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06/20/2023
RoboCat: A Self-Improving Foundation Agent for Robotic Manipulation
The ability to leverage heterogeneous robotic experience from different ...
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06/16/2023
π2vec: Policy Representations with Successor Features
This paper describes π2vec, a method for representing behaviors of black...
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03/13/2023
Vision-Language Models as Success Detectors
Detecting successful behaviour is crucial for training intelligent agent...
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07/01/2021
Interactive decoding of words from visual speech recognition models
This work describes an interactive decoding method to improve the perfor...
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06/18/2021
Active Offline Policy Selection
This paper addresses the problem of policy selection in domains with abu...
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11/27/2020
Offline Learning from Demonstrations and Unlabeled Experience
Behavior cloning (BC) is often practical for robot learning because it a...
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11/06/2020
Large-scale multilingual audio visual dubbing
We describe a system for large-scale audiovisual translation and dubbing...
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11/01/2019
Positive-Unlabeled Reward Learning
Learning reward functions from data is a promising path towards achievin...
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10/02/2019
Task-Relevant Adversarial Imitation Learning
We show that a critical problem in adversarial imitation from high-dimen...
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09/26/2019
A Framework for Data-Driven Robotics
We present a framework for data-driven robotics that makes use of a larg...
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09/03/2019
Making Efficient Use of Demonstrations to Solve Hard Exploration Problems
This paper introduces R2D3, an agent that makes efficient use of demonst...
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05/24/2018
Hyperbolic Attention Networks
We introduce hyperbolic attention networks to endow neural networks with...
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04/17/2018
Learning Awareness Models
We consider the setting of an agent with a fixed body interacting with a...
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07/11/2017
The Intentional Unintentional Agent: Learning to Solve Many Continuous Control Tasks Simultaneously
This paper introduces the Intentional Unintentional (IU) agent. This age...
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06/20/2017
Programmable Agents
We build deep RL agents that execute declarative programs expressed in f...
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03/14/2017
Learned Optimizers that Scale and Generalize
Learning to learn has emerged as an important direction for achieving ar...
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11/11/2016
Learning to Learn without Gradient Descent by Gradient Descent
We learn recurrent neural network optimizers trained on simple synthetic...
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11/11/2016
Learning to Navigate in Complex Environments
Learning to navigate in complex environments with dynamic elements is an...
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11/06/2016
Learning to Perform Physics Experiments via Deep Reinforcement Learning
When encountering novel objects, humans are able to infer a wide range o...
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06/14/2016
Learning to learn by gradient descent by gradient descent
The move from hand-designed features to learned features in machine lear...
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03/01/2016
Noisy Activation Functions
Common nonlinear activation functions used in neural networks can cause ...
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11/18/2015
ACDC: A Structured Efficient Linear Layer
The linear layer is one of the most pervasive modules in deep learning r...
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12/22/2014
Deep Fried Convnets
The fully connected layers of a deep convolutional neural network typica...
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12/21/2014
Extraction of Salient Sentences from Labelled Documents
We present a hierarchical convolutional document model with an architect...
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11/12/2014
Deep Multi-Instance Transfer Learning
We present a new approach for transferring knowledge from groups to indi...
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10/04/2013
Narrowing the Gap: Random Forests In Theory and In Practice
Despite widespread interest and practical use, the theoretical propertie...
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08/29/2013
Linear and Parallel Learning of Markov Random Fields
We introduce a new embarrassingly parallel parameter learning algorithm ...
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06/03/2013
Predicting Parameters in Deep Learning
We demonstrate that there is significant redundancy in the parameterizat...
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02/20/2013
Consistency of Online Random Forests
As a testament to their success, the theory of random forests has long b...
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08/04/2012
Recklessly Approximate Sparse Coding
It has recently been observed that certain extremely simple feature enco...
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09/16/2011
Learning where to Attend with Deep Architectures for Image Tracking
We discuss an attentional model for simultaneous object tracking and rec...
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09/16/2011
