit assignment in reinforcement ...
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With Little Power Comes Great Responsibility
Despite its importance to experimental design, statistical power (the pr...
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Ideas for Improving the Field of Machine Learning: Summarizing Discussion from the NeurIPS 2019 Retrospectives Workshop
This report documents ideas for improving the field of machine learning,...
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TDprop: Does Jacobi Preconditioning Help Temporal Difference Learning?
We investigate whether Jacobi preconditioning, accounting for the bootst...
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Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims
With the recent wave of progress in artificial intelligence (AI) has com...
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Towards the Systematic Reporting of the Energy and Carbon Footprints of Machine Learning
Accurate reporting of energy and carbon usage is essential for understan...
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Separating value functions across time-scales
In many finite horizon episodic reinforcement learning (RL) settings, it...
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Distilling Information from a Flood: A Possibility for the Use of Meta-Analysis and Systematic Review in Machine Learning Research
The current flood of information in all areas of machine learning resear...
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An Introduction to Deep Reinforcement Learning
Deep reinforcement learning is the combination of reinforcement learning...
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The RLLChatbot: a solution to the ConvAI Challenge
Current conversational systems can follow simple commands and answer bas...
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Adversarial Gain
Adversarial examples can be defined as inputs to a model which induce a ...
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Where Did My Optimum Go?: An Empirical Analysis of Gradient Descent Optimization in Policy Gradient Methods
Recent analyses of certain gradient descent optimization methods have sh...
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Reward Estimation for Variance Reduction in Deep Reinforcement Learning
In reinforcement learning (RL), stochastic environments can make learnin...
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Learning Robust Dialog Policies in Noisy Environments
Modern virtual personal assistants provide a convenient interface for co...
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Ethical Challenges in Data-Driven Dialogue Systems
The use of dialogue systems as a medium for human-machine interaction is...
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Underwater Multi-Robot Convoying using Visual Tracking by Detection
We present a robust multi-robot convoying approach that relies on visual...
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Cost Adaptation for Robust Decentralized Swarm Behaviour
The multi-agent swarm system is a robust paradigm which can drive effici...
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Deep Reinforcement Learning that Matters
In recent years, significant progress has been made in solving challengi...
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Benchmark Environments for Multitask Learning in Continuous Domains
As demand drives systems to generalize to various domains and problems, ...
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A Survey of Available Corpora for Building Data-Driven Dialogue Systems
During the past decade, several areas of speech and language understandi...
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