
SemiSupervised Learning of Visual Features by NonParametrically Predicting View Assignments with Support Samples
This paper proposes a novel method of learning by predicting view assign...
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A Closer Look at Codistillation for Distributed Training
Codistillation has been proposed as a mechanism to share knowledge among...
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Advances in Asynchronous Parallel and Distributed Optimization
Motivated by largescale optimization problems arising in the context of...
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Recovering Petaflops in Contrastive SemiSupervised Learning of Visual Representations
We investigate a strategy for improving the computational efficiency of ...
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On the Convergence of Nesterov's Accelerated Gradient Method in Stochastic Settings
We study Nesterov's accelerated gradient method in the stochastic approx...
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Advancing machine learning for MR image reconstruction with an open competition: Overview of the 2019 fastMRI challenge
Purpose: To advance research in the field of machine learning for MR ima...
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SlowMo: Improving CommunicationEfficient Distributed SGD with Slow Momentum
Distributed optimization is essential for training large models on large...
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A GraphCNN for 3D Point Cloud Classification
Graph convolutional neural networks (GraphCNNs) extend traditional CNNs...
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Stochastic Gradient Push for Distributed Deep Learning
Large minibatch parallel SGD is commonly used for distributed training ...
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fastMRI: An Open Dataset and Benchmarks for Accelerated MRI
Accelerating Magnetic Resonance Imaging (MRI) by taking fewer measuremen...
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Provably Accelerated Randomized Gossip Algorithms
In this work we present novel provably accelerated gossip algorithms for...
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TarMAC: Targeted MultiAgent Communication
We explore a collaborative multiagent reinforcement learning setting wh...
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Learning Graphs from Data: A Signal Representation Perspective
The construction of a meaningful graph topology plays a crucial role in ...
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Asynchronous SubgradientPush
We consider a multiagent framework for distributed optimization where e...
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Memory vectors for similarity search in highdimensional spaces
We study an indexing architecture to store and search in a database of h...
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Storing sequences in binary tournamentbased neural networks
An extension to a recently introduced architecture of cliquebased neura...
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Improving Sparse Associative Memories by Escaping from Bogus Fixed Points
The GriponBerrou neural network (GBNN) is a recently invented recurrent...
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GANC: Greedy Agglomerative Normalized Cut
This paper describes a graph clustering algorithm that aims to minimize ...
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Greedy Gossip with Eavesdropping
This paper presents greedy gossip with eavesdropping (GGE), a novel rand...
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Michael Rabbat
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