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05/31/2022
The CLRS Algorithmic Reasoning Benchmark
Learning representations of algorithms is an emerging area of machine le...
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02/02/2022
Unified Scaling Laws for Routed Language Models
The performance of a language model has been shown to be effectively mod...
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07/20/2021
Large-scale graph representation learning with very deep GNNs and self-supervision
Effectively and efficiently deploying graph neural networks (GNNs) at sc...
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10/23/2020
A Combinatorial Perspective on Transfer Learning
Human intelligence is characterized not only by the capacity to learn co...
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06/10/2020
Gaussian Gated Linear Networks
We propose the Gaussian Gated Linear Network (G-GLN), an extension to th...
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02/21/2020
Online Learning in Contextual Bandits using Gated Linear Networks
We introduce a new and completely online contextual bandit algorithm cal...
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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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09/30/2019
Gated Linear Networks
This paper presents a family of backpropagation-free neural architecture...
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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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09/12/2019
Modular Meta-Learning with Shrinkage
Most gradient-based approaches to meta-learning do not explicitly accoun...
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02/05/2019
A Generalized Framework for Population Based Training
Population Based Training (PBT) is a recent approach that jointly optimi...
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02/01/2019
TF-Replicator: Distributed Machine Learning for Researchers
We describe TF-Replicator, a framework for distributed machine learning ...
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10/11/2018
One-Shot High-Fidelity Imitation: Training Large-Scale Deep Nets with RL
Humans are experts at high-fidelity imitation -- closely mimicking a dem...
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09/27/2018
Sample Efficient Adaptive Text-to-Speech
We present a meta-learning approach for adaptive text-to-speech (TTS) wi...
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05/29/2018
Observe and Look Further: Achieving Consistent Performance on Atari
Despite significant advances in the field of deep Reinforcement Learning...
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05/29/2018
Playing hard exploration games by watching YouTube
Deep reinforcement learning methods traditionally struggle with tasks wh...
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04/23/2018
Distributed Distributional Deterministic Policy Gradients
This work adopts the very successful distributional perspective on reinf...
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03/02/2018
Distributed Prioritized Experience Replay
We propose a distributed architecture for deep reinforcement learning at...
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01/02/2018
DeepMind Control Suite
The DeepMind Control Suite is a set of continuous control tasks with a s...
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03/04/2017
Generative Compression
Traditional image and video compression algorithms rely on hand-crafted ...
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02/23/2017
Toward Streaming Synapse Detection with Compositional ConvNets
Connectomics is an emerging field in neuroscience that aims to reconstru...
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12/07/2016
A Multi-Pass Approach to Large-Scale Connectomics
The field of connectomics faces unprecedented "big data" challenges. To ...
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11/20/2016
Deep Tensor Convolution on Multicores
Deep convolutional neural networks (ConvNets) of 3-dimensional kernels a...
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10/31/2014
Addressing the non-functional requirements of computer vision systems: A case study
Computer vision plays a major role in the robotics industry, where visio...
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03/17/2014
Simulation leagues: Analysis of competition formats
The selection of an appropriate competition format is critical for both ...
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10/22/2013