
A Machine of Few Words – Interactive Speaker Recognition with Reinforcement Learning
Speaker recognition is a well known and studied task in the speech proce...
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Munchausen Reinforcement Learning
Bootstrapping is a core mechanism in Reinforcement Learning (RL). Most a...
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The Monte Carlo Transformer: a stochastic selfattention model for sequence prediction
This paper introduces the Sequential Monte Carlo Transformer, an origina...
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Fictitious Play for Mean Field Games: Continuous Time Analysis and Applications
In this paper, we deepen the analysis of continuous time Fictitious Play...
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Show me the Way: Intrinsic Motivation from Demonstrations
The study of exploration in Reinforcement Learning (RL) has a long histo...
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What Matters In OnPolicy Reinforcement Learning? A LargeScale Empirical Study
In recent years, onpolicy reinforcement learning (RL) has been successf...
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Primal Wasserstein Imitation Learning
Imitation Learning (IL) methods seek to match the behavior of an agent w...
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Reinforcement Learning
Reinforcement learning (RL) is a general framework for adaptive control,...
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Leverage the Average: an Analysis of Regularization in RL
Building upon the formalism of regularized Markov decision processes, we...
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Countering Language Drift with Seeded Iterated Learning
Supervised learning methods excel at capturing statistical properties of...
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SelfEducated Language Agent With Hindsight Experience Replay For Instruction Following
Language creates a compact representation of the world and allows the de...
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Momentum in Reinforcement Learning
We adapt the optimization's concept of momentum to reinforcement learnin...
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On Connections between Constrained Optimization and Reinforcement Learning
Dynamic Programming (DP) provides standard algorithms to solve Markov De...
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"I'm sorry Dave, I'm afraid I can't do that" Deep Qlearning from forbidden action
The use of Reinforcement Learning (RL) is still restricted to simulation...
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Credit Assignment as a Proxy for Transfer in Reinforcement Learning
The ability to transfer representations to novel environments and tasks ...
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Approximate Fictitious Play for Mean Field Games
The theory of Mean Field Games (MFG) allows characterizing the Nash equi...
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MULEX: Disentangling Exploitation from Exploration in Deep RL
An agent learning through interactions should balance its action selecti...
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Foolproof Cooperative Learning
This paper extends the notion of equilibrium in game theory to learning ...
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Deep Conservative Policy Iteration
Conservative Policy Iteration (CPI) is a founding algorithm of Approxima...
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Targeted Attacks on Deep Reinforcement Learning Agents through Adversarial Observations
This paper deals with adversarial attacks on perceptions of neural netwo...
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Scaling up budgeted reinforcement learning
Can we learn a control policy able to adapt its behaviour in real time s...
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A Theory of Regularized Markov Decision Processes
Many recent successful (deep) reinforcement learning algorithms make use...
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Playing the Game of Universal Adversarial Perturbations
We study the problem of learning classifiers robust to universal adversa...
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Visual Reasoning with Multihop Feature Modulation
Recent breakthroughs in computer vision and natural language processing ...
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Observe and Look Further: Achieving Consistent Performance on Atari
Despite significant advances in the field of deep Reinforcement Learning...
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EndtoEnd Automatic Speech Translation of Audiobooks
We investigate endtoend speechtotext translation on a corpus of audi...
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Leveraging Demonstrations for Deep Reinforcement Learning on Robotics Problems with Sparse Rewards
We propose a general and modelfree approach for Reinforcement Learning ...
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LIGCRIStAL System for the WMT17 Automatic PostEditing Task
This paper presents the LIGCRIStAL submission to the shared Automatic P...
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Modulating early visual processing by language
It is commonly assumed that language refers to highlevel visual concept...
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Noisy Networks for Exploration
We introduce NoisyNet, a deep reinforcement learning agent with parametr...
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Observational Learning by Reinforcement Learning
Observational learning is a type of learning that occurs as a function o...
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Deep Qlearning from Demonstrations
Deep reinforcement learning (RL) has achieved several high profile succe...
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Endtoend optimization of goaldriven and visually grounded dialogue systems
Endtoend design of dialogue systems has recently become a popular rese...
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Listen and Translate: A Proof of Concept for EndtoEnd SpeechtoText Translation
This paper proposes a first attempt to build an endtoend speechtotex...
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GuessWhat?! Visual object discovery through multimodal dialogue
We introduce GuessWhat?!, a twoplayer guessing game as a testbed for re...
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Is the Bellman residual a bad proxy?
This paper aims at theoretically and empirically comparing two standard ...
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Difference of Convex Functions Programming Applied to Control with Expert Data
This paper reports applications of Difference of Convex functions (DC) p...
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