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08/24/2023
APART: Diverse Skill Discovery using All Pairs with Ascending Reward and DropouT
We study diverse skill discovery in reward-free environments, aiming to ...
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08/17/2023
Diversifying AI: Towards Creative Chess with AlphaZero
In recent years, Artificial Intelligence (AI) systems have surpassed hum...
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12/30/2022
POMRL: No-Regret Learning-to-Plan with Increasing Horizons
We study the problem of planning under model uncertainty in an online me...
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10/19/2022
Palm up: Playing in the Latent Manifold for Unsupervised Pretraining
Large and diverse datasets have been the cornerstones of many impressive...
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09/09/2021
Bootstrapped Meta-Learning
Meta-learning empowers artificial intelligence to increase its efficienc...
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06/21/2021
Emphatic Algorithms for Deep Reinforcement Learning
Off-policy learning allows us to learn about possible policies of behavi...
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06/01/2021
Reward is enough for convex MDPs
Maximising a cumulative reward function that is Markov and stationary, i...
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02/13/2021
Online Apprenticeship Learning
In Apprenticeship Learning (AL), we are given a Markov Decision Process ...
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02/12/2021
Discovery of Options via Meta-Learned Subgoals
Temporal abstractions in the form of options have been shown to help rei...
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02/07/2021
Online Limited Memory Neural-Linear Bandits with Likelihood Matching
We study neural-linear bandits for solving problems where both explorati...
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10/13/2020
Balancing Constraints and Rewards with Meta-Gradient D4PG
Deploying Reinforcement Learning (RL) agents to solve real-world applica...
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03/31/2020
Learning to Ask Medical Questions using Reinforcement Learning
We propose a novel reinforcement learning-based approach for adaptive an...
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02/28/2020
Self-Tuning Deep Reinforcement Learning
Reinforcement learning (RL) algorithms often require expensive manual or...
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11/23/2019
Deep learning reconstruction of ultrashort pulses from 2D spatial intensity patterns recorded by an all-in-line system in a single-shot
We propose a simple all-in-line single-shot scheme for diagnostics of ul...
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11/05/2019
Apprenticeship Learning via Frank-Wolfe
We consider the applications of the Frank-Wolfe (FW) algorithm for Appre...
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05/23/2019
Inverse Reinforcement Learning in Contextual MDPs
We consider the Inverse Reinforcement Learning (IRL) problem in Contextu...
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05/23/2019
Average reward reinforcement learning with unknown mixing times
We derive and analyze learning algorithms for policy evaluation, apprent...
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05/23/2019
Action Assembly: Sparse Imitation Learning for Text Based Games with Combinatorial Action Spaces
We propose a computationally efficient algorithm that combines compresse...
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02/26/2019
Planning in Hierarchical Reinforcement Learning: Guarantees for Using Local Policies
We consider a settings of hierarchical reinforcement learning, in which ...
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01/24/2019
Deep Neural Linear Bandits: Overcoming Catastrophic Forgetting through Likelihood Matching
We study the neural-linear bandit model for solving sequential decision-...
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09/06/2018
Learn What Not to Learn: Action Elimination with Deep Reinforcement Learning
Learning how to act when there are many available actions in each state ...
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03/15/2018
Deep Learning Reconstruction of Ultra-Short Pulses
Ultra-short laser pulses with femtosecond to attosecond pulse duration a...
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03/13/2018
Hierarchical Reinforcement Learning: Approximating Optimal Discounted TSP Using Local Policies
In this work, we provide theoretical guarantees for reward decomposition...
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02/16/2018
Train on Validation: Squeezing the Data Lemon
Model selection on validation data is an essential step in machine learn...
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05/21/2017
Shallow Updates for Deep Reinforcement Learning
Deep reinforcement learning (DRL) methods such as the Deep Q-Network (DQ...
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11/29/2016
Is a picture worth a thousand words? A Deep Multi-Modal Fusion Architecture for Product Classification in e-commerce
Classifying products into categories precisely and efficiently is a majo...
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06/22/2016
Visualizing Dynamics: from t-SNE to SEMI-MDPs
Deep Reinforcement Learning (DRL) is a trending field of research, showi...
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06/16/2016
Deep Reinforcement Learning Discovers Internal Models
Deep Reinforcement Learning (DRL) is a trending field of research, showi...
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02/08/2016
Graying the black box: Understanding DQNs
In recent years there is a growing interest in using deep representation...
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02/07/2016