Alexandre Galashov | DeepAI

AI Chat

Featured Co-authors

Zhe Wang
161 publications
Yee Whye Teh
122 publications
Nicolas Heess
104 publications
Pushmeet Kohli
93 publications
Remi Munos
89 publications
Razvan Pascanu
87 publications
Michal Valko
73 publications
Karl Tuyls
50 publications
Marc'Aurelio Ranzato
47 publications
Thore Graepel
46 publications
Laurent Charlin
43 publications

∙ 06/14/2023

Kalman Filter for Online Classification of Non-Stationary Data

In Online Continual Learning (OCL) a learning system receives a stream o...

0 Michalis K. Titsias, et al. ∙

∙ 04/25/2023

Towards Compute-Optimal Transfer Learning

The field of transfer learning is undergoing a significant shift with th...

0 Massimo Caccia, et al. ∙

∙ 05/23/2022

Data augmentation for efficient learning from parametric experts

We present a simple, yet powerful data-augmentation technique to enable ...

0 Alexandre Galashov, et al. ∙

∙ 11/18/2020

Game Plan: What AI can do for Football, and What Football can do for AI

The rapid progress in artificial intelligence (AI) and machine learning ...

11 Karl Tuyls, et al. ∙

∙ 10/27/2020

Behavior Priors for Efficient Reinforcement Learning

As we deploy reinforcement learning agents to solve increasingly challen...

10 Dhruva Tirumala, et al. ∙

∙ 10/16/2020

Learning Dexterous Manipulation from Suboptimal Experts

Learning dexterous manipulation in high-dimensional state-action spaces ...

0 Rae Jeong, et al. ∙

∙ 09/10/2020

Importance Weighted Policy Learning and Adaption

The ability to exploit prior experience to solve novel problems rapidly ...

6 Alexandre Galashov, et al. ∙

∙ 09/07/2020

Information Theoretic Meta Learning with Gaussian Processes

We formulate meta learning using information theoretic concepts such as ...

0 Michalis K. Titsias, et al. ∙

∙ 06/12/2019

Task Agnostic Continual Learning via Meta Learning

While neural networks are powerful function approximators, they suffer f...

0 Xu He, et al. ∙

∙ 05/15/2019

Meta reinforcement learning as task inference

Humans achieve efficient learning by relying on prior knowledge about th...

5 Jan Humplik, et al. ∙

∙ 05/03/2019

Information asymmetry in KL-regularized RL

Many real world tasks exhibit rich structure that is repeated across dif...

6 Alexandre Galashov, et al. ∙

∙ 03/28/2019

Meta-Learning surrogate models for sequential decision making

Meta-learning methods leverage past experience to learn data-driven indu...

22 Alexandre Galashov, et al. ∙

∙ 03/18/2019

Exploiting Hierarchy for Learning and Transfer in KL-regularized RL

As reinforcement learning agents are tasked with solving more challengin...

20 Dhruva Tirumala, et al. ∙

∙ 11/28/2018

Neural probabilistic motor primitives for humanoid control

We focus on the problem of learning a single motor module that can flexi...

12 Josh Merel, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world